Sharpe ratio - Forex Education

Sharpe Ratio in FOREX?

I read a few things about how to use Sharpe Ratio to measure a stock portfolio.
Now in FOREX (let's say I only buy/sell EURUSD and nothing else), how to compute a relevant Sharpe Ratio?
submitted by basjj to Forex [link] [comments]

Former investment bank FX trader: Risk management part II

Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Part II
  • Letting stops breathe
  • When to change a stop
  • Entering and exiting winning positions
  • Risk:reward ratios
  • Risk-adjusted returns

Letting stops breathe

We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.

Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.

ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.

Reasons to change a stop

As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.

The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?

Entering and exiting winning positions

Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.

Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.

Entering positions with limit orders

That covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.

Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.

Risk:reward and win ratios

Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.

A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.

Risk-adjusted returns

Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.

Sharpe ratio

The Sharpe ratio works like this:
  • It takes the average returns of your strategy;
  • It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
  • It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent.
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.

VAR

VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.

A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.

Coming up in part III

Available here
Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

Position Sizing and Sharpe Ratio Questions

Hi Everyone,
I recently finished and back tested a Forex trading algo. This is the first ever algo I have built and tested so I have a few questions. For position sizing I have tested out volatility adjusted lot sizing, martingale, and the kelly criterion. All of these produce decent results but the best position sizing is using a single lot for every trade. So, I was wondering if I should keep using one lot as the position sizing until I find something better? My second question is about the Sharpe Ratio. The algo returns good metrics like a 7% drawdown, a 60% winrate, a profit factor of 2.30; however, the Sharpe Ratio is a 0.26. Would you guys recommend any ways to raise this or should I leave the Ratio alone?
Thank you.
submitted by Seabass012901 to algotrading [link] [comments]

Book Review : Basic Python for Finance

tl;dr - way better books out there
so the pros are
  1. it's cheap
  2. it's only 200 pages
cons
  1. it's poorly edited - some sections literally repeat themselves. in his defense it's self published, so proofreading, etc, may have been skipped for costs
  2. uncoded references - sharpe ratio, backtesting, connectivity - all mentioned, no examples given
  3. a number of trading strategies covered, but they're all two liners ( apart from an SMA crossover ), no code, no real discussion on them
in summary - it's a small book about graphing timeseries from pandas really. in parts it comes across as a rehash of other books or web pages, some of the data is lifted straight from other people's projects ( Jason Brownlee, etc ). says it covers stocks and bonds, but there's 5 lines covering bonds. apparently forex traders use timeseries to determines entry and exit points for stocks so, in conclusion, get one of Yves books.
best of luck
Link as requested
https://www.amazon.co.uk/gp/product/1699920257/ref=ppx_yo_dt_b_asin_image_o00_s00?ie=UTF8&psc=1
submitted by EdenHouse81 to algotrading [link] [comments]

An Honest Review of T3 Newsbeat Live

T3 Newsbeat Live is run by Mark Melnick, a 20-year veteran trader from New York. According to him, he made his first million at the age of 19 during the dot-com boom back in the late 90s.
He claims that his trading room is the fastest growing trading room at T3 and also the Wall Street’s #1 trading room. You can see this in the description of his videos on Youtube.
He is a big proponent of reaching the highest win rate possible in trading. He openly shares some of his trading strategies in free videos and claims that some of his strategies are batting over 70% or even 80 %.
He also often says that some of the members enjoy a win rate over 90% using his strategies.
I will let you be the judge of this.
Self-Promotion
He makes a lot of videos to attract new people into his trading room. His daily videos are uploaded on Facebook and Youtube almost daily even on Weekends (mostly excluding Friday evening & Saturdays).
In so many videos you’d hear him talking about how his trading room has an edge over other trading rooms while bashing other trading rooms as a whole.
He often talks about how his trading room bought stocks/options at the near bottom or shorted at the near top using his “algorithmic analysis” which can be applied to all markets (stocks, future, forex, crypto).
Piques your curiosity, right?
In fact, that’s how I got to give his trading room a try.
“Who in the hell wouldn’t want to catch the top & bottom in the markets, right?”
So, you would think people in his room and himself are making a killing using his algorithmic analysis?
Not so fast… (in fact, his algorithmic analysis is just drawing trendlines and identifying the most probable support and resistance)
When it works (of course, nothing works 100% of the time), you are able to catch just few cents off the top and bottom when it works if you follow his trade.
However, you have no idea how long you’d have to hold your position. Mark doesn’t know either.
So, he usually goes for nickels and dimes and rarely holds a position longer than 5 minutes.
Even if he’s good at picking bottoms and tops, you’d often risk more than nickels and dimes just to make nickels and dimes. Make sense, right?
…….
…….
…….
Also, because he gets out of his positions fast, he misses out on riding some potentially big trades.
Oh, how I wish stay in that position a bit longer. He doesn’t say but one can surmise that he often leave too much on the table.
Of course, it’s important to take your profit fast when you scalp but you consistently leave too much on the table like he does, one has to wonder if he has any system for taking profits (otherwise, it’s all discretionary guessing).
This type of bottom/top picking is not his main strategy, though.
The strategy that makes him the most amount of money might surprise you. I will get to this later.
How Mark Trades (Mark’s Trading Setups and Strategies)
Mainly, he scans the market in the morning for earnings reports, analysts’ upgrades/downgrades and other catalysts that have potential to make moves in the market.
He openly shares his mockery or insult of analysts, calling certain analysts “idiots” or “imbeciles”.
He puts on his first trade(s) early in the morning (from 9:30AM to 10:00AM Eastern Standard Time) when the market move is the most volatile.
Some of his strategies use market order during this period of volatile time using options. You can see why this can be very risky and especially on thinly traded options with side spread.
He does point out this but sometimes you hear people in the room stuck in an options position that they can’t get out.
Just like his trades from calling the top/bottom of a stock, he gets in and gets out of a position within minutes if not seconds while going for nickels and dimes while staring at 1minute and 5-minutes charts.
That applies to most, if not all of his strategies. (Yes, sometimes he does catch bigger moves than nickels and dimes.)
When you trade during the most volatile time in the morning, you’re subjected to wild moves in both directions. If you’re overly prudent or inexperienced in trading, your stop (unless very wide), has a very high chance of hitting. A lot of times it might stop you out and go in the direction that you predicted.
So, when you’ve been trading during this time, you’d probably don’t set a stoploss order or a hard stop to avoid getting fleeced.
You do have to be proactive at cutting your loss as quickly as possible. Otherwise you’d find yourself scrambling to get out your position while the bid keeps dropping.
I have to say that Mark is very cautious and he does get out of trades very fast if he has doubt.
A lot of times he lets out exhausting, heavy sighs and even murmurs some swear words when things don’t seem to go the way he wants in a trade. Besides calling certain analysts, “imbeciles” and “idiots”, this is quite unprofessional but no one in the room has the gut to point things out like this.
The irony is that he is the “head of trading psychology” at T3 and it doesn’t seem like that he doesn’t have much control over his trading psychology and let alone his emotion.
People in trading chatrooms, like a herd of sheep, as a whole exhibit herd mentality. Even in an online chatroom, you don’t often see someone ruffling feathers and say what they really want to say.
This is probably because of the certain amount of people believing whatever he says without questioning the validity and quality of his comments.
He has several strategies and according to him all of them have win rate over %70.
However, he also comes up with new strategies as often as every month. He either comes up with new strategy or tweaks his existing strategies.
According to him, the reason is that the market is always evolving and you need to constantly adapt yourself to the ever-changing market environment.
What do you think? Does this sound like someone with an edge?
And for someone who scalps for nickels and dimes, he claims to have the highest Sharpe Ratio that he has ever seen in the industry. I’m NOT making this up. He often utters remarks like “My Sharpe Ratio is one of the highest I’ve seen in my twenty-year trading career.”, “I want to create a of traders with a very high Sharpe Ratio.
How can you achieve a high Sharpe Ratio when you scalp all the time?
And let’s not even talk about commissions generated from frequent scalping.
Who cares about commissions when you can be a scalper with high Sharpe Ratio?
Now, I want to talk about something controversial about his most profitable strategy.
Chatters
According to him, he makes the most amount of money using what he calls “Chatters”. He admits he bets on this kind of trades heavily.
His chatter trades are based on the “newsflow” of big funds making a move in certain stocks and piggybacking on the same trade before others catch on.
No one knows how he exactly gets his “newsflow” and he doesn’t give a straight answer when asked.
Maybe he pays a lot for this kind of information or maybe it’s given to him for free. Who knows?
But it makes sense. The name of the room is Newsbeat Live. Without this the name wouldn’t be the same.
This is probably the only real edge that he has and it’s understandable that he doesn’t want to reveal how he get this kind of newsflow and from where.
By joining his trading room he’ll make a callout on these trades for you to take advantage of.
In order to do this kind of trade, you have to be very quick on your trigger finger.
Almost always the initial move is done within a couple of minutes, if not seconds. If you get in late, you find yourself a sucker buying at or near the top.
Also, because you want to get in as soon as you hear his “chatter” announcements, he advised people to get in within 5 seconds of each chatter announcement and use market order to get in. He said that if he had a small account, he’d bet 100% on this kind of “high-octane” chatter trades and get in and get out fast for “easy” money.
This was how chatter trades were done
…Until one they when many people got burned badly.
Back in September or October of 2019, a lot of people in the room lost a lot money because they market ordered call options contracts on a chatter trade.
The spread on that trade was something like BID: 0.5 ASK: 5.00 few seconds after he announced it.
I didn’t take that trade. No way, I’m going to buy something that has a spread like that.
If you’ve been trading options you know that this kind of spread can happen. Many people that day in the room marketed-in on the trade, taking the offer at ASK.
They found themselves buying at $5.0 per contract when someone probably bought the same contract at $0.40 or $0.50 just few seconds ago.
Someone walked away with decent profits on that trade.
This was the biggest trading chatroom fiasco I’ve ever seen.
People in the room grieving and throwing numbers of how much they had just lost. 10K, 20K, 30K and even $60K.
Could it be also that someone who lost more and didn’t want to talk about it because it’d hurt too much? And how embarrassing to talk about such a loss. I give credit to people who spoke up about it.
People were obviously distressed and what did Mr. Mark Melnick do at this moment?
Initially, he didn’t say much. But what he said he was going to walk away from the trading desk to clear his mind.
It took a while for him to come back and he mentioned that it hurt him a lot that people lost a lot of money and encouraged people not to hesitate to contact him.
I don’t think he ever said anything about that he made a mistake insinuating to load up on chatter trades. No apology since everyone who took the trade did it at their own risk. He advised people to reach out to their broker and do whatever it takes to get their trades annulled because the market makers in that trades were despicable crooks and evil.
But let’s get one thing clear. Perhaps the cold hard truth.
Since Mark is the one who announces chatter trades. he basically frontruns everyone who gets in on these trades after him. There were times when he doesn’t take his own chatter trades and lets the room have it.
But when he does, it’s a guarantee win for him.
He has some sycophantic followers in his trading room and these people are always hungry for chatter plays. I can imagine drooling over the idea of next chatter trades.
It’s human to naturally seek the least path of resistance and this type of trade requires no skill but having fast trigger finger and a platform that allows fast execution.
By taking his chatter trades, you are most likely to make money as long as you act fast to get in and get out.
The thing is, you don’t know when it’s exactly the next chatter trade is going to happen.
If you take a bathroom break, you just miss it. If you take a phone call or answer a door bell, you just missed it.
So, it requires you to be glued to your monitor(s) if you want to make the most of your subscription.
So, we went over Mark’s most profitable strategy. But wait we haven’t yet to talk about his overnight swing trades.
Mark’s Swing Trades
His overnight swing trades jokes. Yes, jokes.
A lot of his overnight trades are done just before earnings announcements when implied volatility is at the highest.
You’ve ever bought a call option just before earnings, predicted the right direction but only to find out that you still lost money next morning? This is because of the implied volatility crush post earnings. A lot of people new to options don’t know this and get taken advantage by veterans this way.
I don’t know if Mark knows or not but I witnessed him buying options this way. I think he understand the concept of implied volatility but why he gets on such trades is a mystery.
I haven’t exactly checked the result of all of his swing trades but I wouldn’t be surprised if people lost more money following his swing trades than anything in the room.
Final Word
Mark offers “free-consultation” on the phone for people who struggle in their trading.
He said that he takes a lot of phone calls but often you’d get the feeling that he is distracted, unable to give an undivided attention for his consultation.
“How would you like to get on a free consultation with a millionaire scalper who can take your trading to the next level?” Appealing isn’t it?
But would you want to get on the phone with someone who is going to give a consultation, even if he or she is distracted?
Oh, it’s a free consultation. Ok, why not? What do I got to lose?
In his videos, you’d hear him saying that he cares for everyone in his trading room and considers them as part of his family. And he runs the trading room out of his good heart and intention more than making money.
Besides he says that he makes more money from his trading than running the room.
My suggestion is that you have a look and you’d be the judge.
He does hold “open house” for his trading room from time to time.
Also, I believe that if you try his trading room for the first time, you try it for a month for about $50. As for me, he’s just another front runner using his trading room to profit with a bad sense of humor and exaggeration that make you cringe.
submitted by appplejack007 to Daytrading [link] [comments]

Looking for someone to collaborate with in exploring some of the fundamental questions in algo trading in relation to quantitative analysis and the Forex market specifically.

I got interested in both algo trading and Forex about the same time. I figured that if I was going to trade in the Forex market or any market there after, I was going to use algorithms to do the trading for me. I wanted to minimize the "human factor" from the trading equation. With the research I have done so far, it seems that human psychology and its volatile nature can skew ones ability to make efficient and logical trades consistently. I wanted to free myself from that burden and focus on other areas, specifically in creating a system that would allow me to generate algorithms that are profitable more often then not.
Consistently generating strategies that are more profitable then not is no easy task. There are a lot of questions one must first answer (to a satisfactory degree) before venturing forward in to the unknown abyss, lest you waste lots of time and money mucking about in the wrong direction. These following questions are what I have been trying to answer because I believe the answers to them are vital in pointing me in the right direction when it comes to generating profitable strategies.
Can quantitative analysis of the Forex market give an edge to a retail trader?
Can a retail trader utilize said edge to make consistent profits, within the market?
Are these profits enough to make a full time living on?
But before we answer these questions, there are even more fundamental questions that need to be answered.
To what degree if any is back-testing useful in generating successful algo strategies?
Are the various validation testing procedures such as monte carlo validation, multi market analysis, OOS testing, etc... useful when trying to validate a strategy and its ability to survive and thrive in future unseen markets?
What are the various parameters that are most successful? Example... 10% OOS, 20% OOS, 50%......?
What indicators if any are most successful in helping generate profitable strategies?
What data horizons are best suited to generate most successful strategies?
What acceptance criteria correlate with future performance of a strategy? Win/loss ratios, max draw-down, max consecutive losses, R2, Sharpe.....?
What constitutes a successful strategy? Low decay period? High stability? Shows success immediately once live? What is its half life? At what point do you cut it loose and say the strategy is dead? Etc....
And many many more fundamental questions....
As you can see answering these questions will be no easy or fast task, there is a lot of research and data mining that will have to be done. I like to approach things from a purely scientific method, make no assumptions about anything and use a rigorous approach when testing, validating any and all conclusions. I like to see real data and correlations that are actually there before I start making assumptions.
The reason I am searching for these answers is because, they are simply not available out on the internet. I have read many research papers on-line, and articles on this or that about various topics related to Forex and quantitative analysis, but whatever information there is, its very sparse or very vague (and there is no shortage of disinformation out there). So, I have no choice but to answer these questions myself.
I have and will be spending considerable time on the endeavour, but I am also not delusional, there is only so much 1 man can do and achieve with the resources at his disposal. And at the end of the whole thing, I can at least say I gave it a good try. And along the way learn some very interesting things (already had a few eureka moments).
Mo workflow so far has consisted of using a specific (free) software package that generate strategies. You can either use it to auto generate strategies or create very specific rules yourself and create the strategies from scratch. I am not a coder so I find this tool quite useful. I mainly use this tool to do lots of hypothesis testing as I am capable of checking for any possible correlations in the markets very fast, and then test for the significance if any of said correlations.
Anyways who I am looking for? Well if you are the type of person that has free time on their hands, is keen on the scientific method and rigorous testing and retesting of various hypothesis, hit me up. You don't need to be a coder or have a PHD in statistics. Just someone who is interested in answering the same questions I am.
Whats the end goal? I want to answer enough of these questions with enough certainty, whereby I can generate profitable algo strategies consistently. OR, maybe the answer is that It cant be done by small fry such as a retail trader. And that answer would be just as satisfactory, because It could save me a lot more time and money down the road, because I could close off this particular road and look elsewhere to make money.
submitted by no_witty_username to Forex [link] [comments]

How To Choose An Automated Trading Platform?

How To Choose An Automated Trading Platform?
When going for an automated trading platform it is very important to look for some important features before you decide on the automated trading platform you want to trade on. Different automated trading platforms offer different services which have their own pros and cons and might suit certain strategies and better than the others.
We have discussed important features that you should consider while choosing an algorithmic trading platform.

Select The Right Automated Trading Platform


https://preview.redd.it/gbx58zrdabu41.png?width=900&format=png&auto=webp&s=5ee3a23bc4f55a88437a8002fedfdf73390ece9b

Backtesting

A backtest is a historical simulation of an algorithmic trading strategy to see how it would’ve performed on the data in the past. Backtest results usually show the strategy’s performance in terms of profits and losses and some popular performance statistics like Sharpe Ratio or Information ratio which help to quantify the strategy’s return on risk. Hence a good backtesting software can be a great plus for an automated trading platform. Backtests can be divided into two categories ‘Research Backtesters’ and ‘Event-Driven Backtesting’.

Programming Languages

Choice of programming language is very important while deciding which platform to use for automating your trading strategy. Different languages have different pros and cons. Most commonly used programming languages used for algorithmic trading are C++, C#, Java, R, Python, and MATLAB. You can refer to one of our recent posts on top backtesting platforms where we’ve discussed popular programming languages.

Data

Different automated trading platforms provide access to/support trading/backtesting of certain securities only; some provide specific access to data feeds like Bloomberg and Thomson/Reuters. For instance, there are platforms dedicated to Forex trading or Equities trading only that too in specific markets. You need to make sure what the automated trading platform offers and then decide based on your needs. The frequency of data that you would need should also be taken into account. Some strategies would require daily EOD data while some other strategies might require intraday trading data.

Web-Based Platform

Some automated trading platforms also provide the web-based platform for online trading and backtesting which makes it easy and convenient to access your trading platform anywhere. The web-based platform may have less number of features compared to the desktop trading platform.

https://preview.redd.it/bwmmw9efabu41.png?width=900&format=png&auto=webp&s=c16e4008e52cf4cdd175241e8698b1fca09b43f4

Complexity

Different automated stock trading platforms vary in ease of use. Some platforms may require actual programming expertise while others may not. Most platforms provide a demo version which can help you decide what fits your comfort level. The complexity of platforms can be different for different assets traded, and one should check the different tools & features available to analyze the specific asset class.

Number of Strategies Allowed

Sometimes there might be restrictions on the number of long or short strategies loaded on a particular account and you might need extra accounts for more strategies. You should also check if you have enough memory on your computer for multiple accounts if required as it can be memory intensive. Some platforms also offer their own trading strategies as add-ons which can be subscribed by paying a periodic or one-time fee.

Commissions/Costs

Trading commissions can impact your profits to a great extent. Carefully choose the plan which suits your trading requirements. Also, check if there are initial and/or monthly fees and what is offered against it to make sure you are only paying for services which you actually want.

Technical Support & Customer Service

Automated Trading platforms are expected to have an extremely high “up-time” and rarely go out of service. Before choosing the platform you should check the history of outages and if there have been any other issues in the past, how soon were those resolved, and how knowledgeable and helpful was the support team.
submitted by FmzQuant to CryptoCurrencyTrading [link] [comments]

Looking for someone to collaborate with in exploring some of the fundamental questions in algo trading in relation to quantitative analysis and the Forex market specifically.

I got interested in both algo trading and Forex about the same time. I figured that if I was going to trade in the Forex market or any market there after, I was going to use algorithms to do the trading for me. I wanted to minimize the "human factor" from the trading equation. With the research I have done so far, it seems that human psychology and its volatile nature can skew ones ability to make efficient and logical trades consistently. I wanted to free myself from that burden and focus on other areas, specifically in creating a system that would allow me to generate algorithms that are profitable more often then not.
Consistently generating strategies that are more profitable then not is no easy task. There are a lot of questions one must first answer (to a satisfactory degree) before venturing forward in to the unknown abyss, lest you waste lots of time and money mucking about in the wrong direction. These following questions are what I have been trying to answer because I believe the answers to them are vital in pointing me in the right direction when it comes to generating profitable strategies.
Can quantitative analysis of the Forex market give an edge to a retail trader?
Can a retail trader utilize said edge to make consistent profits, within the market?
Are these profits enough to make a full time living on?
But before we answer these questions, there are even more fundamental questions that need to be answered.
To what degree if any is back-testing useful in generating successful algo strategies?
Are the various validation testing procedures such as monte carlo validation, multi market analysis, OOS testing, etc... useful when trying to validate a strategy and its ability to survive and thrive in future unseen markets?
What are the various parameters that are most successful? Example... 10% OOS, 20% OOS, 50%......?
What indicators if any are most successful in helping generate profitable strategies?
What data horizons are best suited to generate most successful strategies?
What acceptance criteria correlate with future performance of a strategy? Win/loss ratios, max draw-down, max consecutive losses, R2, Sharpe.....?
What constitutes a successful strategy? Low decay period? High stability? Shows success immediately once live? What is its half life? At what point do you cut it loose and say the strategy is dead? Etc....
And many many more fundamental questions....
As you can see answering these questions will be no easy or fast task, there is a lot of research and data mining that will have to be done. I like to approach things from a purely scientific method, make no assumptions about anything and use a rigorous approach when testing, validating any and all conclusions. I like to see real data and correlations that are actually there before I start making assumptions.
The reason I am searching for these answers is because, they are simply not available out on the internet. I have read many research papers on-line, and articles on this or that about various topics related to Forex and quantitative analysis, but whatever information there is, its very sparse or very vague (and there is no shortage of disinformation out there). So, I have no choice but to answer these questions myself.
I have and will be spending considerable time on the endeavour, but I am also not delusional, there is only so much 1 man can do and achieve with the resources at his disposal. And at the end of the whole thing, I can at least say I gave it a good try. And along the way learn some very interesting things (already had a few eureka moments).
Mo workflow so far has consisted of using a specific (free) software package that generate strategies. You can either use it to auto generate strategies or create very specific rules yourself and create the strategies from scratch. I am not a coder so I find this tool quite useful. I mainly use this tool to do lots of hypothesis testing as I am capable of checking for any possible correlations in the markets very fast, and then test for the significance if any of said correlations.
Anyways who I am looking for? Well if you are the type of person that has free time on their hands, is keen on the scientific method and rigorous testing and retesting of various hypothesis, hit me up. You don't need to be a coder or have a PHD in statistics. Just someone who is interested in answering the same questions I am.
Whats the end goal? I want to answer enough of these questions with enough certainty, whereby I can generate profitable algo strategies consistently. OR, maybe the answer is that It cant be done by small fry such as a retail trader. And that answer would be just as satisfactory, because It could save me a lot more time and money down the road, because I could close off this particular road and look elsewhere to make money.
submitted by no_witty_username to algotrading [link] [comments]

FX carry strategies (part 2): Hedging | Systemic Risk and Systematic Value

fintech #trading #algotrading #quantitative #quant #fx #forex #hft #financial

FX carry strategies (part 2): Hedging There is often a strong case for hedging FX carry trades against unrelated global market factors. It is usually not difficult to hedge currency positions – at least partly – against global directional risk and against moves in the EURUSD exchange rate. The benefits of these hedges are [1] more idiosyncratic and diversifiable currency trades and, [2] a more realistic assessment of the actual currency-specific subsidy or risk premium implied by carry, by applying hedge costs to the carry measure. Empirical analysis suggests that regression-based hedging improves Sharpe ratios, reduces risk correlation and removes downside skews in the returns of global FX carry strategies. Hedging works well in conjunction with “economically adjusted” FX carry and even benefits the performance of relative FX carry strategies that have no systematic risk correlation to begin with.
This post is based on proprietary research of Macrosynergy LLP and SRSV Ltd. FX car.....
Continue reading at: http://www.sr-sv.com/fx-carry-strategies-part-2-hedging/
submitted by silahian to quant_hft [link] [comments]

Is sharpe ratio the golden standard of portfolio optimisation?

If not, please point me in the right direction
submitted by peachesxxxx to Forex [link] [comments]

Preparing for the Impulse: The Japanese Yen Surge

Preparing for the Impulse: The Japanese Yen Surge
See first: https://www.reddit.com/Forex/comments/clx0v9/profiting_in_trends_planning_for_the_impulsive/

Against it's major counterparts, the JPY has been showing a lot of strength. It's now getting into areas where it is threatening breakouts of decade long support and resistance levels.

Opportunity for us as traders if this happens is abundant. We've not seen trading conditions like this for over 10 years on this currency, and back then it was a hell of a show! In this post I'll discuss this, and my plans to trade it.

I'm going to focus on one currency pair, although I do think this same sort of move will be reflected across most of the XXXJPY pairs. The pair I will be using is GBPJPY. I like the volatility in this pair, and along with the JPY looking continually strong and there being uncertainty in the GBP with possible Brexit related issues, this seems like an ideal target for planning to trade a strong move up in the JPY.

The Big Overview

I'll start by drawing your attention to something a lot of you will have probably not been aware of. GBPJPY has always been in a downtrend. All this stuff happening day to day, week to week and month to month has always fitted into an overall larger downtrend. In the context of that downtrend, there have been no surprises in the price moves GBPJPY has made. This is not true of the real world events that drove these moves. Things like market crashes, bubbles and Brexit.

https://preview.redd.it/5gfhwxcy6wj31.png?width=663&format=png&auto=webp&s=4d4806dee84a7bbe073e08d153da946222893eeb

Source: https://www.poundsterlinglive.com/bank-of-england-spot/historical-spot-exchange-rates/gbp/GBP-to-JPY

I know this has been largely sideways for a long time, but it is valid to say this is a downtrend. The highs are getting lower, and the lows have been getting lower (last low after the Brexit fall and following 'flash crash' some weeks later).
This is important to understand, because it's going to help a lot when we look at what has happened over the last 5 - 10 years in this pair, and what it tells us might be about to happen in the coming few months and year to come. If the same pattern continues, a well designed and executed trade plan can make life changing money for the person who does that. I hope those of you who take the time to check the things I say here understand that is very feasible.

The last Decade


In the same way I've shown you how we can understand when a trend has corrective weeks and see certain sorts of price structure in that, from 2012 to 2015 GBPJPY had a corrective half decade. In the context of large price moves over decades, this was a sharp correction. I've discussed at length in my posts how sharp corrections can then lead into impulse legs.

https://preview.redd.it/kvnrqau07wj31.png?width=675&format=png&auto=webp&s=8e96f02a189a811d511ef7946037fd670d106b1b
I've explained though my posts and real time analysis and trades in the short term how in an impulse leg we would expect to see a strong move in line with the trend, then it stalling for a while. Choppy range. Then there being a big spike out move of that range. Making dramatic new lows. Then we'd enter into another corrective cycle (I've been showing you weeks, it's more practical. We'll be looking at the same thing scaled out over longer, that's all).

At this point, we can say the following things which are all non-subjective.
  • GBPJPY has always been in a downtrend.
  • A clear high after a strong rally was made in 2016
  • Since then, GBPJPY has downtrended
5 year chart confirms the latter two points.

https://preview.redd.it/a44rzzs47wj31.png?width=686&format=png&auto=webp&s=43fbebe933fa80d1c24a1f8fde2c08653d125d18

These are interesting facts. We can do a lot of with this information to understand where we may really be in the overall context of what this pair is doing.

The Clear Trend Cycle of the Last 5 Years


If we were to use the Elliot Wave theory, based on the above data we have we'd expect to see down trending formations on the weekly chart over the last 5 years. These would form is three distinct trend legs, each having a corrective pattern after. We would expect to see after that a strong correction (corrective year in down trending 5 year cycle), it stop at the 61.8% fib and then resume a down trend. The down trend would form similarly in three main moves.

https://preview.redd.it/ghvgzr577wj31.png?width=663&format=png&auto=webp&s=caeedc4f48ab3b4d1ed921ef519a33200db62868

Whether or not you believe Elliot Wave theory is any good or not, this is what it would predict. If you gave someone who knew about Elliot trading the facts we've established - they'd make this prediction. So let's see how that would look on the GBPJPY chart. I'm having problems with my cTrader platform today, so will have to use MT4 charting.


These are three distinct swings from a high to a low. It also fits all the other Elliot rules about swing formation (which I won't cover, but you can Google and learn if you'd like to). We then go into a period of correction. GBPJPY rallies for a year.
This corrective year does not look very different from a corrective week. Which I've shown how we can understand and trade though various different posts.

https://preview.redd.it/m9ga8pp97wj31.png?width=590&format=png&auto=webp&s=6ed069207b8297c0ab67d6608206b57a1b354fef
Source: https://www.reddit.com/Forex/comments/cwwe34/common_trading_mistakes_how_trend_strategies_lose/

Compare the charts, there is nothing different. It's not because I've copied this chart, it is just what a trend and correction looks like. I've shown this is not curve fitting by forecasting these corrective weeks and telling you all my trades in them (very high success rate).

What about the retrace level?
When we draw fibs from the shoulders high (which is where the resistance was, there was a false breakout of it giving an ever so slightly higher high), it's uncanny how price reacted to this level.

https://preview.redd.it/68pa0bgc7wj31.png?width=667&format=png&auto=webp&s=8f78ce2c11f267f32dacd17c8717dcfa1f8bcb6a
This is exactly what the theory would predict. I hope even those sceptical about Elliot theory can agree this looks like three trend moves with corrections, a big correction and then a top at 61.8%. Which is everything the starting data would predict if the theory was valid and in action.

Assumptions and Planning


To this point, I've made no assumptions. This is a reporting/highlighting of facts on historical data of this pair. Now I am going to make some assumptions to use them to prepare a trade plan. These will be;

  • This is an Elliot formation, and will continue to be.
  • Since it is, this leg will have symmetry to the previous leg.

I'll use the latter to confirm the former. I'll use a projection of what it'd look like if it was similar to the previous move. I'll put in my markers, and look for things to confirm or deny it. There'll be ways to both suggest I am right, and suggest I am wrong. For as long as nothing that obviously invalidates these assumptions happens in the future price action, I'll continue to assume them to be accurate.

Charting Up for Forecasts

The first thing I have do here is get some markers. What I want to do is see if there is a consistency in price interactions on certain fib levels (this is using different methods from what I've previously discussed in my posts, to avoid confusion for those who follow my stuff). I am going to draw extension swings and these will give level forecasts. I have strategies based upon this, and I'm looking for action to be consistent with these, and also duplicated in the big swings down.
I need to be very careful with how I draw my fibs. Since I can see what happened in the chart, it obviously gives me some bias to curve fit to that. This does not suit my objective. Making it fit will not help give foresight. So I need to look for ways to draw the fib on the exact same part of the swing in both of the moves.

https://preview.redd.it/d5qwm8vg7wj31.png?width=662&format=png&auto=webp&s=ad2deba557f9f6d8a0fe06d34cbe3307e7cccc24

These two parts of price moves look like very similar expressions of each other to me. There is the consolidation at the low, and then a big breakout. Looking closer at the top, both of them make false breakouts low before making a top. So I am going to use these swings to draw my fibs on, from the low to the high. What I will be looking for as specific markers is the price reaction to the 1.61% level (highly important fib).
A strategy I have designed around this would look for price to stall at this level, bounce a bit and then make a big breakout and strong trend. This would continue into the 2.20 and 2.61 extension levels. So I'm interested to see if that matches in.

https://preview.redd.it/mpoqz4aj7wj31.png?width=663&format=png&auto=webp&s=710d72120085c1e137c800f57a36f910f78eebcb
Very similar price moves are seen in the area where price traded through the 1.61 level. The breakout strategy here predicts a retracement and then another sell to new lows.
On the left swing, we made a retracement and now test lows. On the right swing, we've got to the point of testing the lows here. This is making this level very important. The breakout strategy here would predict a swing to 61 is price breaks these lows. This might sound unlikely, but this signal would have been flagged as possible back in 2008. It would require the certain criteria I've explained here, and all of this has appeared on the chart since then. This gives me many reasons to suspect a big sell is coming.

On to the next assumption. For this fall to happen in a strong style like all of these are suggesting, it'd have to be one hell of a move. Elliot wave theory would predict this, if it was wave 3 move, these are the strongest. From these I'm going to form a hypothesis and then see if I can find evidence for or against it. I am going to take the hypothesis that where we are in this current GBPJPY chart is going to late come to been seen in a larger context as this.

https://preview.redd.it/tkfzja5n7wj31.png?width=661&format=png&auto=webp&s=47fc014619a61728f16e1527e729b82edad6b94e

This hypothesis would have the Brexit lows and correction from this being the same as the small bounce up before this market capitulated. This would forecast there being a break in this pair to the downside, and that then being followed by multiple sustained strong falls. I know this looks insanely big ... but this is not much in the context of the theme of the last 50 years. This sort of thing has always been what happened when we made this breakout.

Since I have my breakout strategy forecasting 61, I check for confluence of anything that may also give that area as a forecast. I'm looking for symmetry, so I take the ratio of the size of the first big fall on the left to the ratio of when it all out crashed. These legs are close to 50% more (bit more, this is easy math). The low to high of the recent swing would be 7,500 pips. So this would forecast 11,000.
When you take that away from the high of 156, it comes in very close to 61. Certainly close enough to be considered within the margin of error this strategy has for forecasting.

I will be posting a lot more detailed trade plans that this. Dealing specific levels to plan to engage the market, stop trailing and taking profit. I'll also quite actively track my trades I am making to enter into the market for this move. This post is to get the broad strokes of why I'm looking for this trade in place, and to help you to have proper context by what I mean when you hear me talking about big sells on this pair and other XXXJPY pairs.
submitted by whatthefx to Forex [link] [comments]

Preparing for the Impulse: The Japanese Yen Surge

Preparing for the Impulse: The Japanese Yen Surge
Against it's major counterparts, the JPY has been showing a lot of strength. It's now getting into areas where it is threatening breakouts of decade long support and resistance levels.

Opportunity for us as traders if this happens is abundant. We've not seen trading conditions like this for over 10 years on this currency, and back then it was a hell of a show! In this post I'll discuss this, and my plans to trade it.

I'm going to focus on one currency pair, although I do think this same sort of move will be reflected across most of the XXXJPY pairs. The pair I will be using is GBPJPY. I like the volatility in this pair, and along with the JPY looking continually strong and there being uncertainty in the GBP with possible Brexit related issues, this seems like an ideal target for planning to trade a strong move up in the JPY.

The Big Overview

I'll start by drawing your attention to something a lot of you will have probably not been aware of. GBPJPY has always been in a downtrend. All this stuff happening day to day, week to week and month to month has always fitted into an overall larger downtrend. In the context of that downtrend, there have been no surprises in the price moves GBPJPY has made. This is not true of the real world events that drove these moves. Things like market crashes, bubbles and Brexit.

https://preview.redd.it/9r6rnqo4rvj31.png?width=1258&format=png&auto=webp&s=738602a2157e08c3f9ec6c588ae603edb5b71a36
Source: https://www.poundsterlinglive.com/bank-of-england-spot/historical-spot-exchange-rates/gbp/GBP-to-JPY

I know this has been largely sideways for a long time, but it is valid to say this is a downtrend. The highs are getting lower, and the lows have been getting lower (last low after the Brexit fall and following 'flash crash' some weeks later).
This is important to understand, because it's going to help a lot when we look at what has happened over the last 5 - 10 years in this pair, and what it tells us might be about to happen in the coming few months and year to come. If the same pattern continues, a well designed and executed trade plan can make life changing money for the person who does that. I hope those of you who take the time to check the things I say here understand that is very feasible.

The last Decade


In the same way I've shown you how we can understand when a trend has corrective weeks and see certain sorts of price structure in that, from 2012 to 2015 GBPJPY had a corrective half decade. In the context of large price moves over decades, this was a sharp correction. I've discussed at length in my posts how sharp corrections can then lead into impulse legs.
https://preview.redd.it/j5q3jrtvsvj31.png?width=1269&format=png&auto=webp&s=a76fdb3de6e943234352f4b9832483c35e082a4b
I've explained though my posts and real time analysis and trades in the short term how in an impulse leg we would expect to see a strong move in line with the trend, then it stalling for a while. Choppy range. Then there being a big spike out move of that range. Making dramatic new lows. Then we'd enter into another corrective cycle (I've been showing you weeks, it's more practical. We'll be looking at the same thing scaled out over longer, that's all).

At this point, we can say the following things which are all non-subjective.
  • GBPJPY has always been in a downtrend.
  • A clear high after a strong rally was made in 2016
  • Since then, GBPJPY has downtrended
5 year chart confirms the latter two points.

https://preview.redd.it/ac1kjwr1uvj31.png?width=1249&format=png&auto=webp&s=f94861cab758119231fff168233bebac832cf456

These are interesting facts. We can do a lot of with this information to understand where we may really be in the overall context of what this pair is doing.

The Clear Trend Cycle of the Last 5 Years


If we were to use the Elliot Wave theory, based on the above data we have we'd expect to see down trending formations on the weekly chart over the last 5 years. These would form is three distinct trend legs, each having a corrective pattern after. We would expect to see after that a strong correction (corrective year in down trending 5 year cycle), it stop at the 61.8% fib and then resume a down trend. The down trend would form similarly in three main moves.

Whether or not you believe Elliot Wave theory is any good or not, this is what it would predict. If you gave someone who knew about Elliot trading the facts we've established - they'd make this prediction. So let's see how that would look on the GBPJPY chart. I'm having problems with my cTrader platform today, so will have to use MT4 charting.


https://preview.redd.it/s8vguiimvvj31.png?width=823&format=png&auto=webp&s=96d023db99041c9ba91f61ab87d3bd48de8da514
These are three distinct swings from a high to a low. It also fits all the other Elliot rules about swing formation (which I won't cover, but you can Google and learn if you'd like to). We then go into a period of correction. GBPJPY rallies for a year.
This corrective year does not look very different from a corrective week. Which I've shown how we can understand and trade though various different posts.
https://preview.redd.it/yowdmil6wvj31.png?width=733&format=png&auto=webp&s=bad142803823e6a7f8af56ef63ebebc574210c4b
Source: https://www.reddit.com/Forex/comments/cwwe34/common_trading_mistakes_how_trend_strategies_lose/

Compare the charts, there is nothing different. It's not because I've copied this chart, it is just what a trend and correction looks like. I've shown this is not curve fitting by forecasting these corrective weeks and telling you all my trades in them (very high success rate).

What about the retrace level?
When we draw fibs from the shoulders high (which is where the resistance was, there was a false breakout of it giving an ever so slightly higher high), it's uncanny how price reacted to this level.
https://preview.redd.it/axvtd22wwvj31.png?width=822&format=png&auto=webp&s=518f309232552ea33921e939b08d2bf28ba76f0b
This is exactly what the theory would predict. I hope even those sceptical about Elliot theory can agree this looks like three trend moves with corrections, a big correction and then a top at 61.8%. Which is everything the starting data would predict if the theory was valid and in action.

Assumptions and Planning


To this point, I've made no assumptions. This is a reporting/highlighting of facts on historical data of this pair. Now I am going to make some assumptions to use them to prepare a trade plan. These will be;

  • This is an Elliot formation, and will continue to be.
  • Since it is, this leg will have symmetry to the previous leg.

I'll use the latter to confirm the former. I'll use a projection of what it'd look like if it was similar to the previous move. I'll put in my markers, and look for things to confirm or deny it. There'll be ways to both suggest I am right, and suggest I am wrong. For as long as nothing that obviously invalidates these assumptions happens in the future price action, I'll continue to assume them to be accurate.

Charting Up for Forecasts

The first thing I have do here is get some markers. What I want to do is see if there is a consistency in price interactions on certain fib levels (this is using different methods from what I've previously discussed in my posts, to avoid confusion for those who follow my stuff). I am going to draw extension swings and these will give level forecasts. I have strategies based upon this, and I'm looking for action to be consistent with these, and also duplicated in the big swings down.
I need to be very careful with how I draw my fibs. Since I can see what happened in the chart, it obviously gives me some bias to curve fit to that. This does not suit my objective. Making it fit will not help give foresight. So I need to look for ways to draw the fib on the exact same part of the swing in both of the moves.

https://preview.redd.it/xgvofjcl0wj31.png?width=823&format=png&auto=webp&s=6d2564bbe2ece9506c425397c672c16cd75a2766
These two parts of price moves look like very similar expressions of each other to me. There is the consolidation at the low, and then a big breakout. Looking closer at the top, both of them make false breakouts low before making a top. So I am going to use these swings to draw my fibs on, from the low to the high. What I will be looking for as specific markers is the price reaction to the 1.61% level (highly important fib).
A strategy I have designed around this would look for price to stall at this level, bounce a bit and then make a big breakout and strong trend. This would continue into the 2.20 and 2.61 extension levels. So I'm interested to see if that matches in.

https://preview.redd.it/4tl024da2wj31.png?width=810&format=png&auto=webp&s=09a813fcdf67a0fac41ff1d9a44b540fd1298106
Very similar price moves are seen in the area where price traded through the 1.61 level. The breakout strategy here predicts a retracement and then another sell to new lows.
On the left swing, we made a retracement and now test lows. On the right swing, we've got to the point of testing the lows here. This is making this level very important. The breakout strategy here would predict a swing to 61 is price breaks these lows. This might sound unlikely, but this signal would have been flagged as possible back in 2008. It would require the certain criteria I've explained here, and all of this has appeared on the chart since then. This gives me many reasons to suspect a big sell is coming.

On to the next assumption. For this fall to happen in a strong style like all of these are suggesting, it'd have to be one hell of a move. Elliot wave theory would predict this, if it was wave 3 move, these are the strongest. From these I'm going to form a hypothesis and then see if I can find evidence for or against it. I am going to take the hypothesis that where we are in this current GBPJPY chart is going to late come to been seen in a larger content as this.

https://preview.redd.it/ctcill674wj31.png?width=814&format=png&auto=webp&s=538847fce98009b8177e079aa6a3ecba0684e73f
This hypothesis would have the Brexit lows and correction from this being the same as the small bounce up before this market capitulated. This would forecast there being a break in this pair to the downside, and that then being followed by multiple sustained strong falls.
Since I have my breakout strategy forecasting 61, I check for confluence of anything that may also give that area as a forecast. I'm looking for symmetry, so I take the ratio of the size of the first big fall on the left to the ratio of when it all out crashed. These legs are close to 50% more (bit more, this is easy math). The low to high of the recent swing would be 7,500 pips. So this would forecast 11,000.
When you take that away from the high of 156, it comes in very close to 61. Certainly close enough to be considered within the margin of error this strategy has for forecasting.

I will be posting a lot more detailed trade plans that this. Dealing specific levels to plan to engage the market, stop trailing and taking profit. I'll also quite actively track my trades I am making to enter into the market for this move. This post is to get the broad strokes of why I'm looking for this trade in place, and to help you to have proper content by what I mean when you hear me talking about big sells on this pair and other XXXJPY pairs.
submitted by whatthefx to u/whatthefx [link] [comments]

[WallText] For those who really want to be forex traders.

Im sry if u find some grammatical errors, english is not my mother language. Let me know and i will fix it.
First of all, look for at least half an hour without interruptions to read this manual.
This is the system that has created trading professionals. He has done it and today he continues doing it, as it happened with me.
It is not a system written in any forum, in fact I believe that it has been the first to collect all the ideas and create a structure to follow to carry them out, but these same ideas and procedures have been the ones that the winning traders have used during decades and will continue to use, since they are based on completely objective and real foundations.
Let's go to it:
Hi all.
It is known that the observation time makes the patterns elucidate, and after some time in the forum and throughout this trading world I have found many patterns in the responses of the people, I have reasoned about them, and I have realized their failures, why they fail to be profitable.
There are people who have put effort into this. Not all, but there are people who have really read a lot, studied a lot, learned a lot and tried a lot, and even then they are not able to achieve stable profitability.
The question is: Is there enough in that effort? Is there a specific moment in the line of learning where you start to be profitable? The question is, logically.
There are traders that generate constant profitability. Hedge funds, investment firms ... and the difference is in areas where people for some reason do not want to invest time.
Why are there more messages in the strategy forums than in the psychology, journals and fundamental analysis together?
As human beings, our brain is programmed to look for quick positive responses. In nature, the brain does not understand the concept of long-term investment. There is only a short-term investment made from the difference between what we think will cost us something and what we think it will contribute. If we think that it will cost us more than it can give us, we simply do not feel motivated. It is a simple mechanism.
The market plays with these mechanisms. There are more scalpers created from the search for that positive emotion than from the search for a scalping system.
In short, we are not programmed to operate, and there lies the fact that only a huge minority of operators are profitable.
Among others, I have observed several patterns of behavior that make a trader fail, and they are:
- Search for immediate pleasure: The trader wants to feel that he has won on the one hand, and on the other he wants to avoid the feeling of loss. Following this there are many traders who place a very low take profit and a very high stop loss. This is not bad if the probabilities have been reviewed before, the mathematical factor of hope, the relation with the drawdown .. but in the majority of the cases absolutely nothing of statistics is known. There is only that need to win. They win, they win, they win, until one day the odds do their job and the stop loss is touched, returning the account to its origins or leaving it with less money than it started. This does not work.
- Search for immediate wealth: Again it is something immediate. People want good emotions, and we want them already. The vast majority of traders approach this world with fantasies of wealth, women and expensive cars, but do not visualize hard work, the sickly hard work behind all this.
From there underlie behaviors like eternally looking for new robots or expert advisors that promise a lot of money, or new systems. The type of trader that has this integrated pattern is characterized by doing nothing more than that. Spend the day looking for new strategies Of course he never manages to earn constant money.
- Think that trading is easy: Trading is not easy, it is simple. Why? Because when you get the wisdom and experience necessary to find yourself in a state of superior knowledge about the market and effectively make money, it is very simple; you just have to apply the same equation again and again. However, it is not easy to reach this equation. This equation includes variables such as risk understanding, mathematics, certain characteristics in the personality that must be assimilated little by little, intelligence, a lot of experience ..
This is not easy. This is a business, and in fact it is one of the most difficult businesses in the world. It may seem simple to see a series of candles on a screen or perhaps a line, or any type of graphic, but it is not. Behind the screen there are hundreds of thousands of very intelligent professionals, very disciplined, very educated, very ...
This business is the most profitable in the world if you know how to carry, since it is based on the concept of compound interest, but it is also one of the most difficult. And I repeat. It's a business, not a game. I think you'll never hear a lawyer say to his boss: "We're going to focus all our time on finding a strategy that ALWAYS makes us win a trial, ALWAYS." What does it sound ridiculous? It sounds to me just as ridiculous for trading.
But you are not to blame, you have been subconsciously deceived through the advertising brokers and your own internal desires, to think that this is something easy.
- Lack of discipline: Trading is not something you can do 10 minutes on Monday and 6 on Thursday. This is not a game, and until you get a regular schedule you can not start earning money. There are people who open a graph one day for 5 minutes, then return to their normal life and then one week returns to look at it for other minutes.
Trading should not be treated as a hobby. If you want to win "some money" I advise you not even to get in, because you will end up losing something or a lot of money. You have to think if you really want trading to be part of your life. It's like when you meet a girl and you want to get married. Do you really want to get into this with all the consequences? Because otherwise it will not work.
Visualize the hard work behind this. Candle nights, frustrations, several hundred dollars lost (at the beginning) .. enter the world of trading with a really deep reason, if you lose a time and money that no one will return, and both things are finite!
- Know something and pretend to know everything: Making money in the markets is not based on painting the graph as a child a paper with crayon wax and pretend to make money.
It is not based on drawing lines or circles, or squares. It is based on understanding the operation of all these tools, the background of the why of the tools of trading.
A trend line only marks the cycle of a wave within a longer time frame, within a longer time frame, and so on indefinitely. In turn, this wave is divided into waves with a specific behavior, divided into smaller waves and Etcetera, and understanding that dynamic is fundamental to winning.
It is not the fact of drawing a line. That can be done by an 8 year old boy. It is the fact of UNDERSTANDING why.
There are traders who read two technical analysis books and a delta analysis book and believe that they are professionals, but do they really understand the behavior of the market? The answer is in their portfolios.
After this explanation that only 10% will have read, I will try to detail step by step something that is 90% yearning, and that will have quickly turned the scroll of your mouse to find the solution to all your problems while supporting the beer in a book of " become rich ", rotten by lack of use.
These steps must be carried out one by one, starting with the first, fulfilling it, moving on to the second, successively and growing. If steps are taken for granted, or not fully met, it simply will not work.
I know this will happen and the person who did it will think "Bah, this does not work." and you will return to your top strategy search routine.
That said, let start:
1º Create a REAL account with 50 dollars approximately:
_ Forget the demo accounts. They are a utopia, they do not work. There is infinite liquidity, without emotions and without slipagge.
These things will change when we enter the real market, and the most experienced person in the world will notice a sharp drop in their profitability when it happens to real accounts.
And not only using a demo account has disadvantages, but using a real one has advantages.
We will have a real slipagge with real liquidity. Real requotes and more. The most important: We will work our emotions at the same time. Because yes, we will lose or win a couple of cents, but that has a subconscious impact of loss.
This means that we will begin to expand our comfort zone from the start.
Using a demo account is simply a disadvantage.
2º Buy a newspaper in the stationery or in Chinese (optional), or write one online or in Word:
A newspaper will be of GREAT help. You can not imagine, for those of you who do not have one, how a newspaper can exponentiate our learning curve. It is simply absurd not to have a diary. It's like taking a ticket of 5 instead of one of 100.
In this diary we will write down observations that we make about the operations that we will carry out in points that I will explain later of this same manual.
We will divide the newspaper into 2 parts:
  • 1 part: The operation itself. We will write the reasons for each operation. The why we have done it.
  • 2 part: How we feel. We will unburden ourselves without explaining how we feel, what our intuition tells us about that particular operation and so on.
How to use:
We will read the newspaper once a week, thinking about the emotions we felt each day and in what situations, and the reasons.
Soon, we will begin to realize that we have certain patterns in the way we feel and operate, and we will have the ability to change them.
We can also learn from mistakes that we make, and keep them always in a diary.
3º Look for a strategy that has the following characteristics:
  • Make it SIMPLE. Nothing of 4 or more indicators or the colors of the gay flag drawn on the graph based on 1000 lines. Why? Because there is always an initial enthusiasm and maybe we can follow a complex strategy for a week, but burned that motivation, saturates us and we will leave it aside.
Therefore, the strategy must be simple. If we use metatrader, the default indicators work. No macd's no-lag and similar tools. That does not lead anywhere. And if you do not believe it, I'll tell you that in all areas of life comes marketing. In addition to trading towards MMA and now I do powerlifts, and there are 1000 exercises to do. However, the classics are still working and work very well. It seems that sellers of strange sports equipment do not share the same opinion, that the only thing they want is to sell!
4º Understand the strategy:
  • We must gut each process of the strategy and reason about it. What does this indicator do? What does this process? Why this and not another? Why this exit ?. Some strategies will be based on unspecified outputs. This does not suppose any problem because as we get experience in that specific strategy, we will remember situations that have occurred, we will see situations that are repeated (patterns) and we will be able to find better starts and entrances. Everything is in our hands.
5° Collect essential statistical information:
  • This part is FUNDAMENTAL, and no operator can have as much security in itself when operating as if it uses a strategy that has at least positive mathematical hope and an acceptable drawdown.
  • Step 1: To carry out this collection of information you need to test the strategy for at least 100 signals. Yes, 100 signals.
Assuming it is an intraday strategy and we do an operation per day, it will take us 100 days (3 months and 10 days approx) to carry out the study. Logically these figures can change depending on the number of operations that we make up to date with the strategy.
I have no doubt that after reading this manual we will go for a quick strategy of scalpers, with 100 signals every 10 minutes where the seller comes out with a big smile in his promotional video.
I personally recommend a system of maximum 2 daily operations to start, but this point is personal.
Is it a long time? Go! It turns out that a college student of average intelligence takes 6 years to finish a career. It takes 6 years just to train, and there are even more races. This does not guarantee any profitability, and in any case most of Sometimes it will get a static return and not based on compound interest. I can never aspire to more.
The market offers compound profitability, there will be no bosses, nor schedules that we do not impose. We will always have work, and we can earn a lot more money than most people with careers or masters. Is it a long time? I do not think so.
As I was saying, we will test the strategy 100 times with our REAL account that we created in step 1. Did you decide to use a demo account? Better look for another manual; This has to be something serious. They are 100 dollars and will be the best investment of all in your career as a trader.
  • Step 2: Once with the report of the 100 strategies in hand, we will collect the following information:
  • How many times have we won and how many lost. Afterwards, we will find the percentage of correct answers.
  • How much have we won and how much have we lost? Afterwards, we will find the average profit and the average loss.
  • Step 3: With this information we will complete the mathematical hope formula:
(1 + average profit / average loss) * (percentage of correct answers / 100) -1
Example:
  • Of the 100 operations there are 50 winners and 50 losers, then the success rate is 50%.
  • Our average profit is 20 dollars and our average loss is 10 dollars.
Filling the formula:
(1 + 20/10) * (50/100) -1
(1 + 2) * (0,5) -1
3 * 0.5 - 1
1,5 - 1 = 0,5
In this example the mathematical expectation is 0.5. It is POSITIVE, because it is greater than 0. From 0, we will know that this strategy will make us earn money over time ALWAYS we respect the strategy.
If after a few days we modify it, then we will have to find this equation again with another 100 different operations. Easy? A result of "0" would mean that this strategy does not win or lose, but in the long run we would LOSE due to the spread and other random factors.
You have to try to find a strategy that, once this study is done, the result of your mathematical hope is greater than 0.2 as MINIMUM.
Finding this formula will also give a curious fact. The greater the take profit in relation to the stop loss, as a general rule more positive will be our mathematical hope. This has given many pages of discursiones about whether to place take profit> stop loss or vice versa.
If our stop was larger than the take profit, then the other ratio (% earned /% lost) should be yes or yes positive.
But this is just curiosities.
let's keep going:
  • 6° Expand our comfort zone:
We will not be able to work with operations of 10 million dollars overnight, but we can progressively condition ourselves to that path.
Assuming all of the above, and with a real account, some experience in the 3 months of information gathering and a positive mathematical hope, we are ready to operate in real with some consistency. But how to carry it out?
The comfort zone is the psychological limits we have before feeling fear or emotional tension. When we get into a fight, we have left our comfort zone and we feel tension, unless we have a psychopathic disorder.
Every time we lean out onto a 300-meter balcony from a skyscraper, we move away from the comfort zone. Every time we speak to a depampanante woman, we move away from our comfort zone.
Our brain creates a comfort zone to differentiate what we usually do and is not substantially dangerous, from the unknown and potentially dangerous to our survival or reproduction. And whenever the brain interprets that these two aspects are in danger, we will feel negative emotions like fear, disgust, loneliness, fury, etcetera.
This topic is much more profound and you would have to read several volumes of evolutionism to understand the why of each thing. The only thing that interests us here is the "what", and the one, that is, that there is a certain comfort zone that must be expanded without any problems.
With trading, exactly the same thing happens. The forex market is a virtual environment in which we lose or gain things, but our brain does not differentiate between reality and what is not, it only attends to stimuli of a certain type.
We can lose food in the middle of the forest or also a crude oil operation.
Our goal is to condition our subconscious so that it is progressively accepting lost and small benefits, and as time goes by, bigger.
The exercise to achieve this is the following:
  • We will operate on that account of 100 dollars with our mathematically positive strategy for 3 more months.
  • After these three months, our account should have benefits, because of the mathematically positive strategy.
  • We will enter 200 dollars more and we will operate a month more raising the lots according to our risk management (I do not advise that the risk is greater than 2%)
At this point, I know how hard it is to resign myself to impatience, but follow those times and do not skip it even if you feel safe, but you will fail, it's simple.
Let's keep going:
  • After that month, we will raise our capital again with a new income. This time we will enter 1000 dollars (save if you do not have 1000 dollars loose, you will recover later on, do you want to make money, enter 1000 dollars.
We will test the operation one month with this new injection. We probably notice difficulties. More blockages, more euphoria when winning ... how will we know when to move on to the next entry? When we do not feel ANYTHING or at most something very shallow, when win or lose If observing the wall and operating is for you the same from an emotional point of view, it is time to enter more money.
  • We will follow this procedure until we have a basic account of 21000 dollars. The amounts to be paid will depend on our ability to not feel emotions, a capacity that will be taking over time.
We will raise capital until we feel that we block too much. In that case we will drawdown to a more acceptable amount, and we will continue at that level until get discipline and lack of reactivity at that level. Later, we will go up.
  • If we want to earn more money, we will continue entering and entering. Always following the conditioning scheme of 1 month.
Why a month?
A study conducted in the United States revealed that the subconscious needs an average of 28 days to create new habits or eliminate old habits. Emotional reactions are part of the habits. If we maintain some pressure of any emotion during the opportune time, in this case 28 days, will create tolerance and the subconscious will need a more intense version of the stimulus to activate.
AND THAT'S ALL!
Follow these steps and you will triumph. Here is the golden chalice, the tomb of Jesus or whatever you want to call it. There is no more mystery in the world of trading. This system will accompany you during the next year, year and a half. It's the one I used and it WORKS. Once done, you will have a very profitable system integrated into your being, since not only will it be mathematically viable, but you will also have the necessary experience to make it infinitely more profitable yet.
In addition, you will have psychology fully worked on a professional level to have conditioned your subconscious gradually.
Happy trading to all of u guys.-
submitted by Harry-Postre to Forex [link] [comments]

2018 Cryptocurrency Crash (Elliott Wave): Inflection Point

2018 Cryptocurrency Crash (Elliott Wave): Inflection Point
Crosspost: https://bitcointalk.org/index.php?topic=2711461.msg47569859#msg47569859
History
—08-JAN-2018: Elliott Wave, https://redd.it/7ptsg3
—12-JAN-2018: Crypto Black Monday, https://redd.it/7pxg0d
—24-JAN-2018: Dotcom vs Crypto, https://redd.it/7skzff
—21-FEB-2018: Bear Market Resumes, https://redd.it/7z8u6n
—28-FEB-2018: Halfway Through, https://redd.it/7umjf9
—13-MAR-2018: Fare Thee Well Ten Thousand, #10kNeverAgain: https://redd.it/842ssd
—19-MAR-2018: Equinox, https://redd.it/85m5tr
—03-APR-2018: April Fools’ Rally, https://redd.it/89jqye
—19-APR-2018: 420 High, https://redd.it/8dbz4f
—25-APR-2018: Symmetrical Triangle, https://redd.it/8ev2ki
—06-MAY-2018: Ten Thousand Tease, https://redd.it/8hdhjn
—29-MAY-2018: Triangle Phinance, https://redd.it/8mwx6z
—10-JUN-2018: Triangle Phinance II, https://redd.it/8q5p68
—23-JUL-2018: Redux, https://redd.it/913xx6
—02-SEP-2018: #ShortSeptember, https://redd.it/9c96vk
—04-NOV-2018: Inflection Point, https://redd.it/9u1y3z
TLDR: https://i.imgur.com/EGmziB1.png
The Bitcoin and cryptocurrency bear market of 2018 has reached a point of inflection, where alternative scenarios and projections can now be explored using Elliott Wave theory.
From the 17-DEC-2017 high to the 06-FEB-2018 low, the Bitcoin market endured a 70% price collapse from the all-time high of $19,891 to a low of $6,000 in just 51 days (BITFINEX). In Elliott Wave parlance, this first phase crash is a simple but sharp three wave a-b-c zigzag pattern.
From the 06-FEB-2018 low, the Bitcoin market then wandered sideways for 168 days until 24-JUL-2018, creating a floor of support at $6,000 whilst making successively lower highs. The psychological $6,000 price has been guarded since it marks support of the psychological USD$100 billion Bitcoin marketcap. In Elliott Wave parlance, this second phase of market development is a triangle pattern consisting of five a-b-c-d-e waves. The internal structure of the waves within the triangle are related to each other in terms of length as the following Fibonacci ratios:
wave-c = wave-a * 0.618 wave-d = wave-b * 0.786 wave-e = wave-c * 0.786 
https://i.imgur.com/Bm4Nx7a.png
The triangle phase of the Bitcoin market completed at the 24-JUL-2018 high. Since then, the third phase of market has been underway with an expectation of creating new lows for 2018 at sub $6,000 prices. Initial approx targets have been projected as follows (BITSTAMP):
@5920: Fibonacci 0.618% of wave-d low projected from wave-e high. @5220: Fibonacci 0.786% of wave-d low projected from wave-e high. @4327: Fibonacci 0.100% of wave-d low projected from wave-e high. @4200: Fibonacci 78.6% decline of entire Bitcoin market. 
Any of the aforementioned approx price levels based on Fibonacci projections are potential targets of where the 2018 bear market may conclude.
Should price retrace below the Fibonacci 78.6% of the entire Bitcoin market, i.e. below the psychological $4,000 level; it may suggest the bear market extends into 2019 with an expectation of a 90%-95% decline of the entire Bitcoin market to approx $1,000 by 2020. Such a scenario would be consistent with the collapse of other historical asset mania bubble bursts, which typically elapse 2 years on average: thebubblebubble.com/historic-crashes
However, the Bitcoin market has reached an inflection point. The third phase of the bear market appears to have stagnated in price and time. Since 09-SEP-2018, price has traded in a narrow 10% range at an average price of $6,400 for almost 60 days thus far. Volatility is now at a 22-month low and technicals such as moving averages are flat-lining across daily timeframes. This behaviour has been quite unexpected. Since completion of the consolidating triangle phase of the market, volume and volatility was expected to breakout. Speculators and traders have left the stabilised cryptocurrency marketplace in favour of the more volatile global equity bear markets.
An alternative scenario can now be considered: Since completion of the triangle at the 24-JUL-2018 high, the concluding phase of the bear market may have declined and truncated at the 11-OCT-2018 low. If so, a cyclical (i.e. short-term) bull market may be commencing within an overall secular (i.e. long-term) bear market. Such a bull market would be termed as a wave-X as part of a complex ongoing long-term bear market structure.
https://i.imgur.com/vePkBiL.png
In some schools of Elliott Wave thought, the wave-X bull market may unfold in five 1-2-3-4-5 impulsive waves; or, as three a-b-c corrective waves considered in other schools of thought. Either way, the size of a wave-X is challenging to predict. Typically, it may retrace either a Fibonacci 38.2%, 50%, 61.8% or 78.6% of the entire 2018 bear market; that is approx $11,081 or $12,720 or $14,360 or $16,705 respectively (BITSTAMP). In some cases, a wave-X may extend to, and even exceed prior all-time highs, like typically seen in commodity and forex markets. The wave-X cyclical bull market could be a swift parabolic move elapsing within 12 months during the course of 2019, and thus the overall secular bear market may still resume to unfold to a low in late 2020.
In summary, the parameters of the inflection point can be currently defined as follows, using BITSTAMP prices…
Bear Market Inflection Points
—A break below the 11-OCT-2018 low of $6,055 would be the first indication to suggest the bear market is still underway.
—A break below the 14-AUG-2018 low of $5,880 would confirm the ongoing bear market.
—A break below $4,000 may suggest an extended bear market leading to a 90%-95% collapse of the entire Bitcoin market by 2020.
Bull Market Inflection Points
—A break above the 15-OCT-2018 high of $6,756 would be the first indication to suggest a bull market may be commencing.
—A break above the 04-SEP-2018 high of $7,412 would likely confirm a bull market is underway.
Notes
—Bitcoin CBOE XBT futures expiries: 14-NOV-2018, 19-DEC-2018
—Bitcoin CME futures last trade dates: 30-NOV-2018, 28-DEC-2018
—Bitcoin ICE Bakkt daily futures tentative launch: 12-DEC-2018
—S&P500: global stockmarket indices appear to have topped, and a bear market is underway. Expectation is a rally into the end of year 2018 towards $2,800+ in the S&P500 index, followed by a decline to approx $2,400 by Easter 2019 to end the brief equity bear market.
—Gold: rally underway, expectation to conclude at approx $1,260, and then bear market resumes to sub $1,000 by 2020.
—US Dollar: expecting uptrend to be bounded by approx 98, and then bear market resumes.
Elliott Wave models are speculative and indicative of price and structure, not time; i.e. the projections may occur sooner or later than anticipated.
—BTC (Weekly): https://i.imgur.com/B0ftUHf.png
—BTC (Daily): https://i.imgur.com/ljfMvlt.png
—BTC (4-hr): https://i.imgur.com/Ip1QQTe.png
submitted by 12345abcde00001 to BitcoinMarkets [link] [comments]

How successful as a trader do you have to be to get capital? Is it difficult to start your own fund?

I wrote an algorithm to trade forex back in the beginning of 2011 and since then it's been performing well in forward testing. However, I've also been manually trading on my own account so the two sets of results are mixed in the one account. I've also recently made some small changes to the code which have noticeably increased the algorithm's risk-weighted return for each pair I trade.
A bit about the algo: I trade it on 9 different currency pairs with close to 1700 trades a year. It's based on options theory with unique entrance/exit coding. I also run with tight stops so there's never a carried loss or large draw-down. 2008-2011 backtesting also provided similar successful results. I've got a better Sharpe ratio than many of the funds/CTAs listed on top rankings. I also have a full-time career and strong academic background.
My question: What type of data/results do you need to get capital?
submitted by eurusdguy to finance [link] [comments]

Indian Financial Sector

The Central Government has been holding meetings with Asian Development Bank, World Bank, and German state-owned development bank KfW for access to low-cost capital to Indian MSMEs, according to MSME minister Nitin Gadkari. The comments gain significance as lack of capital is the biggest challenge for the growth of MSMEs.
-Financial Express
The RBI today asked banks to link all new floating-rate loans for housing, personal and MSMEs to external benchmark based interest rate from 1 Oct, in a bid to allow faster transmission of its rate cuts to consumers. It has been observed that due to various reasons, the transmission of policy rate changes to the lending rate of banks under the current MCLR framework has not been satisfactory, the RBI said in a statement.
-Livemint
PSBs can now create Chief General Manager (CGM) posts as per their business needs. The Department of Financial Services (DFS) in the Finance Ministry granted the flexibility to all nationalised banks. CGM posts (in a fresh scale termed as scale VIII) can be created (with Board approval) in nationalised banks that have total business of ₹10 lakh crore or higher, sources said. Such CGMs will act as an administrative and functional layer between the existing levels of General Manager and Executive Director. The number of CGM posts created should not exceed the ratio of 1:4 between the total number of posts of CGM and GM.
-Budiness Line
The RBI-constituted task-force on developing a vibrant secondary market for corporate loans has called for setting up a central loan contract registry to remove information asymmetries between buyers and sellers. The 6-member task force, headed by Canara Bank chairman TN Manoharan, was formed to examine the scope for developing a secondary market for corporate loans and make recommendations to facilitate rapid development of such a vibrant market.
-Business Standard
Global rating agency Moody's on September 4 upgraded the outlook on Punjab National Bank, which will merge OBC and United Bank of India with itself, to 'positive' from 'stable'. It also affirmed the local and foreign currency deposit ratings of Canara Bank, OBC, Syndicate Bank and Union Bank at Baa3/P-3.
-Moneycontrol.com
Canara Bank today said its board will meet next week to consider capital infusion of up to Rs 9,000 crore through issuance of preferential equity shares to the government of India. The board will also consider amalgamation of Syndicate Bank with it, the Bank said in a regulatory filing.
-Moneycontrol.com
HR integration will be the top priority in the merger of Syndicate Bank with Canara Bank and branch rationalisation would be looked at only after all aspects of integration are completek, . Syndicate Bank’s MD & CEO Mrutyunjay Mahapatra said. He saidthat the merger process will not slow down business.
-Economic Times
Canara Bank MD & CEO R A Sankara Narayanan, told that there would not be any loss of employment after merger. He had also confirmed that both the banks will stick to business projections and have a dedicated team to focus on integration without affecting normal business.
-Economic Times
LIC, that has seen its investment in IDBI Bank erode by more than half over the past year or so, has also seen the value of its investments in other PSU banks plunge. The sharp fall in the price of PSU bank stocks and dilution of its stake owing to capital infusion by the government, has eroded its wealth in these banks. LIC has lost over Rs 17,000 crore of its wealth in PSBs over the past year. Excluding IDBI Bank, it has lost over ₹4,800 crore in other PSBs.
-Business Line
ICICI Bank has cut its lending rates by 0.10% across all maturities, sources said on Sep 4. Under the revised rates, effective Sep 1, the bank's 1-year MCLR will come down to 8.55%, while the overnight MCLR will be 8.30%.
-Moneycontrol.com
Bank of Baroda will raise up to Rs 1,132.05 crore by issuing fresh shares to its staff under the Employee Share Purchase Scheme (ESPS), the bank said. Bank of Baroda will raise up to Rs 1,132.05 crore by issuing fresh shares to its staff under the ESPS, the bank said. The decision was taken by the compensation committee of the board at its meeting held on Tuesday, the bank said in a regulatory filing. decision was taken by the compensation committee of the board at its meeting held on Tuesday, the bank said in a regulatory filing.
-Moneycontrol.com
YES Bank has settled a case pertaining to ‘selective disclosure’ of assets quality with market regulator SEBI. The Bank settled the matter under the so-called consent mechanism paying Rs 51.6 lakh as settlement charges. Yes Bank’s compliance officer Shivanand Shettigar paid another Rs 14.45 lakh as settlement charges in the same matter.
-Business Standard
Wipro has received a long-term $300 million contract from ICICI Bank to provide digital technology led services. The Co said in a filing to the BSE that it has secured a strategic 7-year engagement from the bank.
-Economic Times
Digital payments saw significant growth in August, with the Unified Payments Interface (UPI) and IMPS touching record highs in terms of both volumes and number of transactions, while payments on BHIM also rose to a 10-month high.
-Business Line
Rating agency CRISIL today cut India’s fiscal year 2020 GDP growthforecast to 6.3% from its earlier forecast of 6.9%, after the economy grew 5% in the first quarter, it’s slowest in almost 6 years. The agency said that lower GDP growth forecast corroborates that India’s economic slowdown is deeper and more broad-based than suspected.
-Economic Times
Even as gross NPA are expected to come down marginally by end of ongoing fiscal, assets over Rs 1 lakh crore that are under pressure are still to be recognised as bad loans, a report by ASSOCHAM- CRISIL said.
-Financial Express
BSNL is monetising land assets to improve revenue while cutting operational costs in the absence of revival package from the government, according to chairman Pravin Kumar Purwar. The telco is looking at cutting its workforce by nearly half once the Centre approves its much-awaited voluntary retirement scheme, Purwar told.
-Economic Times
Rising gold prices have prompted the RBI to apply the brakes to its purchase of the metal as a forex reserve asset. After the last offtake of 5.6 tonnes this April, the apex bank has not made any fresh purchases. According to the data from the International Monetary Fund's International Financial Statistics (IFS), RBI has been holding 618 tonnes of gold as part of its forex reserves since April this year.
-Business Standard
USD/INR 72.12
SENSEX 36724.74(+161.83)
NIFTY50 10844.65(+46.75)
 -#040919 
submitted by venuangamaly to indianews [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
Generated with BBoe's Subreddit Stats (Donate)
submitted by subreddit_stats to subreddit_stats [link] [comments]

What is the Sharpe Ratio? What is Sharpe Ratio?  Definition of Sharpe Ratio ... Trading Education: Performance evaluation with Sharpe ... The Sharpe Ratio - YouTube Sharpe Ratio Explained - Investment strategies - YouTube Hit ratio of 90% and Sharpe of 8: New solution to old market timing problem

In MT4, the Sharpe Ratio for Forex Trading is the ratio of arithmetic average profit (average income over a period) to standard deviation. How effective this approach is a rhetorical question. After all, the absence of risk-free income increases the coefficient, thus distorting the result. If we are talking about the comparison of investing in different currency pairs on Forex, then it should ... Sharpe Ratio. When we talk about Sharp Ratio in the forex market, what we’re talking about is the measure of risk-adjusted return in a trade/s. It came to front thanks to Prof. William Sharpe, a recipient of the Nobel Prize in Economics. The calculation for the Sharpe Ratio is quite simple. Die Sharpe-Ratio ist eine finanzmathematische Kennzahl einer Geldanlage. Es wird dabei die Rendite einer Geldanlage gegenüber dem Risiko bei festem Zinssatz betrachtet. Ziel der Sharpe-Ratio ist es, ein Maß zu finden für die pro Risikoeinheit feststellbare Mehrrendite. Damit kann ein Vergleich zwischen verschiedenen Geldanlagen durchgeführt werden. Je höher die Sharpe-Ratio ist, umso mehr ... In 1996, the Sharpe ratio was created by William Sharpe. Ever since then it’s been used as the referenced risk in finance. It is that popular because of its ease of use. In 1990, Professor Sharpe was awarded a Nobel prize in Economic Science for his effort towards CAPM. And this later contributes to its credibility. Use of Sharpe Ratio in Forex. 1.6. Conclusion. Introduction to Sharpe Ratio. A Noble Laurette in Economics, William Sharpe developed the Sharpe ratio in order to measure the real rate of return for an investment opportunity after adjusting the risk factor involved in it. The Sharp ratio is mostly used to assess whether an investment justifies the risk or not. Specifically, it is used to ... The Sharpe Ratio of a forex strategy is not a determining factor on its own. The Sharpe Ratio can be especially helpful when it comes to comparing different methods and techniques but should not be used to make conclusions without any other supporting metrics. Having a profitable trading strategy with low volatility is a great target to try and meet, but it should not rule your life. The ... Es gibt eine Vielzahl von Fonds und ETFs am Markt. Mit der „Sharpe-Ratio“ können Anleger die Produkte identifizieren, die besser sind als der Durchschnitt – oder sogar besser als die Benchmark.

[index] [7749] [24907] [11142] [18347] [20789] [18986] [18016] [20638] [23977] [16681]

What is the Sharpe Ratio?

This video shows how to calculate the Sharpe Ratio. The Sharpe Ratio measures the reward (excess return) to risk (volatility) of a portfolio. This allows inv... Developed in Bodrum, Turkey, his FX strategy turns out having a hit ratio of 90% (75% hit ratio when applied in equities) and a Sharpe of 8 … In this Opalesque.TV BACKSTAGE video, Baris shares ... This tutorial from TranspariTrade explores: What is the Sharpe Ratio? http://www.transparitrade.com Sharpe ratio is a measure of excess portfolio return over the risk-free rate relative to its standard deviation. If two funds offer similar returns, the one ... Watch Corvin Cordila, Head of Tip TV Education, discuss the concept and usage of the "Sharpe Ratio' - which is excess returns one receives for the extra vola... Risk-adjusted return is more important than absolute return. Let's talk about the Sharpe Ratio. Take control of your financial future ! Visit my website: htt...

http://binaryoptiontrade.imtuhoffhava.ml