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Why 7% is the Difference between Failure and Success in Trading
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Why 7% is the Difference between Failure and Success in Trading

  #61 (permalink)
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The thread discussion got me more interested in analysis. Found a great resource for Free Stats Software.

As the market gives me plenty of time between my setups, this is something I plan to get more into. I spent my time in the stats class in university chatting up the pretty honey next to me... but I'm back, it's an interesting field.

"...the degree to which you think you know, assume you know, or in any way need to know what is going to happen next, is equal to the degree to which you will fail as a trader." - Mark Douglas
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  #62 (permalink)
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Fantastic thread, just reading it for first time.

It is now a Sticky thread.

Mike

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  #63 (permalink)
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Fat Tails View Post
@Anagami: Very dangerous conclusion: You have a nice system and you hope to make a win rate of 80%. If the win rate drops by 10% to 72%, your expectancy drops to zero.

Expectancy at 80% : 0.8 * (10 - 1.8) * $ 5 - 0.2 *(20 +1.8) * $5 = $ 32.80 - $ 21.8 = $ 11
Expectancy at 72%: 0.72 * (10-1.8) * $5 - 028 *(20 + 1.8) * $5 = $ 29.52 - $ 28.00 = 0.52 $

The problem is that the model calculates the fixed fractional amount based on the assumption that you have a known edge. This would hold true for card games, at least over the period during which the rules of those games are not changed. Trading is a game with ever changing rules, so there is an additional risk that the backtested or assumed edge does not exist.

No model covers the model risk, and here the model risk is huge, as it includes the assumption of a known and stable edge. Also there is an operational risk. Would you feel happy if you ran a position of 64 contracts of YM with an account of $ 100,000? The favorable results with the win rate of 80% heavily rely on leverage. The leverage is suggested by the Optimal F model, because it ignores model and operational risks.

Models simplify, so they should not be applied to reality without care. If I was to trade anything like this, I would rather rely on a Monte Carlo Simulation of a backtest and a forward test then a model. The model should only be used for understanding the basic mechanisms, for example it is certainly interesting if a model postulates that there could be an optimum size for trades.

Excellent summation!!

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  #64 (permalink)
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great math thread.

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  #65 (permalink)
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Great thread

Thanks for this thread. Right up my street.

Here's a curve ball. What about blending strategies sequentially to adjust overall potential?

For example, trade a 1:1 60% accuracy system to grind out a weekly (or daily, or monthly or whatever) target and then switch to a much a higher risk:reward system with a trailing stop on the weekly gains to limit downside exposure.

This is a type of 'barbell' approach where you can (in theory) get exposure to asymetrical payoffs.

Thoughts?

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  #66 (permalink)
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mokodo View Post
Thanks for this thread. Right up my street.

Here's a curve ball. What about blending strategies sequentially to adjust overall potential?

For example, trade a 1:1 60% accuracy system to grind out a weekly (or daily, or monthly or whatever) target and then switch to a much a higher risk:reward system with a trailing stop on the weekly gains to limit downside exposure.

This is a type of 'barbell' approach where you can (in theory) get exposure to asymetrical payoffs.

Thoughts?

I am not seeing any advantage of following this path. I would continue to trade the system with the R-Multiple of 1 and the win rate of 60%.

The only reason to trade two different systems in parallel (not sequentially!) would be a negative correlation of their returns. In that case drawdowns should be reduced allowing for a higher leverage.

The only problem with this approach is that the negative correlation often turns positive in a flight-to-safety scenario, and the higher leverage does not make things better either. See the demise of Long Term Capital Management. I think that they traded non-correlated or weakly correlated strategies, which turned out to be positively correlated when the flight-to-safety event (Russia defaulting on bonds) occurred.

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  #67 (permalink)
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Hi Fat Tails,

I guess my 'angle' on this is not purely maths based, but practical in how I can use it to trade better and that in my case incorporates my psychology. I do employ such a 'barbell' approach which panders to my split trading personality. Very safe most the time and then - after a line in the sand is crossed - very risky.

I think Paul Tudor Jones has said that after you have grinded out a 30 or 40% year you have earned the right to go for it and perhaps book a 100%+ year. From a psychological perspective this makes sense (or at least it does to me), as you will probably have needed to trade well to get to that level in the first place and will be well tunded in when you drop the hammer and increase risk and/or the targets.

So not to divert the OP's intention of the thread, I'll bow out.

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  #68 (permalink)
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mokodo View Post
Hi Fat Tails,

I guess my 'angle' on this is not purely maths based, but practical in how I can use it to trade better and that in my case incorporates my psychology. I do employ such a 'barbell' approach which panders to my split trading personality. Very safe most the time and then - after a line in the sand is crossed - very risky.

I think Paul Tudor Jones has said that after you have grinded out a 30 or 40% year you have earned the right to go for it and perhaps book a 100%+ year. From a psychological perspective this makes sense (or at least it does to me), as you will probably have needed to trade well to get to that level in the first place and will be well tunded in when you drop the hammer and increase risk and/or the targets.

So not to divert the OP's intention of the thread, I'll bow out.

I understand your position from a psychological point of view. George Soros called this going for the jugular .... What they probably meant is that once your have been profitable, it makes sense to increase size or to include trading strategies that may expose you to larger draw downs.

I do not think that this means necessarily switching to a different type of trade. You might simply build your position by pyramiding, once you have gained confidence, because the market has validated your strategy.

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  #69 (permalink)
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eudamonia View Post
From my own testing I've found that edges become relatively stronger the higher the timeframe (and holding time) of the trade. The more often you trade, the greater the vig and the more difficult it is to obtain an edge. So why trade short-term?

Trading short-term allows you to place more bets. Provided your strategy comes with an intrinsic edge (let's denote this with some fixed value called the expected mean of returns), Bernoulli's theorem states that the larger the number of bets, the closer the sample mean of returns approaches the expected mean. As such, you should experience a smaller deviation of the sample mean from the expected value for every fixed unit interval of time while your strategy is run. In more concrete wording, the more the number of bets, the smaller the deviation of your realized daily returns from the expected mean of daily returns that you should experience, and hence higher Sharpe ratio. It can be estimated that the maximum compounded growth rate attainable with your strategy varies with the square of your Sharpe ratio, an order of magnitude faster than losses from transaction costs. By this reasoning, quite the contrary, there is actually an absolute advantage in shorter time frames.

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artemiso View Post
Trading short-term allows you to place more bets. Provided your strategy comes with an intrinsic edge (let's denote this with some fixed value called the expected mean of returns), Bernoulli's theorem states that the larger the number of bets, the closer the sample mean of returns approaches the expected mean. As such, you should experience a smaller deviation of the sample mean from the expected value for every fixed unit interval of time while your strategy is run. In more concrete wording, the more the number of bets, the smaller the deviation of your realized daily returns from the expected mean of daily returns that you should experience, and hence higher Sharpe ratio. It can be estimated that the maximum compounded growth rate attainable with your strategy varies with the square of your Sharpe ratio, an order of magnitude faster than losses from transaction costs. By this reasoning, quite the contrary, there is actually an absolute advantage in shorter time frames.

@artemiso: Brilliant post, you hit the nail on the head.

However, there is one minor glitch. Transaction costs do matter. If you trade ever smaller timeframes, transaction costs will outgrow the intrinsic edge, and you strategy will be making losses.

That said from your statement above and the knowledge that transaction costs will overcome the edge for very small timeframes, you may conclude that there is an OPTIMUM timeframe to trade.

Under optimum I understand the timeframe that allows you to attain the maximum compounded growth rate.


I have tried to give an example for the optimum frequency / targets in the thread "Risk of Ruin". You will probably like these posts:

https://futures.io/psychology-money-management/15602-risk-ruin-7.html#post210597
https://futures.io/psychology-money-management/15602-risk-ruin-8.html#post210800
https://futures.io/psychology-money-management/15602-risk-ruin-8.html#post210847

The key is understanding that the variance of return matters, and that you more easily achieve a better variance with a high win rate than with a high R-Multiple.

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