LT/ST conflicting situations

On Friday, I posted the following IWM Robot comments:

[I]It is frustrating that the IWM Robot sat out the last uptrend. As I explained earlier, this was due to conflicting ST/LT edges that developed rather early in this uptrend (pink arrow) and forced the robot to revert to cash.

From that point on, the IWM robot would have taken a new position only if a strong signal had been issued.

Below is the figure that represents the LT/ST edge evolution. We can see that the conflict continued for nine days before it was resolved with a buy signal (blue arrow), but one that was neutral.

This ST/LT figure raises the following question: When a position has been interrupted by conflicting edges, is it better to consider that the original signal is still valid when the conflict resolves in the direction of the original signal?

I will study past ST/LT conflicts and see what results we have.

Please note that at yesterday's close, we again had a LT/ST conflicting situation.


Pascal[/I]

[ATTACH=CONFIG]11219[/ATTACH]

I did some further research to see if at the blue arrow (conflict is being resolved), we could consider that the previous signal (green arrow) was still valid.

I did such an experiment whose results are shown below. The returns are slightly improved, but we can see that even if the last case produced a 9.69% return, the two previous case produced very negative returns. All in all, 12 positive and 10 negative.

[ATTACH=CONFIG]11220[/ATTACH]

[ATTACH=CONFIG]11221[/ATTACH]

In other words, it is best to keep everything as it is right...?

Pascal, have you ever considered adding an outside element to the Robots, for example any of the existing market indicators, be they momentum, trend, breadth or any other, to further improve methodology? I am asking simply to know your opinion on whether you think Robots are fully self-sufficient, or you think theoretically they could benefit from such fusion?
(by the way, I am well aware that any change would require hell load of a backtesting)

Thanks.

[QUOTE=Andrei;18183]In other words, it is best to keep everything as it is right...?

Pascal, have you ever considered adding an outside element to the Robots, for example any of the existing market indicators, be they momentum, trend, breadth or any other, to further improve methodology? I am asking simply to know your opinion on whether you think Robots are fully self-sufficient, or you think theoretically they could benefit from such fusion?
(by the way, I am well aware that any change would require hell load of a backtesting)

Thanks.[/QUOTE]

Andrei,


When you develop a trading system, the issue at some point is to identify the weaknesses and then find solutions.
However, trying to include new indicators without knowing what you want to improve is not helpful.

Regarding to your first question: is it best to keep the system as is?
The first question is to find if there is an issue with the set of conflicting situations that I published.
What lies in the background of this set of data? There is something obvious that leads to the real question and thus the real improvement that I just tested in the past few hours.

I will write later about this issue.


Pascal

[QUOTE=Pascal;18186]Regarding to your first question: is it best to keep the system as is?
The first question is to find if there is an issue with the set of conflicting situations that I published.
What lies in the background of this set of data? There is something obvious that leads to the real question and thus the real improvement that I just tested in the past few hours.
[/QUOTE]

Not sure if this is the "obvious" to which you refer, but there were a string of large winning trades that would have been missed at the beginning of the 2009 bull...just a few weeks after the QE1 announcement.

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The purpose of a model is not only to maximize reward but to optimise the reward to risk ratio. Higher losses could offset that ratio even with slightly improved reward.

[QUOTE=EB;18187]
Not sure if this is the "obvious" to which you refer, but there were a string of large winning trades that would have been missed at the beginning of the 2009 bull...just a few weeks after the QE1 announcement.

[ATTACH=CONFIG]11228[/ATTACH][/QUOTE]

Exactly! Then, the second obvious issue is that the great majority of the LT/ST conflicts are on "buy" signals.
It means that the IWM robot had conflicting situations on buy signals, especially at the start of QE1 and also in the past weeks. The common points between these two periods is the high volatility. High volatility is linked to fear and to better shorting opportunities. Hence, the IWM Robot does not see that at specific points in the market life, high volatility was a consequence of forced shorts covering.

We can see in the list below - from which I erased the short signals - that the average ATR is 3.43% this is 1% higher than the average ATR for the past 5 years. This confirms that there is a volatility interpretation issue.

[ATTACH=CONFIG]11232[/ATTACH]

The question is now: how can we build a filter that would sort out the bad red trades and keep the good green trades. This is where I'd go to Andrei and ask if he has in his tool box some sort of indicator that can do such a job.

I found such a filter and used it to build another column.

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I then sorted the results, seprating the positive from the negative of this new filter.
I believe that we now have an improvement over the existing IWM Robot, that takes care of Buy signals in high volatility environments.

[ATTACH=CONFIG]11234[/ATTACH]


Pascal

Look like this filter is used to identify the short covering activity by setting a threshold for ATR. Is this filter ATR - average(ATR) ??

[QUOTE=mingpan.lam;18192]Hi Timothy,

How do you measure your system's reward to risk ratio when you back test your system? I also focus on profit and max drawn down and I think measuring the reward to risk ratio may be a better choice.

average (Profit/drawdown)

Cheers,

Ellis[/QUOTE]

Ellis,

I measure average profit over [I]maximum [/I]drawdown, rather than average to average. The problem with volatility is the human element -- there's only so much pain I can handle. :-)

Tim

[QUOTE=Timothy Clontz;18193]Ellis,

I measure average profit over [I]maximum [/I]drawdown, rather than average to average. The problem with volatility is the human element -- there's only so much pain I can handle. :-)

Tim[/QUOTE]

Thks Tim.

Very true. Something the backtest result is good but when the drawdown happens, you feel the pain !!

[QUOTE=Pascal;18191]
We can see in the list below - from which I erased the short signals - that the average ATR is 3.43% this is 1% higher than the average ATR for the past 5 years. This confirms that there is a volatility interpretation issue.

[ATTACH=CONFIG]11232[/ATTACH]

The question is now: how can we build a filter that would sort out the bad red trades and keep the good green trades. This is where I'd go to Andrei and ask if he has in his tool box some sort of indicator that can do such a job.

I found such a filter and used it to build another column.
[/QUOTE]

My answer would be, that honestly I have no idea! But I see that you found such a filter... So, what is that column to the right?

Great job, Pascal!

Regarding measuring risk/reward of a system: Maximum drawdown is not a very good measure for system risk. Also it is not a good predictor for[I] future [/I]drawdown. There is math logic behind the popular saying "the worst drawdown of a system is yet to come".
We look at backtests trying to get an estimate for a system's future behavior with an underlying assumption that the statistical characteristics will remain the same. But the maximum drawdown is not a good representation of the statistical distribution of trade results; it expresses just a single path of trade that occured up to this point.
A simple example: The following trade results could come from two systems with similar statistical characteristics:
A. +2 -3 +2 -1 +2 -2 +1
B. +2 -2 -3 -1 +2 +2 +1
In evaluating the potential risk of a system, measures that look at the statistics of trade results and not a single path would be more predictive. Downward Deviation, or Downward Deviation of rolling periods would be a much better measure for system's risk. Sortino, or even Sharpe Ratio would give a better prediction for future system risk adjusted return than (past profit) / (maximum drawdown).

[QUOTE=Andrei;18195]My answer would be, that honestly I have no idea! But I see that you found such a filter... So, what is that column to the right?

Great job, Pascal![/QUOTE]

The issue with ATR is that it is un-directional. So what we need is simply to get the direction back into ATR or at least have an indicator that separately produces the ATR direction.

Standard Wyckoff or Larry Williams indicators usually say that when the price finishes at the top half of its day range, this is a positive sign of accumulation. The idea is simply, instead of using the day's range, to take the day's true range, get the mid-point and calculate the ratio of the difference between the close and the mid-point to the mid point. (Close-Midpoint)/Midpoint. This small formula gives you a directional strength of the true range. What I do is then calculate the 20EMA of that value. if it is negative then the buy trade cannot restart when the LT/ST conflicts stops. Otherwise, it can restart.


Pascal