LT/ST conflicting situations

[Pascal]

On Friday, I posted the following IWM Robot comments:

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 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.

[Andrei]

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.

[Pascal]

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.

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

[EB]

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.

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.

[Timothy Clontz]

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.

[Pascal]

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.

Attachment 11228

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.



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.



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.




Pascal

[mingpan.lam]

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

[Timothy Clontz]

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

Ellis,

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

Tim

[mingpan.lam]

Ellis,

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

Tim

Thks Tim.

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

[Andrei]

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.

Attachment 11232

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.

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!