Model discussion

[Pascal]

Not yet for GDX. Next week probably.

For your ease, I attach a file with the GDX trade records.
Since inception, the EOD GDX Robot produced a return of 13.98%.
The EOD combined to the RT GDX MF with all the signals produced 25.10%.
The EOD combined to the RT GDX MF with only the strong signals produced 32.33%.

These results are not exceptional, but they are not catastrophic either (Buy and hold produced a return of -28.06%.)

This trading environment is very challenging to say the least.



Pascal

GDX_record.xls

[Harry]

Dear Pascal,

Thank you for the updated trades and thoughts. Speaking for myself, a RT model is not much use unless a RT email alert system is developed. Even so, it still may be of no use as I spend a large part of my day away from the desk.

If time determines the RT system to be the way to go, I wonder if you have considered using IB or Tradestation and setting up an account where others can link and mirror your account's trades? With IB I believe you can earn a % profit (not sure about Tradestation)? Anyway, this may be an option for those not near the PC during market hours?

[Rembert]

Let's have a look at the GDX robot. For an explanation of some terms used here I refer to my IWM robort analysis on the previous page. For some EOD trades I don't have the initial stop data so I replaced those by an average stop as calculated from PdP's Excel file. Regarding the real time models I did the same but used the average for all trades. This means the results will not be entirely accurate so take them with a grain of salt. I think the general picture will not be too far off regardless.

Let's start with the EOD model ...



Overall the numbers are an improvement compared to IWM. Based on the trade history GDX seems to have a positive (albeit small) expectancy and a low standard deviation resulting into a SQN number of about 1.65 (see previous post for SQN interpretation table).

The GDX model rules ensure that a position is often closed before the full R1 stop is hit or a high R multiple of profit is reached. This translates into a low standard deviation helping the model be more consistent. Tough the large initial stops makes it hard to get a high R profit resulting in a lower expectancy.

What about position sizing ? Well that's up to each individual. As a guideline one can have a look at these tables using the SQN number. Keep in mind these drawdowns are for the entire account and on top of any other mech/disc trading you might be doing.



The compound return of the EOD GDX is 9.75% when putting one's entire account unleveraged into each trade. Of course in real life that's not how it works because taking that much risk on each trade carries a huge risk of ruin with it and can be called gambling at best.

Let's say you take a reasonable 1% account risk per trade. Since the model made 2.90R in total you would have made 2.90%. Combined with the IWM model's -5.25 R at 1% account risk per trade that would translate into a combined loss of 2.35%.

I realise I'm stating the obvious here but this is kind of disappointing. Especially since I like the concept and believe it can work. Another thing to note is the small sample size of trades we have at the moment which might not be a true representation of the robot's capabilities in all kinds of different market regimes. That being said I can't say the robots are a viable investment for me at this stage. I would like to see an improvement in the models KPI's first.

To end on a positive note let's have a look at the GDX RT results ...

RT (strong signals only) shows some promise with better results compared to the EOD model. RT with all signals performs about on par to EOD.

[mklein9]

I couldn't agree with you more, Rembert. Great work and well stated. I also have a strong belief in the underlying concept of EV, but have had issues with the implementation recently. It seems to me that the effort to add complexity in the layers on top of EV should be spent instead on increasing the signal-to-noise ratio of the EV signal itself, so that those added layers become unnecessary. The primary issue I believe the development team is dealing with is absolutely fundamental: insufficient signal, insufficient samples to provide reliable indications, judged by statistical measures of robustness. Maybe the RT approach provides some of that, but like some others here I cannot take advantage of RT.

-Mike

[asomani]

Thank you very much, Rembert. The information you provided is quite helpful. I'm always keen to read your thoughts, as well.

[Pascal]

Let's have a look at the GDX robot. For an explanation of some terms used here I refer to my IWM robort analysis on the previous page. For some EOD trades I don't have the initial stop data so I replaced those by an average stop as calculated from PdP's Excel file. Regarding the real time models I did the same but used the average for all trades. This means the results will not be entirely accurate so take them with a grain of salt. I think the general picture will not be too far off regardless.

Let's start with the EOD model ...



Overall the numbers are an improvement compared to IWM. Based on the trade history GDX seems to have a positive (albeit small) expectancy and a low standard deviation resulting into a SQN number of about 1.65 (see previous post for SQN interpretation table).

The GDX model rules ensure that a position is often closed before the full R1 stop is hit or a high R multiple of profit is reached. This translates into a low standard deviation helping the model be more consistent. Tough the large initial stops makes it hard to get a high R profit resulting in a lower expectancy.

What about position sizing ? Well that's up to each individual. As a guideline one can have a look at these tables using the SQN number. Keep in mind these drawdowns are for the entire account and on top of any other mech/disc trading you might be doing.



The compound return of the EOD GDX is 9.75% when putting one's entire account unleveraged into each trade. Of course in real life that's not how it works because taking that much risk on each trade carries a huge risk of ruin with it and can be called gambling at best.

Let's say you take a reasonable 1% account risk per trade. Since the model made 2.90R in total you would have made 2.90%. Combined with the IWM model's -5.25 R at 1% account risk per trade that would translate into a combined loss of 2.35%.

I realise I'm stating the obvious here but this is kind of disappointing. Especially since I like the concept and believe it can work. Another thing to note is the small sample size of trades we have at the moment which might not be a true representation of the robot's capabilities in all kinds of different market regimes. That being said I can't say the robots are a viable investment for me at this stage. I would like to see an improvement in the models KPI's first.

To end on a positive note let's have a look at the GDX RT results ...

RT (strong signals only) shows some promise with better results compared to the EOD model. RT with all signals performs about on par to EOD.

Thank you Rembert. This is a great work.



Pascal

[Rembert]

Nice to hear you guys liked my post. Regarding RT signals. Like some members have mentioned ... for many (including me) it's near impossible to execute trades in realtime. I don't know if it would hurt performance but I wonder if a possible compromise could be to send an e-mail alert like 20 mins before the close with the RT status at that moment. Members can then put a market on close order in with their broker if action is needed. This would also eliminate many potential intraday whipsaws by the RT system.

[Pascal]

I believe that it is important to see how the model operates in today's environment.
Below is a MF figure for the past 500 days. Please focus on the distance between signals. You can see that on the right of the Figure, we have had many signals issued: the model is whipsawing. This tells us that the model does not react well in this environment when cheaper PM miners attract more money because of a "safe heaven" feeling of gold related investments, but then goes down fast the next day when gold reacts negatively to us US$ bounce.



I believe that the model will work again in a more appropriate environment. However, today's environment is what we are faced with (Tuning the model to use longer time frame will fix the most recent whipsaws, but will destroy past performance.)

Turning to the RT model, we can see even more whipsaws. The model avoids us being on the wrong side of the trade, but the many whipsaws render an execution almost impossible, even for me. We also all know that whipsaws can kill a portfolio, especially when one uses leverage.



When we look at the average returns of each normal "Buy" trades from the GDX MF, we can see that for the first days of trading, the drawdown is important, while the return is almost nil. The figure shown below tells to "give room to the trade." However, the RT model works on the opposite of that principle: it says "change the position because there is a MF directional change". Since December 22, the EOD strategy produced a loss of 4%, while the RT strategy produced a gain a little higher than 9%, but with 2.5 times more trades, whose execution itself might be an issue.



When we now look at the Bought Oversold signals, it is clear that these are better signals, with quicker payback and lower DD. However, we did not have such a signal since Mid of last year. A pretty safe strategy, but hardly a strategy that meets the need of an "active trader" like me.



This is the reason why I am sticking to my strategy explained earlier: at each normal buy signal, I buy a 2014 leap using 10% of a normal position. This allows to "give room to the trade," while limiting the risk to a small position. The danger is that if the market continues to whipsaw, I would be forced to buy new leaps at every (cheaper) buy signal and end up building a losing position which could stay against me if the sector continues to be negative for another 18 months, which I doubt it will.

Yesterday, while I was not at my desk, the RT system issued a buy signal. Maybe time for another leap, if I can it cheap today.



As a last word: you might have noted that most XLX models produce better trades when the signal is "Buy Oversold".
One strategy could be to Buy one position on a buy oversold signal of an XLX ETF and buy two positions when this signal is in the same direction as the 20DMF, but trade short only when the 20DMF issues a short signal.

For such a strategy, an E-mail alert system in RT seems appropriate, with a confirming e-mail 20 minutes before the close.

Anyway, something to think about.


Pascal