Model discussion

[Pierre Brodeur]

Pascal,

Although it might prove interesting to include evolving measure(s) of volatility to improvement the Market timing model, my intuition tells me that it won't make a great difference. Absolute non volatility measures of OB/OS do a very good job of estimating value (RSI & STO are absolute measures).

In my humble opinion, the Model needs to be confronted with a new independent variable in what could be a multiple factor model. Again, one of your friend's Billy indicator comes to mind: MA[$TICK] (600 minutes) slope would do a good job of measuring "the trend" and it is independent because it has nothing to do with volume analysis.

But the point here is not the variable to pick given that you are in a better position that any of us to figure out the best one(s) to select, but the addition of other variables.

Pierre Brodeur

[Timothy Clontz]

Just a generic observation: models generally run into trouble when they fine tune TOO much. Lowering the target and increasing the number of Robots might solve the problem. That is, instead of trying to squeeze the most out of the generic market, why not try to squeeze a little out of the juiciest ETFs?

The 9 sector ETFs I use in my own model are very highly traded, and I know you have a better model to tweak them with.

[TraderD]

Pascal,
Although it might prove interesting to include evolving measure(s) of volatility to improvement the Market timing model, my intuition tells me that it won't make a great difference. Absolute non volatility measures of OB/OS do a very good job of estimating value (RSI & STO are absolute measures).
Pierre Brodeur

An absolute measure of an OB/OS oscillator requires an absolute numeric threshold to be used. Since it's unrealistic (and often unwieldy) to expect the chosen threshold to always be right (ie high Win%), two other goals are typically preferred:
(1) Win a lot when you're right and lose a little when you're wrong (ie high gain ratio, which leads to high PF)
(2) Make the threshold choice such that performance isn't overly sensitive to slight changes of threshold value

The problem with OS threshold misses is that they inevitably lead to a large loss in the form of a string of mis-directed trades (repeated attempts to re-short an uptrend instead of being in buy mode). Only testing can check whether requirement #2 above holds with a choice of -70. My gut feeling is that this could be a problem without use of a more relaxed direction determinant, possibly involving another independent indicator.

Trader D

[Pierre Brodeur]

(2) Make the threshold choice such that performance isn't overly sensitive to slight changes of threshold value

The problem with OS threshold misses is that they inevitably lead to a large loss in the form of a string of mis-directed trades (repeated attempts to re-short an uptrend instead of being in buy mode). Only testing can check whether requirement #2 above holds with a choice of -70.
Trader D

No indicator is perfect, of course and as traders we have the luxury of being able to put any indicator in the current market dynamics context which many model have difficulty doing. That is why many modern models (especially risk models) have volatility regime adjustments to calibrate factor volatilities to current market levels. But that is a very difficult thing to do if only because risk is non linear. Others use nonstationary stochastic processes (ARCH & GARCH models) in order to deal with the fact that model coefficient do change over time. However, RSI for example has the advantage of being between 0% and 100% and thus if this would reflect the distribution ( normal or otherwise) of historical value (OB/OS) it would be a major improvement over the absolute indicators currently available or the current arbitrary OB/OS hard coded numbers (i.e.: 70) currently being used by Pascal.

My gut feeling is that this could be a problem without use of a more relaxed direction determinant, possibly involving another independent indicator.
Trader D

I believe we are in agreement on the need for another independent indicator.

[mingpan.lam]

Here's my opinions

1. 20DMF
--> agreed with Timothy, increased the numbers of ETF the robots trade, for example, when most ETF is in buy mode, the remaining neutral mode ETF cannot take short term short entry (a failed safe mechanism), alternatively, when most ETF is in short mode, the remaining neutral mode ETF cannot take short term long entry


2. The GDX MF

Model Weaknesses

• The model acts very fast on a signal change but might be prone to whipsaws, mostly due to the underlying volatility.
--> it happened in Dec last year, does it really due to volatility or does it due to the low volume because of holiday? Or, volatility due to the low volume?


3. The Robots

• Update the statistical trading tables for both robots
--> is it possible to automate the process for the statistical trading tables?


4. RT On-going development work

--> sms alert (can be done via twitter)

5. Sector Rotation (SR) trading model

--> can we use GDX MF model to run on each different sectors? Then we don't need to worry about the stock.

--> I think real time system will be v. useful to provide a better entry and tight stop but we need an real time alert system.

[senco]

The biggest challenge we have is a very short history of data available for backtesting; any idea that will resolve the few occurrences where the model broke down cannot be confirmed with statistical confidence. For this reason, the 20DMF had a couple of tweaks in the past. Were those optimal? We shall probably know only in many years from now (n fact, we trust the model because it makes fundamental sense, not because of a thorough out of sample statistical validation – for this we do not have sufficient data points. Adaptive OB/OS determination makes sense and it might be more robust than an arbitrary level. Maybe.
So what can one do? On a conceptual level: (a) keep the model as simple as possible – the less parameters, decisions and ‘knobs’ there are - the less brittle it will be, (b) introduce additional data points of a somewhat different ilk by incorporating other indicators (for decision, confirmation, or vote), and (c) use several systems/robots for diversification. Well, all ideas mentioned earlier in this thread :-)
On a practical level – there are a number of ‘breadth related’ indicators that could be used quite effectively to (i) identify bottoms - maybe combine with 20DMF in some voting mechanism, and (ii) identify a bullish state of the market – to get the 20DMF out of a ‘neutral’ state, and/or be used together either in a voting, or an allocation mechanism.
By ‘breadth related’ indicators I mean things like: new highs/new lows, volume or issues advance/decline, TICK, TRIN (Arms), number of issues over or crossing a moving average. These days the data for these indicators can be easily accessed in real time - see my comment in the Tradestation thread.
Breadth models try to measure the underlying happenings in the market as the MF does, though in a different way - and they can be used to create good timing models on their own. There is a good possibility that combining them with 20DMF will increase the model's robustness.

[senco]

While at it, a couple of general thoughts:

- Whipsaws: If the losses on whipsaws are small, best to look at those just as the cost of doing business. Many systems whipsawed in the huge volatility of last year much more than in the last twenty years, simply bringing out the reality of the market... politicians and central banks flip-flopping.

- When modifying / tweaking a model, it is a good idea to continue and maintain full data series (past and future) of both versions, not just discard the old one. In my experience one can still learn from systems abandoned many years ago.

- We are very interested in the Maximum Drawdown of a backtest (and more than that, of a system we trade live). It is also important to understand that the MDD does not represent well the statistics of a trading system output (it is the outcome of a specific path in time, out of many that could have happened). Therefore, MDD is not a good predictor of a system’s future drawdown and is not a good measure for a system’s risk. The saying “your worst drawdown did not happen yet” has indeed a theoretical basis. When comparing different versions of a system in development - it is much better to use measures with more statistical contents, like a rolling period downward deviation.

[TraderD]

While at it, a couple of general thoughts:
- Whipsaws: If the losses on whipsaws are small, best to look at those just as the cost of doing business. Many systems whipsawed in the huge volatility of last year much more than in the last twenty years, simply bringing out the reality of the market... politicians and central banks flip-flopping.

AFAICT, EV as a follower of large money can only be as good as they are. 2011 performance of large funds have been rather dismal (an understatement), so it's likely to expect EV to deteriorate in its predictive ability. Paul in a recent GGT post shows a bunch of examples where contrary to LEV divergence, price keeps going in the other direction, which begs the use of this technique with other indicator(s) as you've suggested, or at least a much more accurate understanding where EV does work.

- We are very interested in the Maximum Drawdown of a backtest (and more than that, of a system we trade live). It is also important to understand that the MDD does not represent well the statistics of a trading system output (it is the outcome of a specific path in time, out of many that could have happened). Therefore, MDD is not a good predictor of a system’s future drawdown and is not a good measure for a system’s risk. The saying “your worst drawdown did not happen yet” has indeed a theoretical basis. When comparing different versions of a system in development - it is much better to use measures with more statistical contents, like a rolling period downward deviation.

Fully agree with MDD comment. Do you have a link to RPDD stat calculations?

[Pascal]

While at it, a couple of general thoughts:

- Whipsaws: If the losses on whipsaws are small, best to look at those just as the cost of doing business. Many systems whipsawed in the huge volatility of last year much more than in the last twenty years, simply bringing out the reality of the market... politicians and central banks flip-flopping.

Whipsaws is a clear limitation in the EV based models and must be dealt with with great care.
Indeed, we have seen the EV often moves in a direction opposite to price on single stocks, because large players would take advantage of higher liquidity to buy/sell positions contrary to the price move. However, when a stock/Sector is on its lower boundary or in oversold, then a bounce in EV might indicate that there is real accumulation because the stock/sector is "cheap".

Hence, when I applied the OB/OS MF model to the 96 sectors that I defined, I noticed that the return was lower than using the usual simpler sector model to buy and short. The reason was simply that the sectors are in a "hectic" manner when in OB/OS. They will switch up/down until they stabilize and move definitively in a new direction. I believe that this is a factor that is "inherent" to EV , especially on single stocks or on a basket of a few stocks.

However, industry groups and total market level measures are less prone to EV whipsaws, because they do compensate each other. We would need the majority of the stocks in the sector to be bought and then sold the next day to have whipsaws on an industry level. This has fewer chances to occur and hence, OB/OS works better the more stocks you use in the basket.


Pascal

[xr-3609]

WOW! Great work! It looks like we need a new instrument to trade the EV Sectors......maybe a "synthetic EV ETF" based on the best five sectors/stocks when a 20DMF signal comes down (or up)!

Greg