Model discussion

[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?

[Pierre Brodeur]

I'm not sure I see the benefit of RSI over the current OB/OS oscillator, which is also bounded by a fixed range (-100,+100).
Trader D

I am not suggesting the use of RSI at all. I am using it as an example in this discussion

[Pascal]

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.

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

EV detects an equilibrium and not a force. It statistically detects when money comes in/out. For a single stock, the movements of money will often be opposite to the price moves, because large players use available liquidity to buy/sell. However, when the price is in a trading range or at a turning point, EV will often show what is happening below the surface and what the next move will be. This is why I always use AB/LER as a combination.

The money flow is however more predictive when it is collected by sectors or industry group.

Also, large money does not necessarily mean that these are large funds. It could be some artificial FED liquidity injection. Therefore, I believe that your statement that EV's predictive ability will deteriorate might or might not be true. I however believe that EV still gives early warnings of what large money is doing. A few years ago, I noted that it could give up to one day advance warning. Today, because the level field is pretty high and everybody is running fast computers, the warning time is probably less than a day.

Anyway, I still prefer to know where the money is going than not to know it.


Pascal

[Pascal]

I am attaching here a general figure of the different models that are in use, but also of a back-test campaign made last week using these models.

We can see that the one level that cannot be traded is the sectors level, simply because these are sectors that I have defined myself and for which there is no instrument. These sectors are mainly used either for the 20DMF or for the stock filters.



Below are the yearly returns of the S&P and the 20DMF. These are returns compounded within one year. If a 20DMF trade is overlapping two years, I separated taking one part in one year and the second in the following year. This way, we can have a better comparison.



The objective of this back-test work was to measure the relevance to trade sector information.
Is it good to buy a sector when the sector issues a buy signal and short it when it issues a short signal?

The results are below. We can see that indeed, sectors trading is better than B/H on the S&P 500.
However, sectors trading in sync with the 20DMF is still better. Unfortunately, "in Sync" does not give better results than the 20DMF itself.

These results are not surprising: they are "in line" with what I had when I did a similar back-test two years ago.
My conclusion at that time was that even when a sector is flashing a buy signal, it still needs to be as close as possible from a 20DMF buy signal. The later we are from that signal, the worst the returns.



Therefore, the next idea was to select only five sectors when the 20DMF issued a signal and then from each of these sectors, get all the stocks AB/LER data and select the five stocks that were showing the best AB/LER combination. The results of such a test are shown below. These are also in line with the results I had two years ago. The table below show us that whatever efforts we can do to select specific stocks, it will be hard to beat a two time leveraged ETF that trades the 20DMF signals. Of course, specific stock trading might lead to lower DD (I did not calculate such DD.)



I however did another test that gives interesting results.
I selected one date in the past and decided to trade either long or short by intervals of 20 days from that date.
this means at day one, I buy the five best sectors and I sell them at day 20.
The five best sectors are those that show the weakest price RS.
On day 20, I again select the five best sectors and buy them.

On exactly the same day, I also short the five sectors that are the most overbought and I sell these positions 20 days later.

The results are shown in the table below.

We can see that this dumb strategy worked well for longs in 2009 and for shorts in 2008.
In 2010 and 2011, it did not work that well.

However, this strategy shows something important: the rotational aspect of the market. It shows that it makes sense to rotate money. This is of course obvious! I still prefer to see it in the data than not seeing it, because this means that it will probably make sense to develop a set of ETFs MF by industry groups and rotate between them.




I will now start working on these industry group MF models.


Pascal

[TraderD]

...
I will now start working on these industry group MF models.
Pascal

Pascal, how do you explain the (admittedly anecdotal) observation that test results of models that use 20DMF invariably show 2010/2011 performance to be lower (typically much lower) than 2008/2009 performance? Is there a reason to suspect the market is becoming more "efficient" in arbitraging away the edge attributed to money flow rotation?

Trader D

[Pascal]

Pascal, how do you explain the (admittedly anecdotal) observation that test results of models that use 20DMF invariably show 2010/2011 performance to be lower (typically much lower) than 2008/2009 performance? Is there a reason to suspect the market is becoming more "efficient" in arbitraging away the edge attributed to money flow rotation?

Trader D

Simple: 2008 and 2009 were trending markets. Crash and reversal from a deep bottom.


Pascal

[mingpan.lam]

Hi Pascal,

Which model GDX robot using in the above table?
Cheers,

Ellis

[Pascal]

Hi Pascal,

Which model GDX robot using in the above table?
Cheers,

Ellis

The second level: Industry group

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

[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