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|Subject: Blending at a Whole New Level||Date: 7/22/2008 12:37 AM|
|Author: Zeelotes||Number: 211385 of 264123|
Although some may think that moving between blends based on the market's environment is too prone to curve-fitting, in my view the opposite is the case. It only makes sense to me to have the blend match the environment. My greatest concern all along as it relates to curve-fitting was the tendency of most to arrive at a blend using the Solver and all of the screen's history with the thought that what was a perfect match with the past would be a perfect predictor of the future. In my book, that is the premier definition of curve-fitting. Of course, with the work last fall a new standard was set for arriving at a blend. A standard based on using all the history up to the date of the new blend's selection (end of each year) for the next year's investment. Then to take that idea and backtest it going forward from the earliest available data right up to the present to see if it actually worked, not just a hope and a prayer, but a system built on concrete evidence that the method had worked in the past and should continue to work going forward.
It only makes sense that a measure that is the most predictive for bullish periods will not be the measure that is most predictive for bearish periods. How could that not be the case? Obviously, it must be. It is for this reason that I set out on this backtesting journey to determine if it would be possible to find a way of doing this that would have worked in real-time historically.
Determining the Bullish and Bearish Periods
Some may have the thought that this is the most important element in the mix. I don't think so. I've tested exponential moving averages on various indexes and the results are pretty consistent. All outperform a random selection of screens for a blend and most definitely outperform an equal weight of all screens by a huge margin. I've also tested other timing systems and found the results to be consistent. The primary component, therefore, is not the means for identifying the periods, but rather, the consistency in doing so.
So I thought I'd pull out one of my simplest methods for determining bullish and bearish periods. It simply takes the new highs and new lows of the index and subtracts the one from the other and applies a weighted moving average to the result to remove excessive whipsaw. When it is above, say zero, you are bullish, and when below, you are bearish. I've used values I've tuned a bit, but anyone is welcome to get the data from Pinnacle and go through the same process. This results in more trades than with the EMA crossovers, but I prefer it anyway simply because it is something that is tried and true and has a very long history of out-performance. From 1978 the Nasdaq Composite has returned a CAGR of 25.25% during the bullish phases and -8.07% during the bearish compared to a long-term buy and hold of 10.89%. Using this indicator the signal turned to bearish on 10/19/2007 and has remained so till now. Can't hardly beat that, now can you?
Treynor/GSD for the Full History as a Benchmark
As a benchmark I'm using the Treynor/GSD which was selected last November as the absolute best measure when used for the full history -- that is, without dividing up between bullish and bearish periods.
Begin Date: 1/2/1989
All Measures Compared
The following table is the fruit of a test where all measures are used for the period up to 7/18/2008. The test compares using Ascending and Descending sort. I'm sorting the results based on the highest return during the bullish period using a descending sort. Here we see that the Sharpe Ratio has finally gotten its revenge since it comes out on top. In fact, Sharpe/GSD descending produces the highest return for the bearish period for the descending sort measures -- some are higher for ascending.
ASC ASC ASC ASC DESC DESC DESC DESC
Nothing comes close to the Sharpe for the bullish period whether you use an ascending or descending sort. But for the bearish period you can also see that under ascending sort these three do quite well: Correlation, Ulcer Performance Index, and Normalized Trough Count. I'll be showing the results of these below.
Improved Blends -- Raising the Blend to a Whole New Level
Here is a table showing the results from above which I will follow with some comments and observations:
Begin Date: 1/2/1989