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This is a guest post by Wayne Whaley, CTA:
I recently posted research on the 40 year (1970-2009) track record of various simple moving average crossover systems on the S&P Cash Index in a post titled “The 200 Day Moving Average Is Your Friend“. See that link for details, but a summary of those study results is shown below. I have added a new column, which shows the maximum loss in any given month for the various trading systems.
To be clear, the 200 day system takes longs above the moving average and moves to 3 Month T-bills below the moving average.
The previous study deemed that the 200 day moving average system, where one moved to T-bills on all short trades was attractive because it’s return was competitive with buy and hold with much less risk than buy and hold (see “Largest Monthly Loss” column above).
There are almost an endless number of permutations of these simple moving average trading systems that can be studied. One that is popular is the “Golden Cross” system, where rather than receiving a signal when the end of day price penetrates the 200 day moving average, you must wait until a faster moving average (in this case, 50 day moving average) penetrates the longer (200 day) moving average.
I decided to look at 10-50 day moving average trends penetrating the 100-350 day moving averages, to see if the backtested results would improve the previous single day trading results. You can see the results below, with the same assumptions as before: go long when the shorter moving average exceeds 1% above the long moving average and short when the moving average exceeds 1% below the longer moving average.
Trading the “Golden Cross” system with the 50 day moving average against the 200 day moving average produced an annual return of 6.86%, with an average profit of 11.10% on longs and an average loss of -1.17% on the shorts. However the best system that I found over the 40 year database was to trade the 10 day moving average against the 250 day moving average.
This system resulted in an average annual return of 7.47%, with a 11.53% return on the longs, a modest -0.91% loss on shorts and it’s worse monthly loss was -14.45%. One possible drawback is that it would generate many more trades than the standard “Golden Cross” system.
If you allowed yourself to move to Treasury bills on shorts, the Golden Cross 200/50 system would improve to 9.38% and the 250/10 system would improve to 9.71%
Summary of all of moving average crossover studies:
A Buy and Hold strategy over the last 40 years had an 8% average annual return and 11.5% when dividends were added.
The best single day price vs. moving average system that we studied was the 200 day moving average system with 9.20% return when short positions resided in T-bills.
The traditional “Golden Cross” 200/50 day system yielded a very similar 9.38% return when shorts were allowed to reside in T-bills.
The best system I tested over the last 40 years was the 250/10 system which yielded 9.71% when shorts were allowed to reside in T-bills.
The 250/10 system would have the drawback of increased transactions, that introduces additional cost and trading slippage into performance, which may offset its modest increased performance.
All of the systems discussed in above, had similar net performance to the buy and hold strategy, but much less risk profiles than the Buy and Hold strategy since they all spent roughly 1/3rd of the trading days in the security of T-bills.
Whether using the simple end of day price or some moving average of price, the results of this analysis supports the institutional popularity of the 200 day type moving average systems, with long, solid, consistent, low risk profit. However, there was little difference between trading performance between using end of the day price or a shorter moving average for generating the trading signals.
There is no guarantee that the market will show the same trading characteristics over the next 40 years that it did in the last 40 years and it is actually almost a given that a different combination of moving average systems will yield the optimum result going forward.
I suppose if you wanted to make a career out of studying these type systems, you could now look at the optimum exponential moving average to use as opposed to simple moving averages.
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