Rotational Trading: Reduce Trades & Improve Returns

With this post I want to share some research I've done in the area of rotational trading (RT). In RT systems stocks or ETFs are ranked according to one or more properties. You ride the best stocks as long as they are among the best stocks, then you change horses and go again.
 
So far so good. Unfortunately some times you change stocks just to see that the stock you sold is doing better again and raising in your ranking. As we know the market has a certain amount of noise that can't be predicted or modeled, hence stocks will raise or fall just because of that noise.  This represent two challenges: trading cost and opportunity cost. Let me present you some ways how to reduce the impact of that volatility in ranking.

Background

There is a number of ways to reduce rank volatility.

1.) Trade only once a week / month

2.) Different criteria for enter / exit a trade

3.) Smooth the rank over the last couple of bars

4.) Combination of above

Test Environment

  • I run all tests on a survivorship free Nasdaq100 index ( January 2001 – June 2011)
  • All trades are close/close without slippage / commission
  • 10 portfolio positions (10% allocation), returns are reinvested
  • Data is adjusted for splits and cash dividends
  • Stocks ranked according to their Rate of change over the last 200 days (ROC200)
  • Ranking is re-calculated every day

Test 1) Weekly Rebalancing

In this test we compare daily ranking vs. weekly ranking. For weekly ranking I decided to re-balance at the last trading day of a week. Important to notice: also for weekly re-balancing daily bars are used for trading and rank calculation.

Number of trades have been reduced by 50+% while we see a modest improvement in absolute returns.

Test 2) Different Entry/Exit Ranks

In this test a trade is entered if the stock is among the best performing stocks and sold if it drops bellow a certain rank (10, 20, 30). Of course new stocks can only be bought if a portfolio slot has been (=an existing position drops bellow 10/20/30).

Interesting enough the absolute returns have improved significantly while reducing trade frequency by about 90%.

Test 3) Rank Smoothing

Instead of using the most recent rank value for taking trading action, the rank gets smoothed with it's most recent values. For this test I applied to different method, simple moving average (MA) and exponential smoothing average (EMA). Rank calculation and trades are done daily.

Applying a ten day EMA seems to be most promising in this case.
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Test 4) Combinations

In a last test we will look at combining different methods.
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Summary

The presented methods provide valid ideas to reduce market noise and improve returns for a simple rotational system. Considering that trading cost (slippage + comissions) has not been part of this test, the absolute return difference is even more significant. The applied methods reduced trades by about 50-90%. So which one is the best one? I prefer weekly rotational trading for my momentum system. However, at the end it's a matter of personal trading style and the specifics / efficiency of your ranking algo.
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Please let me know your opinion and ideas in the comment section bellow.
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- Frank
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