2007 Sep 11 - Tue

Recent Paper on Profitability of Technical Stock Trading

There is a recent, very readable paper from Stephan Schulmeister called The Profitability of Technical Stock Trading has Moved from Daily to Intraday Data. His abstract goes like this:

This paper investigates how technical trading systems exploit the momentum and reversal effects in the S&P 500 spot and futures market. The former is exploited by trend-following models, while the latter by contrarian models. In total, the performance of 2580 widely used models is analyzed. When based on daily data, the profitability of technical stock trading has steadily declined since 1960 and has become unprofitable over the 1990s. However, when based on 30-minutes-data the same models produce an average gross return of 8.8% per year between 1983 and 2000. These results do not change substantially when trading is simulated over six subperiods. Those 25 models which performed best over the most recent subperiod produce a significantly higher gross return over the subsequent subperiod than all models. Over the out-of-sample-period 2001-2006 the 2580 models perform much worse than between 1983 and 2000. This result could be due to stock markets becoming more efficient or to stock price trends shifting from 30-minutes-prices to prices of higher frequencies.

One of the interesting comments he makes is that contrarian strategies appear to be more profitable than do trending strategies.

In the article, the author offers up some possible reasons why technical trading is harder (but I should temper that remark and say that successful trading is more profitable with 'higher frequency' data--5 minute bars over 30 minute bars or daily data):

The decline in the profitability of technical trading based on daily data could be explained in two different ways. The "adaptive market hypothesis. (Lo, 2004; Neely-Weller-Ulrich, 2006) holds that asset markets have become gradually more efficient, partly because learning to exploit profit opportunities wipes them out, partly because information technologies steadily improve market efficiency (Ohlson, 2004). The second explanation holds that technical traders have been increasingly using intraday data instead of daily data. This development could have caused intraday price movements to become more persistent and, hence, exploitable by technical models. At the same time price changes on the basis of daily data might have become more erratic. This would then cause technical trading to become less profitable based on daily prices (but not on intraday prices).

Another interesting quote I came across regarding how everyone's trades get jumbled together, and what trader's think about it:

... traders have to form expectations about expectations of all other traders (Keynes. "beauty contest. problem).

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