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Backtesting technical indicators (that determine market psychology) - how well would they have done?

For example RSI was published in 1978. Before its creation - did it performed better or worse?

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A simple model for any trading strategy that is fitted using historical data is that the in-sample performance is some combination of

  1. Genuine alpha
  2. Overfitting "alpha"

and that out of sample, you just get the genuine alpha. Additionally, alpha may decay over time, but it is unlikely to improve. In the absence of other effects, you would therefore expect any trading strategy to have much better performance before it was published and became widely known.

To test this with RSI, I used a data set of 32 commodity futures from 1960 to 2016, and created a simple trend-following strategy that uses the RSI indicator with a 21-day lookback period. Trades on day t are formed using information up to and including the close of day t-1, and are assumed to be executed at the closing price on day t. Positions are sized to give roughly equal risk in each contract over the entire sample. All results are gross of transaction costs.

The results pre- and post-publication are

                        1960-1978    1979-2016
Annualised Return           8.79%        3.54%
Annualised Volatility       5.97%        5.49%
Sharpe Ratio                1.47         0.64

It is clear that the strategy has not performed as well since it was published, and in fact it has been completely flat since 2009 - indicating a possible post-publication effect.

Of course, other explanations should be explored (e.g. running a systematic strategy with daily rebalance may not have been feasible before the widespread availability of personal computers, or transaction costs may have been prohibitively high in the past).

One final note - I have used the RSI as a momentum indicator here. The original article, published in Commodities magazine by J. Welles Wilder in July 1978, envisioned the RSI being used as a reversal indicator, i.e. you would sell when the RSI was high and buy when it was low. Given the strong results from using it as a momentum indicator prior to publication, I am at a loss to explain this!

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  • $\begingroup$ I'd also add that if an indicator truly works, then its performance is likely to decrease as more people start using it. So if you have one that works, use it to your advantage before publishing it as a research study! $\endgroup$ – rbm Jul 18 '17 at 14:36
  • $\begingroup$ This brings up a very interesting idea for testing the concept of technical trading indicators. Thanks for that, I think it is well worth a study. What metrics would you consider appropriate in this kind of study and do you have any good source for when different indicators were introduced to the market? $\endgroup$ – drobertson Jul 18 '17 at 19:37
  • $\begingroup$ Also would you mind share what tool you used to perform the analysis? I want to do some of these but am lost $\endgroup$ – Daniel Jul 19 '17 at 4:08
  • $\begingroup$ @Daniel I did the analysis in MATLAB. $\endgroup$ – Chris Taylor Jul 19 '17 at 7:56
  • $\begingroup$ @drobertson There's not much argument for using anything other than the standard metrics (excess return, volatility, sharpe ratio, size of drawdowns). Note that this topic has been done to death in academic papers and in industry since at least the 1970s - just google "technical trading out of sample" or "technical trading overfitting" or "finance backtest overfitting" for many examples. $\endgroup$ – Chris Taylor Jul 19 '17 at 8:11

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