OverBought/OverSold

One of my interests is looking into ways to improve investing returns. I decided to look just at the S&P500 on a monthly basis since 1967. Mebane Faber has noted that the returns to a 10 month simple moving average strategy earns significant returns. In this sample, the returns are statistically significant with a 12.2% return (13.5% standard deviation) compared to a statistically insignificant 5.8% (18.3%) when below. I wanted to test three common OverBought/OverSold indicators on a monthly basis and then check to see if they would be any benefit when combined with the 200 day strategy.

The three indicators I used were Relative Strength Index, Slow Stochastic, and Bollinger Bands. I would imagine that most people who would come to this site has heard of these concepts (which you can google if my explanations aren't good enough), but I'll explain their basic concepts anyway. The Relative Strength Index scales the ratio of the size of recent up moves to down moves. If there are more up moves, then the ratio will tick up which is then scaled from 0 to 100. The %K fast stochastic indicator measures where the most recent close is relative to the range the stock has been trading in. If it is trading near recent highs, then it will be closer to 100 and closer to 0 when trading near lows. Slow Stochastic is a 3 month MA of the fast. Bollinger Bands measure 2 (or n) standard deviations away from the moving average. For all of these, I use ten months as the initial range. I'm only able to do the slow stochastic since 1988 since I couldn't get highs or lows before then.

The biggest problem with these is that compared to the 10 month strategy, these have relatively few occurrences. So instead of being concerned with Sharpe ratios, I'm mostly concerned with statistical significance.

The results are that few of the indicators result in statistically significant returns. Overbought/oversold points on the 2 stdev Bollinger Bands are not significant with almost zero return when greater than the 2 and too few observations when less than the -2 (though that return is about 20% annualized). With breakpoints at 20 and 80, the oversold RSI is not statistically significant, but the Overbought is statistically significant in the positive direction. In other words, when the RSI is greater than 80, the market generally keeps going up. However, at the 90 breakpoint, it is no longer statistically significant. Combining those two signals (greater than 80, less than 90 (or 95) is statistically significant and occurs in about 72 months (14.5% of total). This indicates to me that the RSI does work as a momentum indicator and as an OverBought/OverSold indicator. Finally, the Slow Stochastic with 20 or 80 is significant (though both are positive). There are only five cases where the Slow Stochastic was under 20 (including March) and the average return in the next month has been 5.4% (this April did not disappoint). Increasing the low breakpoint up to 25 still gives significance and increasing the high breakpoint all the way up to 95 still shows significance with positive returns (I expected negative). This would indicate to me that Stochastics are not particularly good as OverBought/OverSold indicators on a monthly basis. However, it is really the most extreme readings that really generate statistically insignificant results. So it might make sense to look at a stochastic of 98, but a stochastic of 85 or 90 is probably more indicative of momentum than anything else.

So how would an investor incorporate these into a strategy? In general, you would want to stay away from situations where you do not generate statistically significant returns and invest when they are. Including the strategy when the slow stochastic is greater 80 or 90 combined with the 200 day MA does not change returns. The 200 day covers the momentum effect already. Avoiding the situations where it is above 98 does not result in a statistically significant difference between the two results. The below 20 or 25 is not statistically significant either. However, both of those two increase the Sharpe ratio of the strategy (note I use since 1988 for this part, but since '67 for the rest).

For the Bollinger Bands, you may as well ignore the OverSold indication since it always comes when you are out anyway due to the 200 day. The OverBought indication increases the Sharp ratio, but its inclusion is not statistically significant compared to the 10month SMA strategy.

What is true for the OverSold in Bollinger Bands, is also true for the RSI. The 200 day already gets you out of the market. Even the best combinations of the OverBought indicator (noted before at 80 and 90) do not improve significantly on the 200 day MA. However, if you reduce the break down to 75 and do not invest when the momentum is greater than that, then you will significantly increase returns at the 10% level. I just kind of pulled that number out of the air so I was surprised it works and am more afraid that it was a bit of curve fitting. The only problem is that if you are an investor looking for total returns, you will reduce the months of investing by almost 50%. Even still, though, if you include the risk-free return, then the historic returns for this strategy are at 11.5% (10.7% SMA) with a standard deviation of 8.1%(11.6% SMA). That ratio of return to risk is consistent over multiple time periods. The ratio is also fairly consistent going down through 70 (and below, though the returns suffer since you are in that many fewer days). The good thing about the RSI is that it is easily incorporated into other strategies since it only uses closing prices.

One additional improvement (that could be some curve fitting action) would be to make three requirements for a position, the first is SMA or below 25 on the stochastic, the second is RSI less than 75, and the third that the stochastic is not greater than 95. This return is significantly greater than the original SMA almost at the 2.5% level. After incorporating the risk-free return, the Sharpe ratio is .71 vs. .63 for only the RSI requirement, and finally .43 for the SMA. I plan on backtesting the TAA strategy with the RSI requirement, but I cannot backtest the complete method since I don't have high/low information for total return indices on bonds and REITs. ETFs have the information, but the time frame is smaller which makes comparisons difficult (though implementation is still possible).

In conclusion, OverBought and OverSold indicators can have some value in pointing out time periods to avoid (or get in), but they seem to have the most value when used in conjunction with each other. There are many dangers with curve fitting when using this kind of analysis, so the general rule is to keep it simple stupid and test a strategy that works on one set of data on other sets and look for some kind of consistency in the returns.