In our last article
on short-term stock index timing, my firm used just one day's worth of data to document that short-term market strength tends to be followed by below average returns, and short-term market weakness tends to be followed by above average returns. In other words, by acting in a way that is contrary to the average investor's impulse to chase market strength and sell market weakness, the disciplined trader can develop a trading edge. The analysis in this article will help you to do this.
Before we get into the data, I wanted to clarify a few points about the analytical approach I am using. Strategy trading is about developing approaches that have a positive expected value over a large class of events or circumstances -- they are not meant as predictions for a specific day or a specific trade.
The goal of this type of analysis is to create the type of advantage enjoyed by a casino: The casino boss does not know how any particular bet will turn out; however, because the machines are programmed to pay out less than they take in, he knows that over time he will win. In the same way, when traders uses this approach to identify opportunities, they don't particularly care about the results of one day or one trade. It might feel better to win than to lose, but this feeling is unrelated to the economic value being created over time.
With this understanding, let’s extend the "recent weakness leads to higher average returns" concept and look at how today's (the formula works with any day) percentage change in the SPDR S&P 500 ETF
(NYSEARCA:SPY) [measured from yesterday's close to today's close] impacts the average return over the next 24 hours [measured as today's close to tomorrow's close]. What has been the average return over the next 24 hours if the market is closing higher vs. if it is closing lower? [Editor's note: The author is referring specifically to the ETF, not the S&P Index (INDEXSP:.INX).]
The significance of this is that on average when the market is closing up more than 1%, the next day is a loss. When the market is closing down by greater than 1%, the next day is an above average gain. I try to explain the significance of this with the casino analogy, and the chart showing how a specific example of this idea performed against buy and hold.
[Editor's note: Basically you are using the 24 hour return of the period just ending to forecast the expected return over the next 24 hours. The author's studies show that this information has useful forecasting value.]
SPY - return next 24 hours if today's close up vs. if down
The average return after an up day was -.02%, and the average return after a down day was .10%. Note also that the average close-to-close return for all days during the test period was .04%. This fits the pattern that we have previously documented. On average, short-term strength is followed by weakness, and short-term weakness is followed by strength. Let’s break up the data a bit further so we can look at how the magnitude of the change up vs. down has impacted the average forward return. In the following graphic, we look at percent change from yesterday's close in segments (0 - 1%, 1 - 2%, 3%+, etc) and then look at average return over the next 24 hours:
SPY close-to-close return, if close today is down or up by:
The overall pattern is quite distinct: Larger percent gains for the current day on average lead to larger expected losses over the next 24 hours, and larger percent losses lead to larger average gains. Notice that these results mirror what we found in our prior article
, when we applied this concept to just one day's worth of data.
Let’s take the above concept and view it as a trading strategy. How has buying (or staying long) when the market is down greater than 1% and holding for 24 hours compared to buy and hold?
If today's close down is greater than 1% from yesterday's close, go long on today's close and exit at tomorow's close.
This graphic demonstrates how powerful these concepts can be. Note that in the above study, the "system" was only in the market about 15% of all trading days. If you found this study interesting, I have posted some supplemental material here
. Specifically, we review one additional short-term pattern, and observe what happens when we combine it with the factor mentioned in this article.
How can this information be used?
For short-term traders, the concepts outlined here and in our last short-term timing article can be refined into effective trading strategies. Some of the most successful futures trading hedge funds use trading systems that are based upon these same concepts.
Many intermediate-term traders have been taught that buying on strength is the best approach to timing trades. While this can work, evidence suggests that over the long run, buying after short-term market dips is most likely to put the odds in your favor.
Finally, this information can help investors. Few investors realize that over long periods of time, small adverse decisions compound and can dramatically reduce returns. The "money weighted return" problem is a great example of this, and it is the second point I address in this article.
The good news is that small, seemingly beneficial decisions can have the opposite effect. An investor who tactically times longer-term ideas might be getting the best of both worlds.
Nat Stewart runs the trading-strategy website www.nastrading.com. The site’s mission: “Help traders capture explosive moves in the forex, futures, and stock markets.”
No positions in stocks mentioned.