Testing a Longer Time Frame

TESTING A LONGER TIME FRAME

At this point you may be thinking that we should test this version of the morning star pattern in a very long time frame. Testing this during the 7 A-year period from the end of 1999 to May of 2007 showed an annualized ROI of negative 25%, and the winning percentage dropped to 42%. What happened? Does the system just fail in longer time frames?

The answer, like many things in trading, comes by looking at the market. Figure 6.11 shows the NASDAQ during the December 1999 to May 2007 test period. During 2000, 2001, and 2002, the market dropped around 80%. As I recall during the first part of that period, the talking heads on the financial shows were encouraging people to “stay the course,” “believe in America,” and worst of all, “buy the dips.” This illustrates how important it is to learn how to read the charts yourself because anyone who knew how to draw trend lines was either out or short in 2000.

FIGURE 6.11: NASDAQ MARKET BETWEEN DEC. 1999 AND MAY 2007

The period between 03/31/00 and 10/04/02 was one of the worst bear markets in history, with the NASDAQ declining from the 5,000 area to the 1,100 area. Testing the morning star pattern during this period (with the requirement that the second day’s high be below the first day’s low) showed 130 trades and an annualized loss of 111%. Only 32% of the trades were profitable. This pattern, and many other long systems, was not able to overcome the strong bearish tendencies of the market during this unique period.

From 10/24/02 to 05/01/07, the market showed a number of normal up and down cycles, but nothing as dramatic as the 2000 to 2002 period. Between 10/24/02 and 05/01/07, this modified morning star pattern showed 142 trades, a little less than three a month, and an annualized ROI of 46%. Winning trades returned an average of 5.3% and losing trades lost an average of 3.6%.

The key point here is to show that market conditions have a strong effect on most trading patterns, and it is important for traders to understand how their patterns perform in different market conditions. It is also important to understand that testing in a longer time frame does not necessarily produce more reliable results. Some traders feel that if a two-year test is good, a five-year test must be more accurate, and an eight-year test would be even better for accurately representing how a pattern performs. Sometimes this is not the case because unusual market conditions can overpower the results.

As we have seen here, increasing the test period length from two to five years might lead one to believe the trading pattern is solid. Another trader who only tested the pattern in the eight year period from 2000 to 2007 would see negative results and conclude the pattern is not worth trading. The difference is that the eight-year period includes one of the worst bear markets in history. What are the odds of the market showing another eight-year period like that in the near future? Not likely. This is why just arbitrarily increasing the test period does not ensure more accurate results when testing trading patterns. Traders can get a better idea of how a system performs by testing in multiple instances of all three basic market conditions.

The Issue of Statistical Relevance

An interesting issue raised by these test results is how to deal with trading patterns that end in a low number of trades during the test period. The heart of this issue is whether the test results are statistically significant. In this case, we saw similar results in two different testing periods, which indicated the filter may not be curve fitting the data in one time frame. However, we should be on our guard when we see a small number of trades during a long test period. It raises some questions as to how likely the results are to be replicated in the future.

A more practical question is that trading less than three patterns a month may not provide enough opportunity for profit. Making a trade every couple of weeks and annualizing the results can give a good annualized ROI, but total dollars flowing into the trader’s account may not be as strong as a pattern with a lower annualized ROI and more consistent trades. Typically, I want to see trading patterns that provide multiple opportunities every week. Because of this issue, I will go back to the requirement of the second day’s close being below the first day’s low. The results of using this requirement are shown in Figure 6.9.

DOES BODY COLOR MATTER?

In the process of making the morning star pattern more specific, we have analyzed the effects of changing the parameters of body size and of a gap down on the second day. The last aspect of the second day of the pattern is the assertion that the body color does not matter. Let’s test that assertion.

The data in Figure 6.12 indicates that during the 01/03/06 to 05/01/07 test period, trading morning star patterns with black bodies on the second day improved both the annualized ROI and the percentage of winning trades as compared to the results of Figure 6.9, which allowed second day black bodies of either color. An example morning star pattern with a black body on the second day of the pattern is shown in Figure 6.13.

FIGURE 6.12: TEST RESULTS FOR MORNING STARS WITH SECOND DAY BLACK BODIES

FIGURE 6.13: MORNING STAR WITH SECOND DAY BLACK BODY

Testing the requirement of the second day black body in the longer time frame of 01/02/04 to 05/01/07 resulted in a 29% annualized ROI (10% for buy and hold) and a winning percentage of nearly 55% percent. This is an improvement over the 20% annualized ROI and 54% winning trades that resulted during the same period when taking trades of either body color on the second day of the pattern.

During these two test periods, the results favor taking morning star trades with black bodies on the second day of the pattern. I also tested the effect of only taking trades during the 01/02/04 to 05/01/07 test period with white bodies on the second day. The test results shown in Figure 6.14 indicate that taking morning star trades with white second day bodies during the 01/02/04 to 05/01/07 period results in a small annualized ROI loss. Testing the second day black bodies in multiple time frames showed an improvement in results, and testing second day white bodies showed a decrease in results. Based on these results, I will incorporate the requirement for a second day black body into the morning star definition.

FIGURE 6.14: TEST RESULTS FOR MORNING STARS WITH SECOND DAY WHITE BODIES

THIRD DAY PARAMETERS

The requirements for the third day of the morning star pattern are relatively simple. It must be a white body and it must close within the top half of the range of the first day of the pattern. I tested different requirements for how far into the first day’s range the last day must close and did not find anything that significantly helped the results.

Gaps may indicate strength, so I tested a requirement that the last day of the pattern gap up. During the 01/03/06 to 05/10/ 07 test period, this new requirement resulted in a slight decrease in the annualized ROI and the percentage of winning trades. Therefore, a gap up on the third day of the pattern does not appear to be something worth incorporating into the morning star definition.

I also found that during this test period, requiring the third day of the pattern to have the largest range of the last five days did not help results. This requirement was found to be useful in other patterns, but does not help the morning star pattern.