Stock Selection - Breakout Analysis

Previously I studied the initiation of a breakout by defining it as either a certain percent move over the previous day's close or a certain move in terms of the 20 day average true range (ATR).  The method used lumped the results together in a manner that could be masking the true behavior of the market.  Specifically, I reported the results for all occurrences that exceeded the threshold breakout value.  This was an adequate method to give a preliminary analysis of possible market behaviors, but a problem arises because the results for the higher breakout values were included in the results for the lower breakout values.  For example, the results for all breakouts exceeding 4% would include the results for breakouts exceeding 10% because 10% breakout magnitudes also exceed 4% breakout magnitudes.

To further dissect the results and provide some insight to the best reporting method, I will be using the same breakout criteria and reporting the results for independent levels of breakouts.  For example, instead of looking at the performance of all breakouts exceeding 4%, I will instead look at breakouts with magnitudes between 3-4%, 4-5%, 5-6%, etc.  In addition, I will also consider the occurrence of breakouts in the past two days which may affect the trade length and number of trades as reported in the previous post.

The entry will be at the open on the day following the breakout trigger.  The exit will occur on the following day's close for an expected trade length of 1 bar.  Once again I will be using the iShares Dow Jones US Total Market Index (IYY) component stocks as a proxy for the entire market.

Here are the results for breakouts that trigger regardless of the prior two day activity:

Here are the results for breakouts that trigger when there are no breakouts in the prior two days:

There are a substantial number of 0%-return trades indicated by the difference between the Monte Carlo Win% and the Percent Profitable for both types of triggers.  Both charts indicate the once the breakout threshold exceeds 10%, the trades become unprofitable on average.  The most profitable trades seem to occur in breakouts on the order of 6-9%, and the 7-8% level is the most profitable with an average trade of 0.18%.  The 7-8% level had an average winning trade of 5.10% and an average losing trade of -4.49%.

The average winning trade increases with increases in the breakout magnitude.  The average losing trade decreases with increasing breakout magnitude.  There are variations when you account for the breakout activity in the prior two days.  The average winning and average losing trades decrease, while the average for all trades increases.  The following chart shows the differences in the average return per trade for each breakout group.

The chart shows that breakouts in the past two days do have a significant effect on the average return per trade.  If we did not isolate out a breakout, the max average return is 0.13% occurring at the 6-7% level.  Once we isolate the breakout form breakouts in the prior two days, the max average return is 0.18% occurring at the 7-8% level.  If you remove breakouts from the past two days, the average trade increases from a maximum of 0.13% to 0.18%, an increase around 40%.  Future analyses will look at the stock activity leading up to a breakout and its effect on the return after a breakout.

I prefer reporting results in independent levels to separate out the influence of higher magnitudes on the data for the lower magnitudes.  In actuality, I would never run a stock scan only looking for breakouts between 6-8% because it is too specific.  Actual stock screens would involve one threshold like >5% with the knowledge that as the percentage increases, the odds for mean reversion increase.  The purpose of these back test exercises is too reveal general market behaviors while trying to determine a robust trading edge.

ANALYSIS SUMMARY:

• Defining results in terms of independent levels provides more information about the data set.
• Trades mean revert on average when the breakout exceeds 10%, as indicated by the negative average trade.
• The most profitable trades occurred with a breakout threshold between 6-9%.
• The maximum average trade was 0.18% for the 7-8% breakout level.  For this level, the average winning trade was 5.10% and the average losing trade was -4.49%.  Future analyses will look at changing the exit to remove some of the downside risk and improve the average trade.
• Removing breakouts from the two days prior to the breakout day increased the returns by 40%.  Future analyses should investigate the effect of the prior days performance on the returns.