Читать книгу Encyclopedia of Chart Patterns - Thomas N. Bulkowski - Страница 55

Table 3.2 shows the first batch of statistics for the bullish AB=CD.

Number found. I found over 2,300 patterns, sorted by market condition, in 1,069 stocks from July 1991 to February 2020. I told my program to limit the number found so it didn't overload my spreadsheet. Not all stocks covered the entire period, and some no longer trade.

Breakeven failure rate. The failure rate (a measure of how many patterns failed to see price climb more than 5%) is quite good, averaging between 3% and 12% of those patterns that reached D and reversed there. To put it another way, if you were to trade a lot of these patterns perfectly, you'd have an 88% chance of seeing price rise more than 5% above the low at D. That's terrific.

Average rise after D. I measured the average rise from the low at D for those patterns reaching D and turning upward. The average rise is disappointing. Non‐Fibonacci‐based patterns in bull markets perform better, averaging 42.4%. However, bear markets beat non‐Fib patterns with the rise averaging 30.5% compared to 28.1%, respectively.

Table 3.2 General Statistics

Description	Bull Market	Bear Market
Number found	1,741	565
Breakeven failure rate	11.6%	3.7%
Average rise after D	38.4%	30.5%
Volume trend	53% Upward	57% Upward
Performance Up/Down volume	40%U, 37%D	33%U, 27%D

Volume trend, performance. Volume trends upward slightly more often than downward, as the table shows. You can improve performance by looking at the volume trend. I used linear regression to determine if volume was trending upward or downward from the start to end of the pattern (A to D). Often you can just look at volume to see the trend.

Both markets see an improvement in performance if volume trends higher. To put it another way, a downward volume trend hurts performance.