Does candlestick technical analysis (examining relationships among opening, high, low and closing prices over the past 1-3 days to identify continuation and reversal signals) generate abnormal returns? In their recent paper entitled “Market Timing with Candlestick Technical Analysis”, Ben Marshall, Martin Young and Lawrence Rose test the profitability of trading stocks included in the Dow Jones Industrial Average based on 28 different candlestick signals. They assume a ten-day holding period after trading at the close on the day after a signal appears. Using stock price data for 1/1/92-12/31/02, they conclude that:
- Trading returns after bullish single-day signals are positive less than half the time. No bullish signals predict abnormal positive returns with high reliability (assuming a normal distribution of returns). In fact, one single-day bullish signal reliably predicts a negative return.
- The returns after bearish single-day signals are negative more than half the time. However, the mean returns for most bearish multi-day signals are positive, and two of these patterns indicate abnormal positive returns with high reliability (assuming a normal distribution of returns).
- Bootstrap tests (which more correctly do not assume a normal distribution of returns) show no evidence that any candlestick signals predict stock price movements.
- Results are robust to use of next-day opening rather than closing prices to initiate trades, and to sample subperiods.
The following figure, taken from the paper, summarizes the basics of candlestick depiction. When stock price closes above (below) its opening level, the candle is white (black).
In summary, neither bullish nor bearish candlestick signals reliably generate abnormal returns in the expected direction for large-capitalization U.S. stocks during recent years.
Reader and author Greg Morris, a Senior Portfolio Manager, comments, as follows:
These types of studies are always short on components and generally miss some basic concepts. Candle patterns MUST first consider the trend (short term) of the market before they can be identified. Identifying a pattern or price movement and calling it a candle pattern without considering the trend is bogus at best.
[A] classic chart pattern (candles also) must include the investor/trader psychology/sentiment that evolves as the pattern evolves – that is what causes the pattern. Having a computer pick out price relationships solely, then saying if they are predictive or not is, well, that is what academia does so well.
Frequently Asked Questions
What is candlestick technical analysis in stock trading?
Candlestick technical analysis is a method of examining relationships among a stock's opening, high, low and closing prices over the past 1-3 days to identify continuation and reversal signals. A candle is white when the price closes above its opening level and black when it closes below. Traders use patterns of these candles as bullish or bearish signals.
Do candlestick patterns reliably predict stock returns?
Candlestick patterns did not reliably predict stock returns in a study of Dow Jones Industrial Average stocks from 1992 to 2002. Bootstrap tests found no evidence that any of 28 candlestick signals predict price movements, and neither bullish nor bearish signals generated abnormal returns in the expected direction. Results held when using next-day opening prices and across sample subperiods.
How are candlestick trading signals tested for profitability?
Candlestick signals were tested by trading Dow Jones Industrial Average stocks on 28 different signals, entering at the close on the day after a signal appears and holding for ten days, using data from 1/1/92 to 12/31/02. Returns were evaluated both assuming a normal distribution and with bootstrap tests, which do not assume normality. The bootstrap approach is considered more appropriate and showed no predictive power.
Why do normal-distribution tests and bootstrap tests give different results for candlestick signals?
Normal-distribution tests and bootstrap tests gave different results for candlestick signals because only the bootstrap does not assume normally distributed returns. Under the normality assumption, one bullish single-day signal reliably predicted a negative return and two bearish multi-day patterns indicated abnormal positive returns. Bootstrap tests, which more correctly handle the return distribution, found no evidence that any signal predicts stock price movements.
What are the criticisms of testing candlestick patterns with computer-based statistical studies?
Critics argue that statistical studies of candlestick patterns omit key components, especially the short-term market trend that must be considered before a pattern can be identified. Portfolio manager Greg Morris also contends that valid patterns must reflect the evolving investor psychology and sentiment that creates them, rather than having a computer pick out price relationships alone. Additionally, the study covered only large-capitalization U.S. stocks (Dow Jones Industrial Average components) for 1992-2002, so findings may not extend to other markets.