The Main Cause of Failure of Some Popular Technical Trading Methods

Trend-following based on indicators and classical chart patterns are two trading methods that were developed in mid 20th century using data from the equity markets mainly. These methods worked well for an extended period of time in those markets due to the presence of autocorrelation. After 1998 these methods struggle because serial correlation in all markets has virtually disappeared.


On the above daily chart of S&P 500 from 01/03/1950 to 12/19/2012 the bottom pane is the 1-Lag rolling 120-day autocorrelation of daily arithmetic returns, defined as [C(i+1)/C(i) – 1]. It suffices to observe that from 01/1950 to 04/1988 the autocorrelation was very high, especially after 07/1964 and through 04/1988, a period of 24 years, with few short periods of negative readings. That was a good time for technical methods based on trend-following and chart patterns and, as a result, traders might have gotten the impression that these methods worked. However, any success was mainly due to the high autocorrelation in the equity markets, i.e., the fact that future prices more than often behaved like past prices. In other markets, such as for example in  commodity futures and currencies that started trading in the mid 1970s, these technical methods were expected to work because they were raised to indisputable trading rules by some authors. In reality, these trading rules were the cause a high rate of trader failures.

The struggle of managed futures performance to generate alpha in the last four years, as reported in recent posts, is also for the most part due to the same effect, i.e., due to the fact that the majority of these funds do trend-following based on methods that were developed in the 1970s and 1980s that worked well due to the serial correlation, as shown on the S&P 500 chart.


In the EURUSD daily spot exchange rate chart from 01/1998, as shown above, it is clear that before 2005 and for the most part the 1-Lag rolling 120-day autocorrelation was negative with only a few short periods of positive values. It is important to realize is that trend-following and chart patterns, especially those based on weekly or even monthly data, could work well only during a few specific periods. Experienced currency traders knew all along that technical trading methods developed on equity data did not perform well in currency trading because of the unpredictability of those markets. The same is the case for commodities markets. Below is a chart of crude oil futures, continuously adjusted:


In this case too we observe that for an extended period of time, from 2003 to 2008, the autocorrelation was negative and for the most part insignificant. There was a period in the early 2000s of positive autocorrelation and then during 2012. These rare periods of positive autocorrelation gave the false impression and hope to some technical traders that trend-following and chart patterns developed long ago by analyzing equity data can work in other markets too but actually the specific methods were irrelevant and their success was due to autocorrelation.


The same phenomenon can be noticed on the continuous sugar futures chart above. The lack of persistent positive autocorrelation is evident. No wonder why technical signals generated by chart patterns and trend-following systems have failed in this market too in the last two years given that after 2010 the autocorrelation was negative.


Most technical methods for longer-term and position trading were developed in mid mid 20th century and were used extensively in the 1980s with the advent of the personal computer that allowed their practical implementation and automation. However, these method were developed primarily using data from the equity market simply because most commodities and currencies were not traded back then in organized exchanges.  Their developers falsely attributed the apparent autocorrelation in the equity markets that basically turned profitable any method based on buying (selling) on strength (weakness) to some predictive capacity of these methods. Essentially, they were fooled by randomness and attributed causal powers to some dubious formations.

Later, other technical traders and book authors raised the methods developed for the equity markets to general trading rules for all markets using totally unjustifiable induction. Examples are rules like”if pattern XYZ forms and it is confirmed, then the market will move higher towards a target equal to T” or “if a moving average of X days crosses above a moving average of Y days, then the market will rise further”. However, the conditions that made these rules profitable in the past were not present in the other markets and thus a high percentage of commodity and currency traders that used them in the 1980s and 1990s lost a lot of money to locals.

The profitability of the trading methods in the equity markets fell steadily after 1988 and by 2007 it was gone as the autocorrelation of the daily returns was arbitraged out by fast traders. It is unlikely that autocorrelation will increase again to levels required for the profitability of technical methods that rely on its existence, like trend-following and chart pattern trading. High Frequency Trading (HFT) is the main mechanism that is currently in effect to arbitrage out autocorrelation and its profits come mainly from technical traders and funds that trade using methods developed in the 1950s when there were pits, traders calculated moving averages manually and charts were available on a weekly basis. Nowadays, these methods do not have any inherent predictive capacity and have been abandoned by the majority of technical  traders in favor of methods such as scalping, price action trading, medium frequency trading and pairs trading, and others know or unknown to the public, most of which are based on mean-reversion principles rather than on trend-following or on directional move confirmation, as with chart patterns.

Charting program: Amibroker

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