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A similar pattern is repeated near the end of the decade. These mutual fund flows were near the start of a significant bear (downtrending) market and bull (uptrending) market respectively. For example, in the beginning of the 2000s, the largest inflows to stock mutual funds were in early 2000 while the largest outflows were in mid-2002. They show that flows generally track the overall level of the market: investors buy stocks when prices are high, and sell stocks when prices are low. Mutual fund flows are published by organizations like Investment Company Institute, Lipper, Morningstar, and TrimTabs. Critics, however, argue that once the strategy has been revised to reflect such data it is no longer 'out-of-sample'. Market timers attempt to avoid these problems by looking for clusters of parameter values that work well or by using out-of-sample data, which ostensibly allows the market timer to see how the system works on unforeseen data. Unfortunately, if the trading rules are over-optimized they often fail to work on future data. ДЄ major stumbling block for many market timers is a phenomenon called ' curve fitting', which states that a given set of trading rules tends to be over-optimized to fit the particular dataset for which it has been back-tested. Moving average strategies are simple to understand, and often claim to give good returns, but the results may be confused by hindsight and data mining. Others say, 'nobody knows' and that world economies and stock markets are of such complexity that market-timing strategies are unlikely to be more profitable than buy-and-hold strategies. The market timers then predict that the trend will, more likely than not, continue in the future. Technical analysts consider it significant when one moving average crosses over another. Some people believe that if the market has gone above the 50- or 200-day average that should be considered bullish, or below conversely bearish. Market timing often looks at moving averages such as 50- and 200-day moving averages (which are particularly popular). Some algorithms attempt to predict the future superiority of stocks versus bonds (or vice versa), have been published in peer-reviewed journals.

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Institutional investors often use proprietary market-timing software developed internally that can be a trade secret.

The tendency to buy mutual funds with high returns and sell those with low returns can reduce profit. Stock market returns tend to go back to the long-term average. Stock market returns are almost unpredictable in the short term.

Buying mutual funds with high returns is called a вЂњreturn-chasing behavior.вЂќ Equity mutual fund flows have a positive correlation with past performance, with a return-flow correlation coefficient of 0.49. The average equity mutual fund investor tends to buy mutual funds with high past returns and sell otherwise. Louis, YiLi Chien, Senior Economist wrote about return-chasing behavior. 'Trend Tracker' reported returns are distorted by survivor bias, selection bias, and fill bias. ДЄfter fees, the average 'trend follower' does not show skills or abilities compared to benchmarks. Market timing can cause poor performance.

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