Some analysts fail to account for data snooping bias in their analyses of market timing indicators. This bias amounts to incorporating pure luck into results by testing many different rule variations or parameter settings within rules (or inhaling the “secondary smoke” of other analysts who have already screened a set of rules/parameters). This luck does not persist out-of-sample. Do any market timing rules generate outperformance after correcting for this bias? In their February 2009 paper entitled “Data Snooping and Market-Timing Rule Performance”, Andreas Neuhierl and Bernd Schlusche assess the profitability of a comprehensive set of simple and complex market timing rules based on fundamental indicators and investor sentiment indicators after correcting for data snooping bias. Simple rules derive from a single indicator, and complex rules derive from multiple indicators. Using thousands of simple and complex rules based on data for the S&P 500 to time the daily close of the S&P 500 index over the period 1980-2007, they conclude that:
Over the entire sample period and a 1981-1994 subperiod, they test 6,792 simple market timing rules and 1,976 complex rules. Over a 1995-2007 subperiod, they test 8,280 simple rules (more types of data available) and 1,976 complex ones. Rules include those based on: financial ratios (earnings-to-price ratio, dividend yield and book-to-market ratio), short-term and long-term interest rates and spreads, expected inflation, measures of investor sentiment (credit spread and put-call ratio), implied volatility index, bond-equity yield ratio and dividend payout ratio.
- In isolation, over the entire 1980-2007 sample period, the best-performing simple (complex) rule outperforms a buy-and-hold strategy by an annualized 2.93% (3.18%).
- Over the the full sample period, no simple or complex market timing rule significantly outperforms a buy-and-hold strategy after correcting for data snooping bias.
- Over 1981-1994 and 1995-2007 subperiods, no simple market timing rule significantly outperforms a buy-and-hold strategy after correcting for data snooping bias.
- Over the 1981-1994 subperiod, certain complex market timing rules do outperform a buy-and-hold strategy even after correcting for data snooping bias and accounting for reasonable transaction costs. However, over the 1995-2007 subperiod, no complex rule significantly outperforms a buy-and-hold strategy after correcting for data snooping bias.
In summary, even though S&P 500 index timing rules based on fundamental indicators and investor sentiment indicators might significantly beat a buy-and-hold benchmark when evaluated in isolation, this outperformance generally evaporates after correcting for data snooping bias. In other words, luck is the dominant differentiator of rule performance.
