How Much Information Is Required to Time the Market?

In this article, the authors present an analytical explanation for why it can be difficult to devise a successful market timing strategy. The authors derive formulas to estimate the minimum required information coefficient for a timing strategy to outperform a buy-and-hold market benchmark, both with and without an alpha target. They show that markets with high Sharpe ratios and those that have low volatility are by nature hard to time. They also show that having high market exposure in a market timing strategy is generally beneficial; however, there can be a critical point beyond which additional market exposure makes timing more difficult. The authors extend the model to cover practical considerations such as transaction costs, skewness and fat tails, and market timing with two correlated assets. Finally, they present a case study to illustrate how investors could apply their framework to choose the optimal market exposure in a market timing strategy using the S&P 500. Key Findings ▪ Under a bivariate normal framework, the authors show that the expected return of a timing strategy comes in two additive parts: one part driven by timing information and the other driven by average market exposure. ▪ There is generally a theoretical nonzero information threshold for a timing strategy to beat a buy-and-hold benchmark. This threshold can serve as a useful guide to determine whether a timing strategy is likely to succeed, complementing historical backtests. ▪ Although an investor can increase timing strategy return by increasing average market exposure without having more timing information, the difficulty of beating a buy-and-hold benchmark with an alpha target increases dramatically as average market exposure becomes very high.