How to Identify and Predict Bull and Bear Markets

Abstract

Characterizing financial markets as bullish or bearish comprehensively describes the behavior of a market. However, because these terms lack a unique definition, several fundamentally different methods exist to identify and predict bull and bear markets. We compare methods based on rules with methods based on econometric models, in particular Markov regime-switching models. The rules-based methods purely reflect the direction of the market, while the regime-switching models take both signs and volatility of returns into account, and can also accommodate booms and crashes. The out-of-sample predictions of the regime-switching models score highest on statistical accuracy. To the contrary, the investment performance of the algorithm of Lunde and Timmermann [Lunde A. and A. Timmermann, 2004, Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets, Journal of Business & Economic Statistics, 22(3):253–273] is best. With a yearly excess return of 10.5% and Sharpe ratio of 0.60, it outperforms the other methods and a buy-and-hold strategy.