Price momentum strategies have historically generated high positive returns with little systematic risk. However, these strategies also experience infrequent but severe losses. During 13 of the 978 months in our 1929–2010 sample, losses to a US-equity momentum strategy exceed 20 percent per month. We demonstrate that a hidden Markov model in which the market moves between latent "turbulent" and "calm" states in a systematic stochastic manner captures these high-loss episodes. The turbulent state is infrequent in our sample: the probability that the hidden state is turbulent is greater than one half in only 20% of the months. Yet in each of the 13 severe loss months, the ex-ante probability that the hidden state is turbulent exceeds 70 percent. This strong forecastability accentuates the price momentum puzzle; a conditional momentum strategy that moves to the risk-free asset when the ex-ante probability of the turbulent state is high exhibits dramatically better performance than the unconditional momentum strategy.
Daniel, Kent, Ravi Jagannathan, and Soohun Kim. "Tail Risk in Momentum Strategy Returns." Columbia Business School, 2012.
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