Momentum Crashes

By Kent D. Daniel, Tobias J. Moskowitz, Pierre Collin-Dufresne, Gur Huberman, Michael Johannes, Tano Santos, Paul C. Tetlock, Sheridan Titman. 2010

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Citations in the corpus

Enhancing Time-Series Momentum Strategies Using Deep Neural Networks (2019, background): “This is particularly relevant as raw momentum strategies without adequate risk adjustments, such as volatility scaling [7], are susceptible to large crashes during periods of market panic [28, 29].”
Tree-Based Conditional Portfolio Sorts: The Relation between Past and Future Stock Returns (2016, unknown): “demonstrated between size and value (Fama and French (1992)), between size and seasonal effects (Daniel and Titman (1997)), and between stock exchange and volume (Brennan et al.”
Enhancing the momentum strategy through deep regression (2019, methodology): “Speciﬁcally, it was reported in Daniel and Moskowitz (2013) that during July and August of 1932, the return of the winner decile portfolio was 32% while that of the loser portfolio was 232%, and during March and May of 2009, the return of the winner decile portfolio was 8% while that of the loser…”
Two centuries of trend following (2014, background): “As mentioned in the introduction, trending behaviour is also observed in the idiosyncratic component of individual stocks [24, 25, 26, 10].”
Volatility‐Managed Portfolios (2017, background): “…gold based on estimating the conditional covariance matrix that performs cross-sectional asset allocation, and Barroso and Santa-Clara (2015) and Daniel and Moskowitz (2016) study volatility timing related to momentum crashes.5 Instead, our approach focuses on the time series of many aggregate…”
Beyond the Carry Trade: Optimal Currency Portfolios (2015, background): “The gain with respect to the Carhart factors comes mainly from the dismal performance of stock momentum in 2009, when it experienced one of its worst crashes in history (Daniel and Moskowitz (2012), Barroso and Santa-Clara (2012)).”
The Impact of Volatility Targeting (2018, unknown): “Barroso and Santa-Clara (2015) and Daniel and Moskowitz (2016) studied risk-managed momentum strategies. unscaled unscaledr r kt t= × Notice that futures and forwards trade on margin, so their returns are already essentially unfunded; thus, the risk-free rate is not deducted.”
The Growth and Limits of Arbitrage: Evidence from Short Interest (2014, methodology): “8 For instance, investor under-reaction might stem from a conservatism bias and use of a representativeness heuristic as in Barberis, Shleifer, and Vishny (1998), a combination of overconfidence and biased self-attribution as in Daniel, Hirshleifer, and Subrahmanyam (1998), or limited attention and ”
Pairs trading in the UK equity market: risk and return (2016, unknown): “Cross-sectional momentum has been shown to be susceptible to periods of persistent negative returns, which occur following periods of persistent negative market returns (Cooper, Gutierrez, and Hameed (2004) and Daniel and Moskowitz (2011)) or economic states (Chordia and Shivakumar (2002)).”
Dissecting Characteristics Nonparametrically (2020, unknown): “As an example, momentum returns conditional on other return predictors vary substantially over time, and we find a momentum crash similar to Daniel and Moskowitz (2016) as past losers appreciated during the recent financial crisis.”