What Explains the Dynamics of 100 Anomalies

By Heiko Jacobs. 2015

162 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

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Citations in the corpus

Anomalies across the globe: Once public, no longer existent? (2020, unknown): “In line with Jacobs (2016), point estimates are higher in developed markets than point estimates in emerging markets.”
Market maturity and mispricing (2016, unknown): “• Accruals [Sloan (1996)] • Net operating assets [Hirshleifer, Hou, Teoh, and Zhang (2004)] • Price momentum [Jegadeesh and Titman (1993)] • Gross profitability [Novy-Marx (2013)] • Asset growth [Cooper, Gulen, and Schill (2008)] • Return on assets [Fama and French (2006), Chen, Novy-Marx, and Zhang”
Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2017, background): “Jacobs (2015) provides a recent overview of 100 capital market anomalies - most of them are based on monthly data and not a single one employs advanced methods from statistical learning.”
Statistical arbitrage pairs trading strategies: Review and outlook (2017, unknown): “Despite these findings, we have to recognize that academic research about pairs trading is still small compared to contrarian and momentum strategies.3 However, interest has recently surged, 1Shleifer (2000) and Jacobs (2015) provide excellent overviews of relevant strategies.”
Deep learning with long short-term memory networks for financial market predictions (2017, background): “For example, Jacobs (2015) or Green et al. (2013) provide surveys comprising more than 100 of such capital market anomalies, which eﬀectively rely on return predictive signals to outperform the market.”