A Taxonomy of Anomalies and Their Trading Costs

By Robert Novy-Marx, Mihail Velikov. 2014

527 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e4e55002cc2adb8a902f76e070c4563ebe105d63

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Citations in the corpus

ESG Rating Disagreement and Stock Returns (2019, methodology): “To gain a realistic impression as to whether they are, we followed the approach advocated by Novy-Marx and Velikov (2016).”
Prospect Theory and Stock Market Anomalies (2020, unknown): “After completing the analysis in Section IV, we came across another set of 23 anomalies, one constructed by Novy-Marx and Velikov (2016) as part of a study of transaction costs, in other words, for reasons that have nothing to do with prospect theory.”
Cross-Sectional and Time-Series Tests of Return Predictability: What Is the Difference? (2018, methodology): “In any event, for managing turnover, one would likely be better off using the various transaction cost mitigation techniques that Novy-Marx and Velikov (2016) discuss rather than implementing them incidentally by choosing between TS and CS thresholds.”
A Transaction-Cost Perspective on the Multitude of Firm Characteristics (2020, unknown): “Novy-Marx and Velikov (2016) finds that the short-term reversal strategy does not improve the investment opportunity set of an investor with access to the Fama-French factors, even when a buy-and-hold transaction-cost-mitigation strategy is employed.”
Are Financial Constraints Priced? Evidence from Textual Analysis (2018, unknown): “This result stands in contrast to much of the anomalies literature, in which anomalies are often driven by the short side, and short positions can be prohibitively costly to trade (Novy-Marx and Velikov, 2016).”
Demystifying Time‐Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations (2020, unknown): “11In undocumented results, we have additionally evaluated the performance of the less efficient range estimators by Parkinson (1980), Garman and Klass (1980) and Rogers and Satchell (1991).”
Shrinking the Cross Section∗ (2017, unknown): “regression (Tibshirani (1996)) and naturally leads to sparse solutions.”
Psychology-based Models of Asset Prices and Trading Volume (2018, background): “…have historically earned a higher average return than would be expected for their risk, as judged by the CAPM, even after taking transaction costs into account, at least for the low transaction costs incurred by sophisticated investors (Frazzini et al., 2015; Novy-Marx and Velikov, 2015).”