Reversal

Heterogeneous Beliefs Model of Stock Market Predictability ArXiv ID: 2406.08448 “View on arXiv” Authors: Unknown Abstract This paper proposes a theory of stock market predictability patterns based on a model of heterogeneous beliefs. In a discrete finite time framework, some agents receive news about an asset’s fundamental value through a noisy signal. The investors are heterogeneous in that they have different beliefs about the stochastic supply. A momentum in the stock price arises from those agents who incorrectly underestimate the signal accuracy, dampening the initial price impact of the signal. A reversal in price occurs because the price reverts to the fundamental value in the long run. An extension of the model to multiple assets case predicts co-movement and lead-lag effect, in addition to cross-sectional momentum and reversal. The heterogeneous beliefs of investors about news demonstrate how the main predictability anomalies arise endogenously in a model of bounded rationality. ...

Diversified Statistical Arbitrage: Dynamically Combining Mean Reversion and Momentum Strategies ArXiv ID: ssrn-1666799 “View on arXiv” Authors: Unknown Abstract This paper presents a quantitative investment strategy that is capable of producing strong risk-adjusted returns in both up and down markets. The strategy combi Keywords: Quantitative investment strategy, Risk-adjusted returns, Momentum, Reversal, Portfolio construction Complexity vs Empirical Score Math Complexity: 7.5/10 Empirical Rigor: 6.0/10 Quadrant: Holy Grail Why: The paper employs advanced mathematical techniques like Principal Component Analysis (PCA) with eigenvalues and eigenvectors for decomposition, indicating high mathematical density. It also presents in-sample and out-of-sample performance analysis across multiple market environments (2008-2009), suggesting significant empirical testing and implementation focus. flowchart TD A["Research Goal: Develop a Quantitative Investment Strategy"] --> B["Methodology: Diversified Statistical Arbitrage"] B --> C["Data: Historical Stock Prices & Market Data"] C --> D{"Compute Signal Generation"} D --> E["Mean Reversion Strategy"] D --> F["Momentum Strategy"] E & F --> G["Dynamic Portfolio Construction"] G --> H["Key Findings: Strong Risk-Adjusted Returns"] H --> I["Outcomes: Effective in Both Up & Down Markets"]