Quant Letter: October 2023, Week 1

Weekly quantitative finance newsletter

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Quantitative

ML and Kalman Filter for Pair Trading: The research uses machine learning and Kalman filtering to improve pair trading strategies, increasing efficiency and returns. (2023-10-03, shares: 4.0)

CEO Effect Revisited with ML: The study suggests that the influence of CEOs on their firms' performance, known as the CEO effect, is not significant, based on machine learning models and predictive analytics. (2023-10-03, shares: 3.0)

Multi-period Static Hedging of Options: The paper expands the method of hedging European options to include options over multiple short maturities, comparing the Black-Scholes and Merton Jump Diffusion models. (2023-09-29, shares: 2.0)

Regime Detection in Multidimensional Time Series Data using Automation: The Wasserstein k-means clustering algorithm effectively identifies regimes in synthetic one-dimensional time series data, with a proposed extension to multidimensional data. (2023-09-29, shares: 2.0)