Low Volatility Stock Portfolio Through High Dimensional Bayesian Cointegration

• DOI: 10.48550/arxiv.2407.10175
• Publication Date: 2024-07-14
• Authors: Parley Ruogu Yang; Alexander Y. Shes...
• Keywords: Stock (firearms)

We employ a Bayesian modelling technique for high dimensional cointegration estimation to construct low volatility portfolios from large number of stocks. The proposed framework effectively identifies sparse and important relationships amongst baskets stocks across various asset spaces, resulting in with reduced volatility. Such persist well over the out-of-sample testing time, providing practical benefits portfolio construction optimization. Further studies on drawdown minimization also highlight including cointegrated as risk management instruments.