可预测性
计量经济学
经济
波动性(金融)
Lasso(编程语言)
股票市场
衡平法
库存(枪支)
金融经济学
随机波动
股票市场指数
计算机科学
统计
数学
机械工程
古生物学
马
万维网
政治学
法学
生物
工程类
作者
Feng Ma,Jiqian Wang,M.I.M. Wahab,Yuanhui Ma
标识
DOI:10.1016/j.ijforecast.2022.08.010
摘要
This study develops a shrinkage method, LASSO with a Markov regime-switching model (MRS-LASSO), to predict US stock market volatility. A set of 17 well-known macroeconomic and financial factors are used. The out-of-sample results reveal that the MRS-LASSO model yields statistically and economically significant volatility predictions. We further investigate the predictability of MRS-LASSO with respect to different market conditions, business cycles, and variable selection. Three factors (equity market returns, a short-term reversal factor, and a consumer sentiment index) are the most frequent predictors. To investigate the practical implications, we construct the expected variance risk premium (VRP) by using volatility forecasts generated from the LASSO and MRS-LASSO models to forecast future stock returns and find that those models are also powerful.
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