{"title":"The Predictive Power of Monetary Policy on International Stock Market Returns—Evidence From TV-ARMAX Model","authors":"Xiao Li, Wenjun Xue, Kaimeng Zhang","doi":"10.46557/001c.91484","DOIUrl":null,"url":null,"abstract":"In this paper, we apply the time-varying ARMA model with exogenous variable (TV-ARMAX) to examine the predictive power of monetary policy on international stock returns. This method allows time-varying coefficient estimates and uses time-dependent cumulated variation penalty to filter noisy outlier data points. Based on a wide range of 31 countries, our method robustly outperforms other popular methods including the simple linear-regression model (SLM), the vector autoregression and its variants (VAR, TV-VAR, and VARX) and the ARMA model with exogenous variable (ARMAX).","PeriodicalId":194045,"journal":{"name":"Asian Economics Letters","volume":"47 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Economics Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46557/001c.91484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we apply the time-varying ARMA model with exogenous variable (TV-ARMAX) to examine the predictive power of monetary policy on international stock returns. This method allows time-varying coefficient estimates and uses time-dependent cumulated variation penalty to filter noisy outlier data points. Based on a wide range of 31 countries, our method robustly outperforms other popular methods including the simple linear-regression model (SLM), the vector autoregression and its variants (VAR, TV-VAR, and VARX) and the ARMA model with exogenous variable (ARMAX).
本文应用带外生变量的时变 ARMA 模型(TV-ARMAX)来研究货币政策对国际股票回报的预测能力。该方法允许时变系数估计,并使用随时间变化的累积变异惩罚来过滤噪声离群数据点。基于 31 个国家的广泛数据,我们的方法稳健地优于其他流行方法,包括简单线性回归模型(SLM)、向量自回归及其变体(VAR、TV-VAR 和 VARX)以及带外生变量的 ARMA 模型(ARMAX)。