Analysis of the Time-Varying Impact of Investment-Specific Technology Shocks on Stock Cross-Sectional Returns:A Quantitative Perspective on Fundamental Investing Based on Machine Learning
Investment-specific technology(IST)is an innovation resulting from the creation of new capital stock at the technological level,which is widely recognized as a significant driver of economic growth,and there is also a close relationship be-tween IST shocks and asset prices.Machine learning methods,extensively utilized in finance,can uncover more influential factors that elucidate asset price volatility.Therefore,examining the impact of IST shocks on asset prices holds substantial prac-tical importance.This paper leverages advancements in fundamental quantitative investing research to screen for the top-performing factor variables with investment performance in the machine learning approach.It constructs three IST shock prox-ies and nine micro-firm characteristics and market risk factors for the period from January 2004 to December 2021,based on data availability,and the TVP-SV-VAR model is employed for time-varying characteristics analysis to elucidate the effect of IST shocks on cross-sectional stock returns under varying firm characteristics.The findings indicate that the influence of IST shocks on cross-sectional stock returns varies over time across firm characteristics,with the direction and magnitude of the impact being uncertain and the lagged impact being short-to medium-term.IST shocks in the short term tend to further influence investors'future expectations of firms by affecting trading frictions such as trading volume and turnover in the short term.At the same time,in the medium term,the impact of IST shocks is more likely to affect growth factors such as changes in shareholders'equity,which in turn affect stock price volatility.
NETL
NSTL
万方数据
