Abstract

This paper aims to explore the dynamic relationships between the crude oil price (shocks) and investor sentiment. Specifically, this paper utilizes web crawler to construct Chinese investor sentiment index. The structural vector autoregression (SVAR) model is then used to decompose the crude oil price shocks into three types of oil price shocks. Finally, the wavelet coherence analysis (WTC) is employed to study the dynamic correlation between crude oil price (shocks) and investor sentiment in the time and frequency domain, and their asymmetric dynamic correlation under different trends of crude oil price. Using data from February 2013 to June 2021, our empirical results suggest the heterogeneous dynamic correlations and lead-lag relationships exist between crude oil price (shocks) and investor sentiment over different time and frequency domains. In addition, there are asymmetric dynamic correlations and lead–lag relationships between crude oil price (shocks) and investor sentiment under different trends of crude oil price.

Highlights

  • Crude oil prices and investor sentiment is crucial for our economic development.Crude oil, as a core source of energy, is essential for the global economy

  • We complement the literature on the dynamic correlation and its lead–lag relationship between crude oil price shocks and investor sentiment by taking a systematic look at asymmetry under different trends of crude oil price

  • The conclusion can be drawn as follows: On the one hand, heterogeneous dynamic correlations and lead-lag relationships exist between crude oil price and investor sentiment over different time and frequency domains

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Summary

Introduction

Crude oil prices and investor sentiment is crucial for our economic development.Crude oil, as a core source of energy, is essential for the global economy. Boubaker and Raza [16] employed a multivariate autoregressive moving average generalized autoregressive conditional heteroskedasticity corrected Dynamic Conditional Correlation (VARMA-GARCH-cDCC) model and wavelet multiresolution analysis to investigate the spillover effects of volatility and shocks between oil prices and the BRICS stock markets at different time horizons. Their results manifested that oil price and stock market prices are directly affected by their own news and volatilities and indirectly affected by the volatilities of other prices and wavelet scale. Fully understanding the relationship between crude oil prices and investor sentiment is crucial for our economic development

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