Economic Psychology in China's Energy Sector: From Capital to Consumer Market

中國能源產業中的經濟心理學:從資本市場到消費者市場

Student thesis: Doctoral Thesis

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Author(s)

Related Research Unit(s)

Detail(s)

Awarding Institution
Supervisors/Advisors
  • Lin ZHANG (Supervisor)
  • Lingling Zhang (External person) (External Supervisor)
Award date9 Sep 2022

Abstract

This research aims to study the influence of economic psychological factors in the energy sector in China. We take the economic psychological factors of market participants as variables and conduct empirical research on their impact on China's energy sector. In the three studies we conducted, we respectively studied the capital and consumer markets. Capital market and consumer market are two major markets in economic operation.

In the study of the capital market, we selected China's newly established crude oil futures as the research object. According to the behavioral finance theory, investor sentiment plays an important role in the trend of asset price and risk in the capital market. In the first study, we examine the extent of predictive power investor sentiment has over the price of China’s crude oil. We first constructed investor sentiment indexes of China’s crude oil futures based on specific economic variables and comments found on one of the most active online financial forums. According to our findings, the long short-term memory model combined with the composite sentiment index performed best due to a lower rate of prediction errors and greater directional accuracy for time-series forecasting of one-day-ahead prices. In this way, this study could aid researchers to more effectively investigate the rapidly changing and highly speculative nature of the energy sector.

In the second study, it incorporates investor sentiment indices into the HAR model to improve its power of predicting crude oil futures risk. Using the 5-minute high-frequency trading data of INE crude oil futures to construct the daily realized volatility, the original and revised HAR models are used for in-sample regression and out-of-sample forecasting daily, weekly, and monthly basis. The results show that the sentiment indices calculated from comments and the search trend have incremental information content for forecasting the realized volatility of INE crude oil futures in the short and middle term, the search volume is the best indicator for weekly risk forecasting of INE crude oil futures. There is no robust index that can improve the performance of HAR-type model for the long-term risk prediction.

We then shifted our focus to the consumer market. Automobile is an important commodity for energy terminal use. The market share competition between new energy vehicles and traditional fuel vehicles is a hot topic in recent years. Therefore, in the study of China's consumer market, we choose new energy vehicles as the research object. Considering that we live in a highly complex social environment, many of our most important decisions are made in the context of social interaction. We introduced the role of proactive social learning in climate change using the public’s Internet search index and argued that the more proactive social learning in climate change, the more the sales of new energy vehicles. Furthermore, we further compare the positive factors of the two aspects of proactive social learning and summarizes the mediating role of localized features by decomposing proactive social learning behavior into the reasons and impacts of climate change and analyzing the results at the city level.