The Dynamic Time-frequency Relationship between International Oil Prices and Investor Sentiment in China: A Wavelet Coherence Analysis.

AuthorYe, Zhengke
  1. INTRODUCTION

    Crude oil is the most important raw material for modern industrial society. In view of its irreplaceable importance, scholars have extensively studied the causes and consequences of crude oil price fluctuations (Kim and Jung, 2018; Karaki, 2018b; Pierru et al., 2018). On the one hand, researchers have explored the factors that cause crude oil price fluctuations (Hamilton, 2008; Edelstein and Kilian, 2009; Hamilton, 2013; Kilian, 2017; Herrera et al., 2019). On the other hand, several studies have analyzed the effect of oil price shocks on the macroeconomy. Specifically, the literature have investigated the effect of oil price shocks on consumption (Edelstein and Kilian, 2009; Alsalman and Karaki, 2019), investment (Edelstein and Kilian, 2007), the labor market (Herrera and Karaki, 2015; Herrera et al., 2017; Karaki, 2018b,a) and financial markets (Edelstein and Kilian, 2009; Alsalman and Herrera, 2015; Xiao et al., 2018). However, the existing literature is mainly concerned with the relationships between crude oil prices and macroeconomic variables from the perspective of fundamentals. With the development of the financialization of commodities, crude oil has gradually begun to share some of the properties of financial products (Degiannakis et al., 2018), and its prices are now more closely related to non-fundamentals. Therefore, some non-fundamental factors are gaining attention from investors and scholars. The concept of investor sentiment in the field of behavioral finance is one of the most concerned non-fundamental factors (He and Zhou, 2018). Thus, this study constructs an investor sentiment indicator for the Chinese stock market and investigates the dynamic co-movement relationship between investor sentiment and crude oil prices as well as three crude oil price shocks in both the time and the frequency domains via wavelet coherence (WTC) analysis.

    Understanding the existence of the dynamic co-movement relationship between investor sentiment and crude oil prices is straightforward. On the one hand, the financialization of commodities results in crude oil becoming an asset that competes equally with other financial assets (Arezki et al., 2014). More financial investors are adding crude oil into their portfolios, which means more speculation in crude oil markets. The significant impact of investor sentiment on speculative demand for assets has been well documented (Du et al., 2016). Hence, investor sentiment in financial markets could influence speculative demand for oil and therefore oil prices. On the other hand, numerous studies have found that fluctuations in crude oil prices affect a range of macroeconomic factors such as inflation, disposable income, and expectations about current and future economic conditions (Wen et al., 2019). As investor sentiment is sensitive to changes in macroeconomic conditions, it may change with fluctuations in crude oil prices.

    Taken together, the theoretical rationale of the above two aspects suggests a co-movement relationship between investor sentiment and crude oil prices. Based on this evidence, scholars have tried to empirically explore the relationship between investor sentiment and crude oil prices from different perspectives. First, the causal relationship between investor sentiment and crude oil prices was the primary focus of early research. By using the Granger causality test, for example, Choi (2014) empirically investigated the causal relationship between investor sentiment and price movements for the NYMEX crude oil futures market from 1999 to 2009. The empirical results suggested that prices significantly lead investor sentiment, whereas investor sentiment does not cause price movements in general. However, the conclusions of this study were not always consistent. He and Casey (2015) created an endurance index of oil service investor sentiment and found that the sentiment index Granger causes changes in crude oil prices and the returns of oil service stocks. Second, with the gradual determination of the causality between investor sentiment and crude oil prices, some scholars began to explore the role of investor sentiment in crude oil price fluctuations. Based on a suite of financial proxies, Deeney et al. (2015) proposed a measure of sentiment for West Texas Intermediate (WTI) and Brent crude oil futures and the empirical results suggested that futures prices for crude oil can be affected by investor sentiment. Furthermore, by applying the quantile regression method, Du et al. (2016) found that investor sentiment helps explain fluctuations in oil prices as well as in gasoline, heating oil, and oil company stock prices. Further, scholars started to explore the role of investor sentiment during drastic fluctuations in crude oil prices. In a quasi-experimental setting, Du and Zhao (2017) found a statistically significant and economically strong effect of investor sentiment on oil prices during the unprecedented surge in the spot price of crude oil from 2003 to 2008. Captured by nine proxies, Qadan and Nama (2018) demonstrated that volatility in these sentiment proxy indices spill over and could explain part of the volatility in oil prices. Third, the impact of crude oil price fluctuations on investor sentiment has received widespread attention from academics. Maslyuk-Escobedo et al. (2017) proposed a proxy for aggregate and individual energy market sentiment reflecting the dynamics of news associated with the energy sector and a variety of distinct energy markets and discovered that price discontinuities in energy commodities are related to large swings in market sentiment. Apergis et al. (2018) obtained similar conclusions that both crude oil and natural gas prices could significantly affect U.S. investor sentiment, using quantile regression. Recently, some scholars have found the contagion effect of crude oil price fluctuations on investor sentiment. Ding et al. (2017), by using a structural vector autoregression (SVAR) model, found that a 1% increase in the international crude oil price leads to a 3.94% decrease in stock market sentiment in the long term; further, the average contagion delay of international crude oil price fluctuations on Chinese stock market investor sentiment is eight months.

    To summarize, although existing studies of the relationship between investor sentiment and crude oil prices have achieved some interesting results, there are still several aspects worthy of further study. On the one hand, most of the studies conduct the research from the perspective of the time domain while ignoring the frequency domain. In other words, the existing studies fail to reveal the dynamic co-movement relationship between investor sentiment and crude oil prices at different frequencies. As we know, the crude oil market involves a variety of agents with objectives rooting in various time horizons. For example, policymakers with the primary concern of market equilibriums in the long term, companies with production and operation cycles ranging from several months to several years and investors with different investment strategies and so on. The effects of all these market components with various frequencies could be heterogeneous. However, the dynamic relationships between investor sentiment and crude oil price at different frequencies are still hidden in the previous research. On the other hand, few studies have focused on emerging economies such as China. As the largest developing country in the world, China has made remarkable strides in economic development and has also played an increasingly important role in the world economy (Zhang and Broadstock, 2016; Wen et al., 2018). China is also one of the largest net importers of oil (Broadstock et al., 2016) and the largest source of oil consumption growth in the world (Finley, 2012). Further, there is a significant difference between investor sentiment in the Chinese market and in other markets due to the existence of a large number of retail investors in China. Hence, it is of great significance to study the co-movement relationship between international crude oil prices and investor sentiment in the Chinese market.

    Therefore, our study takes a fresh look at this relationship. Following Baker and Wurgler (2006), we construct an investor sentiment index in the Chinese stock market through a two-stage principal component analysis (PCA) as the key investor sentiment proxy in our study. Then, for the first time, we adopt the perspective of both the time and the frequency domains by employing WTC analysis, a specific method under the wavelet analysis framework. Through the application of WTC analysis that decomposes time series data into various timescales, the relationship among time series can be studied from the time and frequency dimensions simultaneously. Specifically, we can explore the co-movement between crude oil prices and investor sentiment in both the short term and the long term and assess if crude oil prices can affect investor sentiment, or be affected by it, in a more visible way. Furthermore, the co-movement patterns of crude oil prices and investor sentiment in different time periods can also be found through WTC analysis. In addition to crude oil prices, we also use an SVAR model to decompose crude oil prices into three oil price shocks, namely an oil supply shock, an aggregate demand shock, and an oil-specific demand shock, following Kilian (2009) and conduct a WTC analysis of their relationships with investor sentiment separately. As pointed out by Su et al. (2018), these three shocks play different roles as drivers of the fluctuations in oil prices over time. Investigating the heterogeneous effects of varying oil price shocks on investor sentiment is of great importance for better understanding the relationship between crude oil prices and investor sentiment.

    Our research on Chinese investor sentiment is a useful supplement to existing research on the...

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