DefinePK

Research Objective

To examine the economic and financial conditions that drive volatility jumps in Chinese equity stocks during the pre and post-COVID-19 periods.

Methodology

The study uses monthly returns of Chinese equity stocks (SZSE index) from July 2010 to August 2023, divided into pre-COVID-19 (July 2010 - November 2019) and post-COVID-19 (April 2020 - August 2023) periods. Volatility jumps are identified using the median variance approach (Andersen, 2012). Stepwise regression analysis is employed to determine the key drivers of these volatility jumps. Monthly economic variables (GDP, industrial production, oil prices, exchange rate, consumer confidence, gold prices, inflation, consumer price index) and financial variables (stock prices, credit spread, policy uncertainty, sentiment index) are used.

Methodology Flowchart

                        graph TD
    A["Data Collection: Monthly Returns of SZSE Index 2010M07-2023M08"] --> B["Divide into Pre/Post COVID-19 Periods"];
    B --> C["Identify Volatility Jumps using Median Variance Approach"];
    C --> D["Collect Monthly Economic and Financial Data"];
    D --> E["Perform Stepwise Regression Analysis"];
    E --> F["Analyze Drivers of Volatility Jumps"];
    F --> G["Compare Pre and Post Crisis Findings"];
    G --> H["Formulate Conclusions and Implications"];                    

Discussion

The study highlights that while economic factors like GDP and industrial production tend to dampen volatility jumps, financial market conditions such as stock prices and policy uncertainty can exacerbate them. The shift observed in the pre and post-COVID-19 periods suggests that the drivers of volatility jumps are not static and can be influenced by major global events. The findings imply that business cycle fluctuations may negatively impact volatility, while short-term financial market uncertainty directly influences jumps.

Key Findings

Economic factors (GDP, industrial production, oil prices, exchange rate) are generally found to negatively influence volatility jumps, while financial conditions (stock prices, policy uncertainty, sentiment index) directly cause jumps in volatility. There is a notable shift in the behavior of economic and financial conditions from the pre-crisis to the post-crisis period.

Conclusion

Economic factors are negatively associated with volatility jumps, while financial conditions are positively associated. The intensity and behavior of these factors shift significantly between the pre and post-COVID-19 periods. Business cycle fluctuations can cause jumps in returns volatility negatively, whereas short-term financial market uncertainty directly influences jumps in Chinese equity markets. Investors and policymakers can use these insights for short-term (financial conditions) and long-term (economic conditions) decision-making.

Fact Check

1. Time Period: The study analyzes Chinese equity stock data from July 2010 to August 2023.
2. Methodology for Jumps: Volatility jumps are identified using the median variance approach of Andersen (2012).
3. Key Drivers: The study identifies economic factors (GDP, industrial production, oil prices, exchange rate) and financial conditions (stock prices, policy uncertainty, sentiment index) as key drivers of volatility jumps.

Mind Map