Exploring Extreme Downside Risks: A Comparative Analysis of the S&P 500 and CSI 300 Index Using Various Risk Metrics
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Weixun Xie
CoPIs:
Sihan Fu
College:
The Dorothy and George Hennings College of Science, Mathematics, and Technology
Major:
Mathematical Sciences
Faculty Research Advisor(s):
Abootaleb Shirvani
Abstract:
This research project conducts a comparative analysis of the S&P 500 and CSI 300 Index over a ten-year period to investigate extreme downside risks. The study employs a range of risk metrics, including drawdown, Value at Risk (VaR), and Conditional Value at Risk (CVaR) methodologies, with a focus on assessing and contrasting the markets' risk exposure at significant confidence levels during periods of extreme downside movement.
To capture the evolving dynamics of extreme downside risks within each market, a comprehensive dataset spanning a decade is utilized. The research adopts a rolling window approach, recalculating the risk metrics with a one-day forward shift of the window to ensure relevance and adaptability to changing market conditions. This methodology provides a nuanced understanding of risk exposure over time.
Furthermore, the study integrates stock returns with the risk metrics to shed light on the intricate relationship between market performance and risk management. By employing visual representations, the research offers insights into the risk-return trade-off within the S&P 500 and CSI 300 Index, providing an understanding of how extreme downside risks impact investment outcomes.
The project's primary objective is to unveil the distinct risk characteristics of these major stock exchanges, contributing to the advancement of risk management practices. The findings aim to inform investors, policymakers, and researchers about the nuances of extreme downside risks in financial markets. By empowering stakeholders with valuable insights, the research facilitates more informed decision-making and robust risk mitigation strategies in an ever-changing financial landscape.