Summary:

On 29 July 2024, ACI hosted a seminar entitled “Data Science and Financial Risk Management”. This seminar explored how advanced statistical techniques are used in monitoring and managing financial risks in emerging markets.

Professor Wolfgang Haerdle, Director of the Institute for Digital Assets, made a keynote presentation in the seminar. Addressing the need for risk measures in various markets, the Financial Risk Meter (FRM) effectively predicts future market risks. The FRM uses Quantile-LASSO regression to identify systemic financial risks and dependencies among extreme events across different assets. It connects asset pricing kernel volatility, the highest possible Sharpe ratio, and overall market volatility. In his studies, the FRM for China demonstrates its strength in detecting systemic risks and shows a negative correlation with the interconnectedness of financial institutions during extreme events. When applied to major financial institutions in Emerging Markets, the FRM highlights peak risks during crises. The expectile FRM improves the prediction of extreme losses and offers a range of risk indicators. Overall, the FRM provides valuable insights into systemic risks across various markets, helping policymakers and investors make informed decisions.

Key Highlights:

1. The financial risk meter predicts the tail-event risk contagion and predicts systemic risk in a single framework.

2. The financial risk meter accurately predicts tail-event risks and return volatility, at both the market and firm levels.

3. The financial risk meter quantifies macroeconomic factors’ contribution to systemic risk via the Shapley method.

By XIE, Taojun