extreme events

Statistical Modeling of Financial Extremes and Volatility Dynamics

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B2 R5220

This thesis provides comprehensive statistical tools for understanding and modeling extreme risks and volatility dynamics in financial markets.

Understanding Extreme Market Behavior: The Efficient Tail Hypothesis

2 min read ·
A new study by researchers Junshu Jiang, James Richards, Raphaël Huser, and David Bolin introduces the Efficient Tail Hypothesis (ETH), an analogue of the Efficient Market Hypothesis focused on extreme events in financial markets. Drawing on extreme value theory, the team developed a novel statistical measure to evaluate whether asset markets remain informationally efficient even during rare, extreme fluctuations. Their findings not only challenge conventional wisdom on market efficiency but also open the door to identifying potential opportunities (and risks) that emerge during market

A sharper view of flood risk

1 min read ·
Extreme weather patterns and regions at risk of flooding could be easier to spot using a new statistical model for large spatial datasets.

Junshu Jiang

Ph.D. Student, Statistics