Statistical Scenario Analysis for Financial Risk Management

Date: Thursday 18 June 2026, 5.30PM - 6.30PM
Hymans Robertson Office, 20 Waterloo Street, Glasgow, G2 6DB
Local Group Meeting
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Ping Wu will present her research on modelling equity returns in a distributional regression framework.  This talk will be followed by a presentation from Joe Meagher discussing Hymans’ approach to scenario analysis.
 
Ping Wu is a Lecturer in the Department of Economics at the University of Strathclyde. She will deliver a talk entitled “U.S. Economy and Global Stock Markets: Insights from a Distributional Approach”.
 
Financial markets are interconnected, with micro-currents propagating across global markets and shaping economic trends. This paper moves beyond traditional stock market indices to examine cross-sectional return distributions15 in our empirical application, each representing a distinct global market. To facilitate this analysis, we develop a matrix functional VAR method with interpretable factors extracted from cross-sectional return distributions. Our approach extends the existing framework from modelling a single function to multiple functions, allowing for a richer representation of cross-sectional dependencies. By jointly modelling these distributions with U.S. macroeconomic indicators, we uncover the predictive power of financial market in forecasting macro-economic dynamics. Our findings reveal that U.S. contractionary monetary policy not only lowers global stock returns, as traditionally under-stood, but also dampens cross-sectional return kurtosis, highlighting an overlooked policy transmission. This framework enables conditional forecasting, equipping policymakers with a flexible tool to assess macro-financial linkages under different economic scenarios.

Following this talk, Joe Meagher from Hymans Robertson will deliver a presentation on Hymans' approach to scenario analysis.
 
Ping Wu (Department of Economics, University of Strathclyde)
Joe Meagher (Hymans Robertson)
 
Royal Statistical Society Glasgow Local Group (glasgowlg@rss.org.uk)
 
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