4 papers
Separation-based causal discovery for extremes
Junshu Jiang, Jordan Richards, Raphaël Huser +1
Structural causal models (SCMs), with an underlying directed acyclic graph (DAG), provide a powerful analytical framework to describe the interaction mechanisms in large-scale comp…
Forecasting the Term Structure of Interest Rates with SPDE-Based Models
Qihao Duan, Alexandre B. Simas, David Bolin +1
The Dynamic Nelson--Siegel (DNS) model is a widely used framework for term structure forecasting. We propose a novel extension that models DNS residuals as a Gaussian random field,…
Intrinsic Whittle--Matérn fields and sparse spatial extremes
David Bolin, Peter Braunsteins, Sebastian Engelke +1
Intrinsic Gaussian fields are used in many areas of statistics as models for spatial or spatio-temporal dependence, or as priors for latent variables. However, there are two major…
The Efficient Tail Hypothesis: An Extreme Value Perspective on Market Efficiency
Junshu Jiang, Jordan Richards, Raphaël Huser +1
In econometrics, the Efficient Market Hypothesis posits that asset prices reflect all available information in the market. Several empirical investigations show that market efficie…