Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.
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Updated
Feb 25, 2024 - Jupyter Notebook
Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.
Code for the WSDM 2021 paper "FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection".
This project studies the effects of the shape parameter estimator uncertainty at different threshold levels on the value-at-risk confidence interval for quantitative risk management (QRM) using the Generalized Pareto Distribution (GPD) from the Extreme Value Theory (EVT) approach.
R package for estimation of elliptical extreme quantile regions
Find The Tail - Matlab
A Multivariate Spatial Extreme Value Analysis of Reconstructed Detided Daily Mean Sea Level Data
Extreme value theory and GANs to generate compound coastal hazards (wind, precipitation, and significant wave height) over the Bay of Bengal.
Simulations for an article about extreme quantile region estimation
Extreme value theory and GANs to generate compound coastal hazards (wind speed + sea level pressure) from ERA5 reanalysis data over the Bay of Bengal.
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