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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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3 results for “Copula-GARCH”

Multivariate time-series modeling with generative neural networksstat.ME

Generative neural networks model multivariate time series data.

problem Modeling cross-sectional dependence in multivariate time series data.

method ARMA-GARCH for serial dependence, PCA for dimensionality reduction, GMMN for cross-sectional dependence.

result GMMN-GARCH approach produces better predictive distributions and probabilistic forecasts.

Generative neural networks Multivariate time series Copula-GARCH ARMA-GARCH PCA

2020-02-25abs ↗pdf ↗

Modeling Volatility and Dependence of European Carbon and Energy Pricesq-fin.ST

Model predicts volatility and dependencies in EUA and energy prices.

problem Analyzing uncertainty and dependencies in European carbon and energy prices.

method Probabilistic multivariate conditional time series model with VECM-Copula-GARCH structure.

result Forecasting performance evaluated in an extensive rolling-window study.

carbon prices energy prices volatility dependence VECM-Copula-GARCH

2022-08-30abs ↗pdf ↗

Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?q-fin.RM

Copulas outperform marginal models in multivariate risk forecasting, reducing model risk by narrowing down the set of models.

problem Model risk in multivariate risk forecasting, especially during crises.

method Comprehensive empirical study comparing Copula-GARCH models with fixed marginals, copulas, or neither.

result Model risk is almost entirely due to copula choice, not marginal models.

model risk multivariate risk forecasting copulas marginals Value-at-Risk

2021-09-22abs ↗pdf ↗