Distributed sensor networks with hundreds of antenna arrays are widely utilized for radar detection systems. When observations of network nodes are correlated, an optimal copula-based fusion (termed CBF) rule is designed for correlated binary decisions under the Neyman-Pearson (NP) framework....

Risk evaluation is a forecast, and its validity must be backtested. Probability distribution forecasts are used in this work and allow for more powerful validations compared to point forecasts. Our aim is to use bivariate copulas in order to characterize the in-sample copulas and to validate...

To improve the dynamic assessment of risks of speculative assets, we apply a Markov switching MGARCH approach to portfolio forecasting. More specifically, we take advantage of the flexible Markov switching copula multivariate GARCH (MS-C-MGARCH) model of Fülle and Herwartz (2021). As an...

The unprecedented fiscal and monetary policy responses during the COVID-19 crisis have increased uncertainty about inflation. During crises periods, the strength of the transmission of inflation uncertainty shocks from one country to another tends to intensify. This paper examines empirical...

This paper studies how to construct and compare various optimal portfolio frame-works for investors in the context of the Vietnamese stock market. The aim of the study is to help investors to find solutions for constructing an optimal portfolio strategy using modern investment frameworks in the...

Highlights:• State-of-art review of vine copulas and stationary vine copulas.• Two types of vine copula models to capture cross-sectional and temporal dependence in ESG data.• Extreme ESG classes (i.e., classes A and D) show the highest and nonGaussian dependence to the market.• Future...

We propose a multi-asset pricing model which allows both the calibration to single-asset vanilla options, and the specification of any joint terminal distribution at each step of a discrete time grid. We also propose a way to calibrate that joint terminal distributions via normal mean-variance...

Despite the technology sector being highly responsive to market fluctuations, individual instances of its lower sensitivity to high market volatility and crisis are documented. This paper analyzes the dependence between the stock market volatility and technology stocks on the U.S. market using...

The availability of high-frequency trading data and developments in computing technology make it possible to evaluate Intraday Value-at-Risk (IVaR), a useful risk management tool for investors and regulators. In this paper, we propose a new model to evaluate and predict the IVaR for stocks based...