DeepVaR: a framework for portfolio risk assessment leveraging probabilistic deep neural networks.

ABSTRACT: Determining and minimizing risk exposure pose one of the biggest challenges in the financial industry as an environment with multiple factors that affect (non-)identified risks and the corresponding decisions. Various estimation metrics are utilized towards robust and efficient risk management frameworks, with the most prevalent among them being the Value at Risk (VaR). VaR is a valuable risk-assessment approach, which offers traders, investors, and financial institutions information regarding risk estimations and potential investment insights. VaR has been adopted by the financial industry for decades, but the generated predictions lack efficiency in times of economic turmoil such as the 2008 global financial crisis and the COVID-19 pandemic, which in turn affects the respective decisions

SUBMITTER: Fatouros G 

PROVIDER: S-EPMC9006212 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature