Portfolio Tail Risk: A Multivariate Extreme Value Theory Approach [PDF]
Entropy, 2020 This paper develops a method for assessing portfolio tail risk based on extreme value theory. The technique applies separate estimations of univariate series and allows for closed-form expressions for Value at Risk and Expected Shortfall. Its forecasting
Miloš Božović
doaj +2 more sources
COVID-19: Tail risk and predictive regressions [PDF]
PLoS ONE, 2022 The paper focuses on econometrically justified robust analysis of the effects of the COVID-19 pandemic on financial markets in different countries across the World.
Walter Distaso +3 more
doaj +3 more sources
Tail Risk Spillover Between Global Stock Markets Based on Effective Rényi Transfer Entropy and Wavelet Analysis [PDF]
EntropyTo examine the spillover of tail-risk information across global stock markets, we select nine major stock markets for the period spanning from June 2014 to May 2024 as the sample data. First, we employ effective Rényi transfer entropy to measure the tail-
Jingjing Jia
doaj +2 more sources
Will a boom be followed by crash? A new systemic risk measure based on right-tail risk [PDF]
Frontiers in Psychology, 2023 In this study, we demonstrate that high short-term gains on the A-share market may lead to significant losses in the future and potentially cause a market catastrophe.
Qing Liu, Mengxia Xu, Jinwu Xiong
doaj +2 more sources
The effect of Size, Value and Idiosyncratic Risk Anomalies on the Relationship between Tail Risk and Stock Excess Returns [PDF]
Iranian Journal of Accounting, Auditing & Finance, 2022 Capital market anomalies are caused by factors haven’t been considered in capital asset pricing models. The theories of extreme value are one of the arguments for explaining anomalies.
Mostafa Ramezani Sharif Abadi +2 more
doaj +1 more source
Is tail risk priced in the cross-section of international stock index returns?
Modern Finance, 2023 This study examines the predictive power of tail risk measures in stock indices returns using a comprehensive dataset covering 50 countries from 1926 to 2021.
Aleksander Mercik
doaj +1 more source
Exploiting Distributional Temporal Difference Learning to Deal with Tail Risk
Risks, 2020 In traditional Reinforcement Learning (RL), agents learn to optimize actions in a dynamic context based on recursive estimation of expected values. We show that this form of machine learning fails when rewards (returns) are affected by tail risk, i.e ...
Peter Bossaerts +2 more
doaj +1 more source
Pensamiento Crítico, 2018 En el presente trabajo se realizará la simulación el efecto de la interdependencia y el contagio en las decisiones de compra y venta de los inversionistasen un mercado financiero de tipo Black-Schole,donde existen dos activos financieros: acciones ...
Jesús Barrantes Limahuaya +2 more
doaj +1 more source
Bivariate Copula Trees for Gross Loss Aggregation with Positively Dependent Risks
Risks, 2022 We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees.
Rafał Wójcik, Charlie Wusuo Liu
doaj +1 more source
Tail Risk and Extreme Events: Connections between Oil and Clean Energy
Risks, 2021 Do tail events in the oil market trigger extreme responses by the clean-energy financial market (and vice versa)? This paper investigates the relationship between oil price and clean-energy stock with a novel methodology, namely extreme events study. The
Elisa Di Febo +2 more
doaj +1 more source