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...

Extreme event modeling has always attracted attention in domains such as hydrology, as well as in major financial markets where modelers benefit from an abundance of available data (Embrechts et. al, 1997). Following the recent global financial crises, however, proper models for modeling such...

The CCC-GARCH model, and its dynamic correlation extensions, form the most important model class for multivariate asset returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of Gaussianity. This paper considers the so-called...

We show that the value of risk reduction changes rapidly when loss is high, due to interactions between skewness of wealth () and kurtosis risk aversion (K(x¯)), increasing ambiguity in model predictions. However, when the initial probability of loss (p) <<< and K(x¯) <(>), risk seeking (risk averse), imprudent...</<<>

This study examines the Pastor-Stambaugh liquidity-augmented four-factor model to revisit whether the marketwide liquidity is indeed a state variable important for asset pricing in the U.S. equity market over the period 1/1966-12/1999. The study applies the Lewellen et al. (2010) two-pass...

We propose a new 3-step resampling approach to forecast portfolio tail risk conditional on the economic state. The approach first predicts economic states using a set of macroeconomic and financial variables. We then forecast the joint distribution of multiple assets in the portfolio according...

Systemic risk has drawn the attention of many researchers and financial institutions since the recent financial crisis. Popular systemic risk measures include CoVaR, CoES, MES and SRISK etc. However, there are only a few methods available on modeling these measures, and even less papers on...

Value-at-Risk (VaR) and Expected Shortfall (ES) are common high quantile- based risk measures adopted in financial regulations and risk management. In this paper, we propose a tail risk measure based on the most probable maximum size of risk events (MPMR) that can occur over a length of time....

This paper develops a Bayesian framework for the realized exponential generalized autoregressive conditional heteroskedasticity (realized EGARCH) model and adopts a standardized Student-t and a standardized skewed Student-t distributions for the return equation. The Bayesian estimators show more...

This study investigates the role of probability distribution in forecasting volatility and Value-at-Risk (VaR). We use the Realized GARCH model and high-frequency data from the cryptocurrency market and show that the role of probability distribution varies across different situations. A skewed-t...