This paper studies random vectors X featuring symmetric distributions in that i) the order of the random variables in X does not affect its distribution, or ii) the distribution of X is symmetric at zero. We derive a number of characterization results for such random vectors, thereby connecting...

We employ a mixed-frequency quantile regression approach to model the time-varying conditional distribution of the US real GDP growth rate. We show that monthly information on the US financial cycle improves the predictive power of an otherwise quarterly-only model. We combine selected quantiles...

The stock options implied volatility skew reflects both the structural risk characteristics of the underlying company and the short-term information flow about the stock price movement. This paper builds a semi-structural cross-sectional option pricing model to separate the structural risk...

Our data, relating to a period of extreme market turmoil, show typical leptokurtosis and skewness, leading us to consider the skewed exponential power distribution of Fernández et al. (1995), referred to as the SEP3. We demonstrate that the conditional forecasting of VaR and CVaR, made up of a...

Using Compustat data, we reproduce the annual return distribution each year from 1963 to 2020 of the largest 500 and the next-largest 1000 US stocks, which on average represent about 96% of investable US stock capitalization. In the average calendar year about 65% (62%) of the largest (smaller)...

No abstract available.This paper proposes a portfolio selection model for Fund of Funds(FoFs) with the framework of mean-variance-skewness-kurtosis. Our model considers the time-varying relationship between realized higher moments and subsequent FoFs. The cardinality constraint is also included...

This paper presents the binomial expansion and series with optimized binomial coefficients. The binomial series is built on the building blocks of optimized binomial coefficients and multiple summations of geometric series

There coexist two popular autoregressive conditional density model classes for series of positive financial variables such as realized volatility. One is a class of multiplicative error models (MEM), where the conditional mean is modelled autoregressively, while the specified shape of...

We derive upper and lower bounds for the Range Value-at-Risk of a unimodal random variable under knowledge of the mean, variance, symmetry, and a possibly bounded support. Moreover, we provide a generalization of the Gauss inequality for symmetric distributions with known support