In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...

Over recent years, a study on risk management has been prompted by the Basel committee for regular banking supervisory. There are however limitations of some widely-used risk management methods that either calculate risk measures under the Gaussian distributional assumption or involve numerical...

This paper addresses the problem of estimating the monotone boundary of a nonconvex set in a full nonparametric and multivariate setup. This is particularly useful in the context of productivity analysis where the efficient frontier is the locus of optimal production scenarios. Then efficiency...

This paper develops a fully nonparametric method for estimating value-at-risk based on the adaptive volatility estimation and the nonparametric quantile estimation. The proposed method is simple, fast and easy to implement. We evaluated its numerical performance on the basis of Monte Carlo study...

Electricity industry is important for our society and the nation's economic strength, and this dissertation includes two important topics in the industry: electricity market auctioning, and short-term load forecasting. In the first part of this dissertation, an optimization algorithm to solve...

This dissertation examines how households should optimally allocate their portfolio choices between risky stocks and risk-free bonds over their lifetime. Traditional lifecycle models in previous work with normal-distributed stock returns suggest that the allocation toward stocks should start...