TITLE:
Forecasting and Backtesting of VaR in International Dry Bulk Shipping Market under Skewed Distributions
AUTHORS:
Qiannan Du
KEYWORDS:
Dry Bulk Shipping Market, Value-at-Risk, Skewed Generalized Error Distribution, Backtesting
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.9 No.5,
May
22,
2019
ABSTRACT: It is extremely important to model the empirical distributions of dry bulk shipping returns accurately in estimating risk measures. Based on several commonly used distributions and alternative distributions, this paper establishes nine different risk models to forecast the Value-at-Risk (VaR) of dry bulk shipping markets. Several backtests are explored to compare the accuracy of VaR forecasting. The empirical results indicate the risk models based on commonly used distributions have relatively poor performance, while the alternative distributions, i.e. Skewed Student-T (SST) distribution, Skewed Generalized Error Distribution (SGED), and Hyperbolic distribution (HYP) produce more accurate VaR measurement. The empirical results suggest risk managers further consider more flexible empirical distributions when managing extreme risks in dry bulk shipping markets.