Non-Parametric Future Looking Value-at-Risk

2011 ◽  
Author(s):  
Anders Wilhelmsson ◽  
Marcus Nossman
Keyword(s):  
At Risk ◽  
2008 ◽  
Vol 11 (05) ◽  
pp. 447-469 ◽  
Author(s):  
TIMOTHEOS ANGELIDIS ◽  
GEORGE SKIADOPOULOS

The fluctuation of shipping freight rates (freight rate risk) is an important source of market risk for all participants in the freight markets including hedge funds, commodity and energy producers. We measure the freight rate risk by the Value-at-Risk (VaR) approach. A range of parametric and non-parametric VaR methods is applied to various popular freight markets for dry and wet cargoes. Backtesting is conducted in two stages by means of statistical tests and a subjective loss function that uses the Expected Shortfall, respectively. We find that the simplest non-parametric methods should be used to measure freight rate risk. In addition, freight rate risk is greater in the wet cargoes markets. The margins in the growing freight derivatives markets should be set accordingly.


Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1639
Author(s):  
Dazhi Wang ◽  
Yanhua Chen ◽  
Hongfeng Wang ◽  
Min Huang

In this research, we study the non-parametric portfolio selection problem with Value at Risk (VaR) minimization and establish a new enhanced Mixed Integer Linear Programming (MILP) formulation to obtain the optimal solutions considering the symmetric property of VaR. We identify that the new MILP formulation can significantly reduce the computation burden of the MILP solver CPLEX. To solve larger-scale practical portfolio selection problems in reasonable computation time, we also develop the Particle Swarm Optimization (PSO) algorithm integrating an efficient Fast Feasible Solution Detection (FFSD) scheme to obtain the near-optimal solutions. Using the simulated datasets with different distribution parameters and skewness and kurtosis patterns, some preliminary numerical results are provided to show the efficiency of the new formulation and FFSD scheme.


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