Publication Type
Journal Article
Version
publishedVersion
Publication Date
11-2015
Abstract
The key contribution in this paper is to provide a new approach in estimating the physical distribution of the underlying asset return by using a quadratic Radon-Nikodym derivative function. The latter function transforms a fitted Variance Gamma risk-neutral distribution that is obtained from traded option prices. The generality of the VG distribution helps to avoid unnecessary mis-specification bias. The estimated empirical distribution is then used to find the risk measure of VaR. We show that possible underestimation of VaR risk using existing methods is largely not due to VaR itself but perhaps due to mis-specification errors which we minimize in our approach. Our method of measuring VaR clearly captures large tail risk in the empirical examples on S&P 500 index.
Keywords
Density Estimation, Value-at-Risk, Forecasting and Prediction
Discipline
Finance and Financial Management | Management Sciences and Quantitative Methods
Research Areas
Finance
Publication
Journal of Mathematical Finance
Volume
5
Issue
5
First Page
423
Last Page
432
ISSN
2162-2434
Identifier
10.4236/jmf.2015.55036
Publisher
Scientific Research Publishing
Citation
Kian Guan LIM; CHENG, Hao; and YAP, Nelson K. L..
New Approach to Density Estimation and Application to Value-at-Risk. (2015). Journal of Mathematical Finance. 5, (5), 423-432.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4892
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.4236/jmf.2015.55036
Included in
Finance and Financial Management Commons, Management Sciences and Quantitative Methods Commons