Estimating market risk under a wavelet-based approach: Mexican case

Author

Tellez, Jesus C. ; Vargas, Teresa ; Hernandez, Jose

Author_Institution

Dept. of Finance & Econ., ITESM, Atizapan de Zaragoza, Mexico

fYear

2009

fDate

8-11 Aug. 2009

Firstpage

353

Lastpage

357

Abstract

This paper aims to estimate value-at-risk and beyond the VaR for the main Mexican stock index (IPC) under a wavelet-based approach. The wavelet approach is used since financial time series have shown to be non-stationary and in most of the times non-normally distributed, and it allows to face the problem when signals have very high frequency components with short time spans, and low frequency components with long time spans. The IPC variance is decomposed into different time-scales using the discrete wavelet transform (DWT) and the least asymmetric (LA) Daubechies wavelet filter. Results show that the decomposed risk measure cannot be rejected at 95% and 99% confidence level.

Keywords

discrete wavelet transforms; econometrics; estimation theory; risk analysis; statistical distributions; stock markets; time series; DWT; IPC variance; LA Daubechies wavelet filter; Mexican case; Mexican stock index; VaR; confidence level; discrete wavelet transform-based approach; expected tail loss; frequency component; least asymmetric Daubechies wavelet filter; market value-at-risk estimation; nonnormal distribution; nonstationary financial time series; time scale; Discrete wavelet transforms; Filters; Finance; Fourier transforms; Frequency; Portfolios; Power generation economics; Reactive power; Tail; Wavelet analysis; Wavelet variance; expected tail loss; value-at-risk;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-4519-6

Electronic_ISBN

978-1-4244-4520-2

Type

conf

DOI

10.1109/ICCSIT.2009.5234557

Filename

5234557