Wavelet based Filtered historical simulation in different time horizons in Tehran Stock Exchange
Quarterly Journal of Securities Exchange

Quarterly Journal of Securities Exchange

Wavelet based Filtered historical simulation in different time horizons in Tehran Stock Exchange

Document Type : Original Article

Authors
Javad Shekarkhah 1
Meysam Amiri 2
vahid vaisizadeh 3
1 Assistant Professor, Department of Accounting, Allameh Tabatabai University, Tehran, Iran.
2 Assistant Professor, Department of Financial Management, Allameh Tabatabai University, Tehran, Iran.
3 PhD Student in Financial Management, Allameh Tabatabai University, Tehran
10.22034/jse.2021.11469.1618
Abstract
Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up to 2023, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. This research seeks to introduce the most accurate and reliable models to estimate Expected shortfall among both conventional and advanced models including Historical simulation model, ARMA-GARCH model, Filtered historical simulation model, Conditional extreme value theory model and a new hybrid semiparametric model called "Wavelet based Filtered historical simulation" in the Tehran Stock Exchange. Based on the results of research, using the 11-year daily main index of Tehran Stock Exchange return from 2010/4/7 to 2020/4/1 (more than 2400 daily of index return data) and applying various backtesting method, the proposed new wavelet based Filtered historical simulation hybrid model has outperforms other competing models in all time horizons and confidence levels.
Keywords
expected shortfall
wavelet theory
conditional extreme value theory model
wavelet based Filtered historical simulation
backtest

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Quarterly Journal of Securities Exchange
Volume 15, Issue 57
Spring 2022
Pages 225-254