Dynamic multi-scale expected shortfall in Tehran Stock Exchange: a spectral decomposition of tail risk across time horizons

Subject Areas : Risk Management

Seyed Ali Mousavi Sarhadi ¹ (Department of Financial Management, Qom Branch, Islamic Azad University, Qom, Iran.)
Hosein Izadi ² (Department of Accounting, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran.)
Mojgan Safa ³ (Department of Accounting, Qom Branch, Islamic Azad University, Qom, Iran.)
Mohammadreza Pourfakharan ⁴ (Department of Accounting, Qom Branch, Islamic Azad University, Qom, Iran.)

Received: 2022-07-27 Accepted : 2022-12-11 Published : 2022-12-22

Keywords: Tehran Stock Exchange, Spectral Analysis, time horizons, Multi-Scale Dynamic Expected shortfall (DMS-ES), tail Risk,

Abstract :

Purpose: The main purpose of the present study is to investigate the tail risk in the Tehran Stock Exchange using dynamic methods and time series spectral analysis in the form of the dynamic multi-scale Expected Shortfall (DMS-ES).Methodology: In this study, the daily data of Tehran Stock Exchange total index in the period 2011/03/26 - 2022/03/19 were used then extracting the short-term, medium-term and long-term information components of the index return time series, four predictive models of expected fallout (ES) were estimated using Taylor (2017) approach at different time horizons.Findings: The results of estimating the models and back tests show that the expected shortfall (ES) is short-term in nature and the dynamic model using short-term components in the one-day time horizon has the highest efficiency among the introduced models. In addition, the results of comparing the models based on the average loss test show that the use of spectral analysis components increases the efficiency of dynamic predictions of the expected shortfall (ES) at different time horizons.Originality / Value: Finally, according to the results of this study, it is suggested to use dynamic models and signal decomposition analysis algorithms to increase the efficiency of risk criteria predictions.

References:

Acerbi, C; Tasche, D. (2002). Expected Shortfall: A Natural Coherent Alternative to Value at Risk. Economic Notes, 31(2), 379–388.

Artzner, P; Delbaen, F; Eber, J. M; Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228.

Berger, T; Gençay, R. (2018). Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment. Journal of Economic Dynamics and Control, 92, 30–46.

Botshekan, M. H; Peymani, M; Sadredin Karami, M. M. (2019). Estimate and evaluate non-parametric value at risk and expected shortfall based on principal component analysis in Tehran Stock Exchange. Journal of Financial Management Perspective, 8(24), 79-102. [In Persian]

Bu, D; Liao, Y; Shi, J; Peng, H. (2019). Dynamic expected shortfall: A spectral decomposition of tail risk across time horizons. Journal of Economic Dynamics and Control, 108, 103753.

Engle, R. F; Manganelli, S. (2004). CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business & Economic Statistics, 22(4), 367–381.

Fallahpour, S; Tabasi, H. (2020). Estimation of Expected Shortfall Based on Conditional Extreme Value Theory Using Multifractal Model and Intraday Data in Tehran Stock Exchange. Financial Research Journal, 22(1), 27-43. [In Persian]

Gerlach, R; Wang, C. (2020). Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures. International Journal of Forecasting, 36(2), 489–506.

Gilanipour, J. (2020). The Evaluation of Systemic Risk in the Iran Banking System by Marginal Expected Shortfall (MES) Criterion. Journal of Economic Research and Policies, 27 (92), 407-429. [In Persian]

Gneiting, T. (2011). Making and Evaluating Point Forecasts. Journal of the American Statistical Association, 106 (494), 746–762.

Graps, A. (1995). An introduction to wavelets. IEEE Computational Science and Engineering, 2(2), 50–61.

Hallin, M; Trucíos Maza, C. C. (2020). Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Model Approach. SSRN Electronic Journal.

Hassani, M; Moradi, S. (2021). The Mediator role of Information Asymmetry in Imperfect Competition Market on the relation between Earnings Forecast Bias & Idiosyncratic Risk derived from Capital Assets Pricing Model. Advances in Finance and Investment, 1(1), 81-100. [In Persian]

Mohammadi Salari, E; Rostami, M. R; Gholami Jamkarani, R; safa, M. (2021). Tail Risk Analysis Using realized measure and Dynamic Asymmetric Laplace Models in Tehran Stock Exchange. Financial Engineering and Portfolio Management, 12(48), 391-410. [In Persian]

Naderi Nooreini, M. M. (2018). The Best Methodology of Estimation of Value-at-Risk in Iranian Mutual Funds. Journal of Asset Management and Financing, 6(1), 159-180. [In Persian]

Patton, A. J; Ziegel, J. F; Chen, R. (2019). Dynamic semiparametric models for expected shortfall (and Value-at-Risk). Journal of Econometrics, 211(2), 388–413.

Percival, D. B; Walden, A. T. (2000). Wavelet Methods for Time SeriesAnalysis. Cambridge university press.

Samavi, M. E; Nikoomaram, H; Madanchi Zaj, M; Yaghobnezhad, A. (2022). Dynamic GAS Based Modeling for Predicting and Assessing the Value at Risk of Tehran Stock Exchange Index and Gold. Advances in Finance and Investment, 3(7), 120-95. [In Persian]

Saranj, A; Nourahmadi, M. (2016). Estimating of value at risk and expected shortfall by using conditional extreme value approach in Tehran Securities Exchange. Financial Research Journal, 18(3), 437-460. [In Persian]

Schleicher, C. ( 2002) An introduction to wavelets for economists. Monetary and Financial Analysis Department Bank of Canada.

Seyfi, S. M. S; Sharifi, A; Arian, H. (2021). Portfolio Value-at-Risk and expected-shortfall using an efficient simulation approach based on Gaussian Mixture Model. Mathematics and Computers in Simulation.

Taiebysani, E; Changi Ashtiani, M. (2018). Forecasting Volatility & Risk Management in Tehran Stock Exchange through Long memory impacts. Financial Engineering and Portfolio Management, 9(34), 121-142. [In Persian]

Taleblou, R; davoudi, M. M. (2018). Estimation of Optimal Investment Portfolio Using Value at Risk (VaR) and Expected Shortfall (ES) Models: GARCH-EVT-Copula Approach. Economics Research, 18(71), 91-125. [In Persian]

Taylor, J. W. (2017). Forecasting Value at Risk and Expected Shortfall Using a Semiparametric Approach Based on the Asymmetric Laplace Distribution. Journal of Business & Economic Statistics, 37(1), 121–133.