Estimation of Expected Shortfall Based on Conditional Extreme Value Theory Using Multifractal Model and Intraday Data in Tehran Stock Exchange

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

FALLAHPOUR SAEED; TABASI HAMED

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: FINANCIAL RESEARCH Year:2020 | Volume:22 | Issue:1 Page(s): 27-43

Download Full-Text

Persian Verion

View:

407

Download:

Cites:

Information Journal Paper

Title

Estimation of Expected Shortfall Based on Conditional Extreme Value Theory Using Multifractal Model and Intraday Data in Tehran Stock Exchange

Author(s)

FALLAHPOUR SAEED | TABASI HAMED | Issue Writer Certificate

Keywords

Back-testingQ1

Expected shortfallQ1

Intraday dataQ1

Multifractal Volatility ModelQ1

Peakover Threshold ModelQ1

Abstract

Objective: After the financial crisis in 2008, market practitioners and financial researchers began to attach more importance to risk measurement and modeling. Expected shortfall is recognized risk measures in financial literature. Methods: By the estimation of Expected shortfall as a coherent risk measure, and by use of conditional extreme value theory and combining new volatility measures, this research attempts to introduce a new model for risk measurement. Intraday data has been used in this research in order to estimate mentioned risk measures. Results: The results show that in comparison with alternative models, such as GARCH conditional peak over threshold models, multifractal conditional peak over threshold models, which utilize Intraday data, perform better in risk estimation. In addition, the use of extreme value theory brings about more favorable results in risk estimation. In this research, we use a new Back-testing models in order to back-test Expected shortfall. Conclusion: The use of the normal distribution function for the disruption components to estimate the expected drop has not been successful, and has led to an estimate of the low risk category. The use of Student's t-distribution in estimating risk measures has been acceptable, although in some cases it has led to an estimate of high risk. Considering extreme value theory of value in the above models has in most cases led to improved model performance. This means that it has moderately adjusted the estimates of the upper hand and the estimates of the.

Cites

No record.

References

No record.

Cite

APA: Copy

FALLAHPOUR, SAEED, & TABASI, HAMED. (2020). Estimation of Expected Shortfall Based on Conditional Extreme Value Theory Using Multifractal Model and Intraday Data in Tehran Stock Exchange. FINANCIAL RESEARCH, 22(1 ), 27-43. SID. https://sid.ir/paper/358815/en

Vancouver: Copy

FALLAHPOUR SAEED, TABASI HAMED. Estimation of Expected Shortfall Based on Conditional Extreme Value Theory Using Multifractal Model and Intraday Data in Tehran Stock Exchange. FINANCIAL RESEARCH[Internet]. 2020;22(1 ):27-43. Available from: https://sid.ir/paper/358815/en

IEEE: Copy

SAEED FALLAHPOUR, and HAMED TABASI, “Estimation of Expected Shortfall Based on Conditional Extreme Value Theory Using Multifractal Model and Intraday Data in Tehran Stock Exchange,” FINANCIAL RESEARCH, vol. 22, no. 1 , pp. 27–43, 2020, [Online]. Available: https://sid.ir/paper/358815/en

Related Journal Papers