Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Comparison of GARCH-class Models and MIDAS Regression with Applications in Volatility Prediction and Value at Risk Estimation
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

We use GARCH(1,1), EGARCH and MIDAS regression to forecast weekly and monthly conditional variance of the OMXS30 equity index and USD/SEK exchange rate. Forecasts are compared with realized volatility and accuracy is evaluated using a Quasi-likelihood loss function and Diebold Mariano test. We estimate normal and t-distributed Value at Risk using forecasted conditional variances and evaluate these estimates using Likelihood Ratio tests for unconditional coverage and temporal independence. We show that MIDAS regression outperforms both GARCH-class models in forecast accuracy, while the difference between GARCH(1,1) and EGARCH varies between data and frequency. Findings suggest that GARCH-class models underestimate conditional variance and react slowly to shocks, producing temporally dependent Value at Risk exceptions for some data. The superiority of MIDAS regression in the variance forecasting problem has implications for option pricing and risk management in the financial sector.

Place, publisher, year, edition, pages
2014.
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:uu:diva-226092OAI: oai:DiVA.org:uu-226092DiVA: diva2:723840
Subject / course
Statistics
Supervisors
Examiners
Available from: 2014-06-13 Created: 2014-06-11 Last updated: 2014-06-13Bibliographically approved

Open Access in DiVA

A Comparison of GARCH-class Models and MIDAS Regression with Applications in Volatility Prediction and Value at Risk Estimation - Prepic, Unosson(1373 kB)1057 downloads
File information
File name FULLTEXT01.pdfFile size 1373 kBChecksum SHA-512
3139b0dba90e72c5cbfa859b50200198c503128662f15ad8dd8640a37a29552335369aa7a27815a7f067dce426e847f2ce8d14b9c02beb0186d3b1fdfc405339
Type fulltextMimetype application/pdf

By organisation
Department of Statistics
Social Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 1057 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 1967 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf