Stochastic modelling of random variables with an application in financial risk management
The problem of determining whether or not a theoretical model is an accurate representation of an empirically observed phenomenon is one of the most challenging in the empirical scientific investigation. The following study explores the problem of stochastic model validation. Special attention is devoted to the unusual two-peaked shape of the empirically observed distributions of the conditional on realised volatility financial returns. The application of statistical hypothesis testing and simulation techniques leads to the conclusion that the conditional on realised volatility returns are distributed with a specific previously undocumented distribution. The probability density that represents this distribution is derived, characterised and applied for validation of the financial model.
Year of publication: |
2003
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Authors: | Moldovan, Max |
Publisher: |
Queensland University of Technology |
Subject: | Keywords: model validation | realised volatility | high-frequency data | two-component effect | modelling of random variables | simple test for normality | change-point detection | small sample | end-of-sample problem |
Saved in:
freely available
Type of publication: | Book / Working Paper |
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Type of publication (narrower categories): | Thesis |
Notes: | Moldovan, Max (2003) Stochastic modelling of random variables with an application in financial risk management. Masters by Research thesis, Queensland University of Technology. |
Source: | BASE |
Persistent link: https://www.econbiz.de/10009438314
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