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Title: Risk measure changes and portfolio optimization theory
Author: Sokolova-Maria, Maria
ISNI:       0000 0004 2677 0513
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2009
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The thesis introduces methodology to imply risk measures from market prices in comparison to the traditional portfolio theory approach, where a predetermined utility function is typically used. Minimum entropy optimization is used to calibrate the risk aversion function. In addition a minimum entropy calibration problem with increasing risk aversion function is discussed. As the risk measure should look at a wider spectrum of percentile levels in order to acquire the risk of all portfolio's assets spectral risk measures are used. Presentation of all recently proposed risk measures, their properties and relations are given. Portfolio optimization algorithm for CVaR and spectral risk measures using linear programming is described. Empirical results are provided to test and support the theory. It is shown that each investor's risk measure is unique to that investor and the risk aversion function is sensitive to portfolio selection, which reveals risk preferences. The impact of portfolio optimization to capital allocation is shown.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available