Dynamic investment models with downside risk control

Mean-variance analysis has been broadly used in the theory and practice of portfolio management. However, the continuous analogy is not fully studied either academically or in practice. This thesis provides a similar efficient frontier to Markowitz (1952) and a general solution using martingale meth...

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Main Author: Zhao, Yonggan
Format: Others
Language:English
Published: 2009
Online Access:http://hdl.handle.net/2429/13517
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spelling ndltd-UBC-oai-circle.library.ubc.ca-2429-135172018-01-05T17:36:50Z Dynamic investment models with downside risk control Zhao, Yonggan Mean-variance analysis has been broadly used in the theory and practice of portfolio management. However, the continuous analogy is not fully studied either academically or in practice. This thesis provides a similar efficient frontier to Markowitz (1952) and a general solution using martingale method employed in Cox and Huang (1989). Comparisons between the expected utility approach and the mean-variance analysis have been made. Traditional utility maximization cannot be used for explicit risk control of downside losses. An adjusted investment objective function by the worst case outcome is incorporated in the investment model. The problem can be divided into two subproblems as in Cox and Huang (1989). Closed form solution is derived for geometric Brownian motion and HARA utility setting. An interesting result is that the investor's decision is governed by a single "security" - a call option on a dynamic mutual fund. A similar strategy, Risk Neutral Excess Return(RNER), to Portfolio Insurance is discussed. With geometric Brownian motion, the RNER strategy has a payoff structure similar to a straddle option strategy. Compare to the strategic asset allocation methods, such as Buy and Hold, Fixed Mix, and Portfolio Insurance , the new approach appears to be superior under a popular risk measure, Value at Risk(VaR). A new objective function is defined for applying stochastic programming to financial investment under uncertainty. Incomplete market conditions are considered in implementing this model. The risk neutral probability is fully studied using stochastic programming techniques. Business, Sauder School of Graduate 2009-10-01T21:45:34Z 2009-10-01T21:45:34Z 2000 2000-11 Text Thesis/Dissertation http://hdl.handle.net/2429/13517 eng For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. 9423158 bytes application/pdf
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language English
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description Mean-variance analysis has been broadly used in the theory and practice of portfolio management. However, the continuous analogy is not fully studied either academically or in practice. This thesis provides a similar efficient frontier to Markowitz (1952) and a general solution using martingale method employed in Cox and Huang (1989). Comparisons between the expected utility approach and the mean-variance analysis have been made. Traditional utility maximization cannot be used for explicit risk control of downside losses. An adjusted investment objective function by the worst case outcome is incorporated in the investment model. The problem can be divided into two subproblems as in Cox and Huang (1989). Closed form solution is derived for geometric Brownian motion and HARA utility setting. An interesting result is that the investor's decision is governed by a single "security" - a call option on a dynamic mutual fund. A similar strategy, Risk Neutral Excess Return(RNER), to Portfolio Insurance is discussed. With geometric Brownian motion, the RNER strategy has a payoff structure similar to a straddle option strategy. Compare to the strategic asset allocation methods, such as Buy and Hold, Fixed Mix, and Portfolio Insurance , the new approach appears to be superior under a popular risk measure, Value at Risk(VaR). A new objective function is defined for applying stochastic programming to financial investment under uncertainty. Incomplete market conditions are considered in implementing this model. The risk neutral probability is fully studied using stochastic programming techniques. === Business, Sauder School of === Graduate
author Zhao, Yonggan
spellingShingle Zhao, Yonggan
Dynamic investment models with downside risk control
author_facet Zhao, Yonggan
author_sort Zhao, Yonggan
title Dynamic investment models with downside risk control
title_short Dynamic investment models with downside risk control
title_full Dynamic investment models with downside risk control
title_fullStr Dynamic investment models with downside risk control
title_full_unstemmed Dynamic investment models with downside risk control
title_sort dynamic investment models with downside risk control
publishDate 2009
url http://hdl.handle.net/2429/13517
work_keys_str_mv AT zhaoyonggan dynamicinvestmentmodelswithdownsideriskcontrol
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