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Asset allocation in wealth management using stochastic modelsRoyden-Turner, Stuart Jack 02 1900 (has links)
Modern financial asset pricing theory is a broad, and at times, complex field. The literature review in this study covers many of the asset pricing techniques including factor models, random walk models, correlation models, Bayesian methods, autoregressive models, moment-matching models, stochastic jumps and mean reversion models. An important topic in finance is portfolio opti-misation with respect to risk and reward such as the mean variance optimisation introduced by Markowitz (1952). This study covers optimisation techniques such as single period mean variance optimisation, optimisation with risk aversion, multi-period stochastic programs, two-fund separa-
tion theory, downside optimisation techniques and multi-period optimisation such as the Bellman dynamic programming model.
The question asked in this study is, in the context of investing for South African individuals
in a multi-asset portfolio, whether an active investment strategy is signi cantly di erent from
a passive investment strategy. The passive strategy is built using stochastic programming with
moment matching methods for non-Gaussian asset class distributions. The strategy is optimised
in a framework using a downside risk metric, the conditional variance at risk. The active strategy
is built with forward forecasts for asset classes using the time-varying transitional-probability
Markov regime switching model. The active portfolio is finalised by a dynamic optimisation using a two-stage stochastic programme with recourse, which is solved as a large linear program. A hypothesis test is used to establish whether the results of two strategies are statistically different. The performance of the strategies are also reviewed relative to multi-asset peer rankings. Lastly, we consider whether the findings reveal information on the degree of effi ciency in the market place for multi-asset investments for the South African investor. / Operations Management / M. Sc. (Operations Research)
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