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Essay / Research Paper Abstract
This 36 page paper considers the use of stochastic modelling in the determination of asset allocation. The paper considers multi-stage stochastic programming and stochastic dynamic programming by comparing this to other models that may be used in assessing the contents of investment portfolios. Other models considered include models with their origins in mean variance theory leading to CAPM, efficient market hypothesis and the Warren Buffet method. The bibliography cites 29 sources.
Page Count:
36 pages (~225 words per page)
File: TS14_TEstochastic.rtf
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Unformatted sample text from the term paper:
Dynamic Programming 38 5. CONCLUSION 39 Figure 1 Risk and Reward Graph 5 Figure 2 Optimised Risk and Reward 10 Figure 3 The introduction of a new stock into the tangency portfolio 17
1. Introduction Asset allocations decision can be problematic at best. The decision of which classes of assets should be bought, sold and held in an investment, whether
it is a single investors portfolio or a larger insurance fund, will be critical in the performance of the fund. The ability to determine what is the best mix of
assets for any give risk and reward equation. Investors and analysts have long sought out tools that can help them identify the way in which they should invest in assets
classes and individual assets. Numerous studies have taken place to assess different approaches to investment when determine what assets or asset classes should be held. In assessing asset allocations
there are usually two main approaches studied and compared; Markowitz mean-variance model and the use of stochastic optimization. The first is a static model the second is more dynamic. However
these are not the only models that have been developed and are utilised. Stochastic optimization is often favoured as the best approaching, being one that that is more dynamic
and flexible, suitable as a tool for analyzing decision problems under uncertainty. The model is gaining popularity, there are also several variations of the model, such as the scenario tree
model and the simulated path model. This paper is going to argue that the best tool to aid with asset allocation is the use of stochastic is superior to other
models that have been developed and is able to deal with the reality of asset allocation allowing for dynamic market conditions more efficiently than alternatives. To examine the model
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