dc.contributor.author | Okwach, G O | |
dc.date.accessioned | 2013-05-12T06:32:27Z | |
dc.date.available | 2013-05-12T06:32:27Z | |
dc.date.issued | 2001-09 | |
dc.identifier.citation | Masters thesis University of Nairobi (2001) | en |
dc.identifier.uri | http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/22212 | |
dc.description.abstract | Managers are confronted with the need to continuously shift resources among competing
uses. The interest is to ensure allocation to the best venture. A good risk measurement
tool affords meaningful estimation of exposure of earnings to lose among competing
venture hence facilitating strategic resource allocation. A proper risk measurement tool
also aids in evaluation of management performance and competencies- indirectly
providing an 'index on efficient resource management
Modern portfolio theory suggests that the risk in a portfolio can be proxied by the
portfolio standard deviation. This means the latter is all that one needs to;
i) encapsulate all the information about risk that is relevant and
ii) construct risk- based rules for optimal risk "management" decisions.
However, in reality, managers think of risk in terms of dollars of loss, not deviations.
Standard deviation is therefore not intuitive.
Value at Risk methodologies present information about the distribution of possible future
losses on a portfolio. From such distribution, the loss exposure of a portfolio at any time
can be calculated and used by management to make decisions on the propriety of
portfolio composition. This study attempted to test the predictive ability of one such
model among Kenyan financial Intermediaries and in the process to also establish the
methods used by those institutions to determine the timing for portfolio composition
changes.
The study found that internally developed models are the most popular means by which
management decides on portfolio composition. These models are unstructured and
change from time to time. The methods applied are tailored to conform to the regulatory
framework within which these institutions operate.
Value at Risk models are little known among Financial Intermediaries in Kenya. The
study found Closed end VaR model to be a good predictor of portfolio composition
changes among financial intermediaries in Kenya. Most companies however tend to
continue applying own tailor made approaches which tend to be rule of thumb based in
determining portfolio composition | en |
dc.language.iso | en | en |
dc.publisher | University of Nairobi. | en |
dc.title | The predictive ability of closed-end value-at-risk model on changes to portfolio composition for selected investment intermediaries in Kenya. | en |
dc.type | Thesis | en |
local.publisher | School of Business Studies | en |