MSc.MF Theses and Dissertations (2018)
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- ItemExotic derivatives pricing using copula-based martingale approach(Strathmore University, 2018) Muganda, Brian WesleyThis study examines the pricing of bivariate exotic derivatives, namely: capped spread option and bivariate digital options, using martingale approach and pair copulae formulations. Pair copulae is used to capture the joint distribution of asset price process and varying dependence structure rather than the univariate marginal distribution used in pricing univariate options. Unique payoff conditions for these exotic options are developed and the prices of these exotic options are obtained under the best fitting pair copulae. We then assess the sensitivity of the exotic option prices to the copula parameter, by formulating a `dependence delta' and `dependence gamma' formula obtained by application of chain rule de-composition to the copula derivative to have h-function and density function representation. Data from 2012 to 2018 from the NYSE of Equity ETFs and Bond ETFs of Frontier Markets, Emerging Market and Developed Markets to construct 10 pair combination of Equity and Bond ETFs as underlyings for the bivariate exotic options. The findings reveal that the t-copula captures best the dependence between the 10 pair combinations of underlyings. The prices of the bivariate exotic options are affected by the strength of the dependence of underlyings. Emerging and Developed market equity ETFs combination are more sensitive to changes in copula parameter. However, emerging market equity ETF and Developed market bond ETF exhibit lower downside dependence and have lower dependence delta. Dependence gamma is generally of similar strength and signage as the dependence delta.
- ItemEfficiency of the markov regime switching GARCH Model in modelling volatility for tea prices(Strathmore University, 2018) Maiyo, Mathew KiplimoThis study examines the ability of the Markov Regime Switching GARCH model, in comparison with the univariete GARCH models, in modelling and forecasting price volatility of the tea traded at the Mombasa Tea Auction within some time horizon. The study uses weekly data, from 2010 to 2017, to analysis regime switching in volatility and provides an in-sample and out-of-sample forecast. Volatility regime switching is first modelled with a Markov switching framework. In-sample and out-of-sample forecasts of volatility using competing MRS-GARCH models and the single regimes GARCH models are then provided. Comparison of in-sample forecast is done on the basis of goodness-of-fit and the comparison of the out-of-sample forecasts is done on the basis of forecast accuracy, using the statistical loss function. The results show that the MRS-GARCH models can remove the high persistence of GARCH models. This shows the priority of MRS-GARCH models and provides evidence of regime clustering. In out-of-sample forecast perfomance, the MRS-GARCH models were better than the single regime GARCH model. However, this superioirity fades for longer time horizon.
- ItemMeasuring and evaluating factors of dynamic term structure models for value-at-risk estimation in the Kenyan market(Strathmore University, 2018) Kanda, Felix KipkorirThe growth of the Kenyan fixed income market and the growing need for investors to diversify the risk in the portfolios has driven the need to quantify the risk associated with the fixed income assets. The measures that are commonly used to estimate bond risk are duration and convexity. However, these measures do not sufficiently assess the risk in fixed incomes. The risk associated with the yield curve illustrates how a portfolio will react to different exposures based on how the yield curve shifts. In this research, we will seek to model the yield curves for the Kenyan market using the dynamic factor models, namely, Nelson-Siegel and Svensson models. We will estimate the factors for both models and seek to establish the distributions of the estimated factors. We will then seek to use the estimated factors from both models to generate the vector of expected bond yields and the covariance matrix that will be used to measure the Value-at-Risk. The results of this research will be used to seek a parametric method of measuring risk in a fixed income in an illiquid market and check whether the estimated factors are good fits to be used in the parametric model.
- ItemDetermination of optimal public debt ceiling for Kenya using stochastic control(Strathmore University, 2018) Kithinji, MillicentPublic debt is a key economic variable. It is the totality of public and publicly guaranteed debt owed by any level of government to either citizens or foreigners or both. Due to recent debt crises in developed countries such as Portugal, Italy, Ireland, Greece and Spain, debt control has become a key important fiscal policy of every government. In this study, we applied a formula proposed by (Cadenillas and Aguilar, 2015) to find out the optimal public debt ceiling for Kenya. We made modification to subjective variables in the explicit formula and used the formula to find the optimal public debt ceiling for Kenya. We illustrate that it is prudent for that government to use a fiscal policy that maintains the debt ratio under an optimal debt ceiling.
- ItemThe Effect of the fluctuation of the Chinese Yuan on the returns of stocks traded in the Kenyan, Ugandan and Tanzanian markets(Strathmore University, 2018) Kibathi, Leonie NjeriThis paper investigated the relationship between Kenya, Tanzanian and Ugandan ex-change rates and the returns of three stocks traded in all three markets. The exchange rates analyzed were from the three countries versus the Chinese Yuan. The data was maintained at weekly intervals and the time period was from January 2012 to December 2017. In this study, both the exchange rate and the stock returns data were found to be non-normally distributed. A unit root test (Augmented Dickey-Fuller) found that both time series were stationary at level form. A test into the causal relationship between the two variables by the Granger Causality test showed that there was a unidirectional relationship between stock returns and the exchange rates that run from the stock returns to the exchange rates. Understanding the flow of influence between exchange rates and stock market returns is essential as the two variables have become important aspects in trading markets. The information about this relationship between stock market returns and exchange rates would help investors to invest prudently by reducing their exposure to risk.
- ItemA Quantitative analysis of the Kenyan students' loan default(Strathmore University, 2018) Kamau, Pauline NyathiraHigher education capacity, quality, and availability has driven more countries to turn to student loan schemes in order to assist students whose families are unable to meet their university costs. Ideally, all students seeking university education should be able to access these loans. It is also expected that student loan applicants pay back the entire loan in the stipulated time frame to allow other needy students joining university to utilize the repaid amounts. In this study, we seek to perform a quantitative analysis of loan applications by computing the probability of default of a given applicant using the qualitative information provided in the application forms. We apply multiple logistic regression with the binomial nominal variable defined either as defaulter or re-payer. Further, we treated different factors affecting default probability of the student as independent variables. The main objective was to find out the effect that the independent variables have on the dependent variable. We then validated the resulting model by comparing its results to observed data from the Kenyan Higher Education Loans Board. Results show the amount of loan reimbursed as the main factor affecting default. This can be an eye-opener for policy makers in their effort to mitigate non-repayment.
- ItemValuation of a locational spread option: the case of tomatoes in Nairobi and Mombasa Counties in Kenya(Strathmore University, 2018) Kimathi, Kenneth GitongaLocational Spread Options are financial instruments that can be used by traders wishing to purchase but not physically acquire produce; to hedge their risks, and / or to take speculative positions, based on their knowledge of market dynamics. In this study, we analyze historical tomato price data in Nairobi & Mombasa counties in Kenya; and observe that the Ornstein Uhlenbeck process best captures the price dynamics due to the mean reverting characteristics noted in the deseasonalized price data. We then derive pricing equations and estimate the model parameters via the use of Maximum Likelihood Estimation. Finally, we use these parameter estimations to perform Monte Carlo simulations, using the antithetic variate variance reduction technique to obtain the option price.
- ItemBad beta, good beta and stochastic volatility in an inter-temporal asset pricing model for the Kenyan stock market(Strathmore University, 2018) Kimundi, Gillian NdukuThe study seeks to investigate whether bad beta (sensitivity to cash-ow news), good beta (sensitivity to discount rate news) and volatility news are significantly priced in the Kenyan stock market. A comparison of the 3 models is done: 2-beta pricing model (with cash-ow news and discount rate news as risk factors), a 3- beta model (including volatility news) and a 4-beta model (including covariation risk in cash-ow and discount rate news). The findings from the study suggest that news terms related to cash flows, discount rates, volatility and the covariation of cash-ow news and discount rate news are all significantly priced in the Kenyan Market. There is evidence that Kenyan investors are highly risk averse, more so towards cash-ow news, than they are to discount rate news. Similarly, the premium charged for volatility news is just as high as that attached to cash flow news. Investors also attach a significant but relatively smaller premium to the risk due to covariation between cash-ow news and discount rate news.
- ItemFrontier stock market linkages: an African perspective(Strathmore University, 2018) Onyango, Christine AmandaVolatility modelling in the multivariate case is becoming an important area of study as the world becomes increasingly more integrated and as barriers to entry in frontier markets come down. Understanding how frontier markets in the African region behave in contrast to those in developed markets is vital in driving portfolio allocation decisions as well as regulatory interventions.In this study we investigate the co-movements of the stock indices of four African countries, Nigeria, Morocco, Mauritius and Kenya using various multi-variate volatility models in relation to those of South Africa and the United Kingdom. We also fit a Kalman filter to the data set and examine the goodness of fit of the two approaches. For the Multi-variate models we fit an Exponentially Weighted Moving Average (EWMA) model, two specifications of Dynamic Conditional Correlation (DCC) models as well as a multivariate volatility model based on Cholesky Decomposition. We use a dynamic linear specification of the Kalman filter to allow for time-varying variances, and generate forecasts. Empirical results show that the diagnostic tests with upper tail trimming reject the EWMA model while both specifications of the DCC model as well as a multivariate model based on Cholesky decomposition is found to be adequate. Kalman filters also provide adequate modelling for each return series on the basis of assessment of residuals.