The goal of this study is to test the accuracy of various mutual fund timing and selectivity models under a range of portfolio managerial skills and varying market conditions. Portfolio returns in a variety of skill environments are generated using a simulation procedure. The generated portfolio returns are based on the historical patterns and time series behavior of a market portfolio proxy and on a sample of mutual funds. The proposed timing and selectivity portfolio returns mimic the activities of actual mutual fund managers who possess varying degrees of skill. Using the constructed portfolio returns, various performance models are compared in terms of their power to detect timing and selectivity abilities, by means of an iterative simulation procedure. The frequency of errors in rejecting the null hypotheses of no market timing and no selectivity abilities shape the analyses between the models for power comparison. The results indicate that time varying beta models of Lockwood- Kadiyala and Bhattacharya-Pfleiderer rank highest in tests of both market timing and selectivity. The Jensen performance model achieves the best results in selectivity environments in which managers do not possess timing skill. The Henriksson-Merton model performs most highly in tests of market timing in which managers lack timing skill. The study also investigates the effects of heteroskedasticity on the performance models. The results of analysis before and after model correction for nonconstant error term variance (heteroskedasticity) for specific performance methodologies do not follow a consistent pattern. / Graduation date: 1992

In recent years, the Markov Regime-Switching model and the class of Archimedean copulas have been widely applied to a variety of finance-related fields. The Markov Regime-Switching model can reflect the reality that the underlying economy is changing over time. Archimedean copulas are one of the most popular classes of copulas because they have closed form expressions and have great flexibility in modeling different kinds of dependencies. In the thesis, we first consider a discrete-time risk process based on the compound binomial model with regime-switching. Some general recursive formulas of the expected penalty function have been obtained. The orderings of ruin probabilities are investigated. In particular, we show that if there exists a stochastic dominance relationship between random claims at different regimes, then we can order ruin probabilities under different initial regimes. Regarding capital allocation problems, which are important areas in finance and risk management, this thesis studies the problems of optimal allocation of policy limits and deductibles when the dependence structure among risks is modeled by an Archimedean copula. By employing the concept of arrangement increasing and stochastic dominance, useful qualitative results of the optimal allocations are obtained. Then we turn our attention to a new family of risk measures satisfying a set of proposed axioms, which includes the class of distortion risk measures with concave distortion functions. By minimizing the new risk measures, we consider the optimal allocation of policy limits and deductibles problems based on the assumption that for each risk there exists an indicator random variable which determines whether the risk occurs or not. Several sufficient conditions to order the optimal allocations are obtained using tools in stochastic dominance theory. / published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

Not available

Modelling and forecasting stock market volatility is a critical issue in various fields of finance and economics. Forecasting volatility in stock markets find extensive use in portfolio management, risk management and option pricing. The primary objective of this study was to describe the volatility in the Johannesburg Stock Exchange (JSE) index using univariate and multivariate GARCH models. We used daily log-returns of the JSE index over the period 6 June 1995 to 30 June 2012. In the univariate GARCH modelling, both asymmetric and symmetric GARCH models were employed. We investigated volatility in the market using the simple GARCH, GJR-GARCH, EGARCH and APARCH models assuming di erent distributional assumptions in the error terms. The study indicated that the volatility in the residuals and the leverage effect was present in the JSE index returns. Secondly, we explored the dynamics of the correlation between the JSE index, FTSE-100 and NASDAQ-100 index on the basis of weekly returns over the period 6 June 1995 to 30 June 2012. The DCC-GARCH (1,1) model was employed to study the correlation dynamics. These results suggested that the correlation between the JSE index and the other two indices varied over time. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.

This thesis presents various dynamic models of corporate decisions to address two main issues: investment distortions caused by debt financing and cash flow sensitivities. In the first chapter, four measures of investment distortion are computed. First, the effect of financing frictions is examined. The tax benefit of debt induces firms to increase their debt capacity and to invest beyond the first-best level on average. The cost of this investment distortion outweighs the tax benefit of debt. Second, Myers's (1977) debt overhang problem is examined in a dynamic framework. Debt overhang obtains on average, but not in low technology states. Third, there is no debt overhang problem in all technology states when debt is optimally put in place prior to the investment decision. Finally, the cost of choosing investment after the debt policy is examined. Equity claimants lose value by choosing to invest after their debt is optimally put in place because they do not consider the interaction between their investment choice and the debt financing conditions. The second chapter explores the impact of financial constraints on firms' cash flow sensitivities. In contrast to Fazzari, Hubbard, and Petersen (1988), cash flow sensitivities are found to be larger, rather than smaller, for unconstrained firms than for constrained firms. Then, why is investment sensitive to cash flow? In the two models examined in the second chapter, the underlying source of investment opportunities is highly correlated with cash flows. Investment may be sensitive to cash flow fluctuations simply because cash flows proxy for investment opportunities. This leaves two important questions. Can this chapter suggest a better measure of investment opportunities than Tobin's Q? Not a single measure for both the unconstrained and constrained firm models. Can this chapter suggest an easily observable measure of financial constraint? Yes: large and volatile dividend-to-income ratios.

No abstract available.

Numerical methods form an important part of the pricing of financial derivatives and especially in cases where there is no closed form analytical formula. We begin our work with an introduction of the mathematical tools needed in the pricing of financial derivatives. Then, we discuss the assumption of the log-normal returns on stock prices and the stochastic differential equations. These lay the foundation for the derivation of the Black Scholes differential equation, and various Black Scholes formulas are thus obtained. Then, the model is modified to cater for dividend paying stock and for the pricing of options on futures. Multi-period binomial model is very flexible even for the valuation of options that do not have a closed form analytical formula. We consider the pricing of vanilla options both on non dividend and dividend paying stocks. Then show that the model converges to the Black-Scholes value as we increase the number of steps. We discuss the Finite difference methods quite extensively with a focus on the Implicit and Crank-Nicolson methods, and apply these numerical techniques to the pricing of vanilla options. Finally, we compare the convergence of the multi-period binomial model, the Implicit and Crank Nicolson methods to the analytical Black Scholes price of the option. We conclude with the pricing of exotic options with special emphasis on path dependent options. Monte Carlo simulation technique is applied as this method is very versatile in cases where there is no closed form analytical formula. The method is slow and time consuming but very flexible even for multi dimensional problems.

No abstract available.

This thesis presents various dynamic models of corporate decisions to address two main issues: investment distortions caused by debt financing and cash flow sensitivities. In the first chapter, four measures of investment distortion are computed. First, the effect of financing frictions is examined. The tax benefit of debt induces firms to increase their debt capacity and to invest beyond the first-best level on average. The cost of this investment distortion outweighs the tax benefit of debt. Second, Myers's (1977) debt overhang problem is examined in a dynamic framework. Debt overhang obtains on average, but not in low technology states. Third, there is no debt overhang problem in all technology states when debt is optimally put in place prior to the investment decision. Finally, the cost of choosing investment after the debt policy is examined. Equity claimants lose value by choosing to invest after their debt is optimally put in place because they do not consider the interaction between their investment choice and the debt financing conditions. The second chapter explores the impact of financial constraints on firms' cash flow sensitivities. In contrast to Fazzari, Hubbard, and Petersen (1988), cash flow sensitivities are found to be larger, rather than smaller, for unconstrained firms than for constrained firms. Then, why is investment sensitive to cash flow? In the two models examined in the second chapter, the underlying source of investment opportunities is highly correlated with cash flows. Investment may be sensitive to cash flow fluctuations simply because cash flows proxy for investment opportunities. This leaves two important questions. Can this chapter suggest a better measure of investment opportunities than Tobin's Q? Not a single measure for both the unconstrained and constrained firm models. Can this chapter suggest an easily observable measure of financial constraint? Yes: large and volatile dividend-to-income ratios. / Business, Sauder School of / Graduate

A thesis submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand in fulfilment of the requirements for the degree of Master of Commerce (M.Com) in Finance, Johannesburg June 2017 / Traditional finance theory surrounding the risk-return relationship is underpinned by the CAPM which posits that a single risk factor, specifically market risk, is priced into asset returns. Even though it is a popular asset pricing model, the CAPM has been widely criticised due to its unrealistic assumptions and the APT was developed to address the CAPM’s weaknesses. The APT framework allows for a multitude of risk factors to be priced into asset returns; implying that it can be used to model returns using either macroeconomic or microeconomic factors. As such, the APT allows for non-traditional factors, such as investor sentiment, to be included. A macroeconomic APT framework was developed for nine countries using the variables outlined by Chen, Roll, and Ross (1986) and investor sentiment was measured by the FEARS index (Da, Engelberg, & Gao, 2015). Regression testing was used to determine whether FEARS is a statistically significant explanatory variable in the APT model for each country. The results show that investor sentiment is a statistically significant explanatory variable for market returns in five out of the nine countries examined. These results add to the existing APT literature as they show that investor sentiment has a significant explanatory role in explaining asset prices and their associated returns. The international nature of this study allows it to be extended by considering the role that volatility spill-over or the contagion effect would have on each model. / XL2018