Previous work on the empirical distribution of security returns has found that equity returns are not normally distributed. These findings have brought the applicability of certain asset allocation and pricing frameworks into question. This study examines whether the removal of a priori macro-outliers and micro-outliers leads to improved fits to the Gaussian distribution for single-listed equities on the Johannesburg Stock Exchange (JSE). Single-listed equities refer to stocks (i) listed on the JSE Main Board over the period covered in this study, (ii) that comprise of the exchange’s largest 100 stocks by market capitalisation, and (iii) have been determined, by comparing American Depository Receipt (ADR) trading volume to JSE trading volume, to be mainly exposed to the South African market. Regarding the predetermined outliers, the study categorises macro-outliers as days related to predictable market announcements which are US nonfarm payrolls announcement days. Similarly, micro-outliers are classified as days linked to predictable sector-specific and firm-specific news, which are sectoral announcement, and company earnings announcement days, respectively. The study aims to contribute to the empirical and theoretical literature on the distributional properties of South African equity returns. This study makes use of a filter to narrow the sample of stocks for empirical investigation over the period from 1 January 2016 to 31 December 2017, and analyses daily stock returns on a 65-day rolling basis. Using only those equities, an evaluation of the goodness-of-fit methodology is conducted using graphical methods, and statistical goodness-of-fit tests sorted into (i) empirical distribution function, (ii) regression and correlation, and (iii) moment tests. It is found that the majority of the data exhibits significant departures from normality in empirical distribution function, and regression and correlation tests. The results were statistically significant at three confidence levels. However, in the case of moment tests, the results show a clear divergence between the methods. It is further demonstrated that while the daily stock returns have improved fits to the normal distribution, they remain predominantly positively-skewed and thick-tailed even after the removal of the a priori outliers. On this basis, it is argued that some downside risk measures, and asset allocation frameworks may not be applicable in the South African context.

The accuracy of the Black and Scholes (1973) delta and vega neutral portfolio for a vanilla option was compared to a benchmark set by the Heston (1993) model in a stochastic volatility environment. The Black-Scholes portfolio was implemented using a fixed volatility and by implying volatility from the market. Additionally, a portfolio based on the Dupire (1994) local volatility model was also compared. It was found that a portfolio consisting of two short maturity options with matching maturities was best hedged by the Black-Scholes model when using implied volatility. This result was not maintained when the two options had mismatching maturities as the proportional differences in the vegas no longer cancelled. Further examination was completed on the type of financial instruments used to hedge volatility, comparing portfolios that consisted of an additional option and a variance swap to offset any vega. It was found that both hedged the option well, with similar accuracies.

The thesis investigates the exogenous maturity vintage model (EMV) as a framework for achieving unification in consumer credit risk analysis. We explore how the EMV model can be used in origination modelling, impairment analysis, capital analysis, stress-testing and in the assessment of economic value. The thesis is segmented into five themes. The first theme addresses some of the theoretical challenges of the standard EMV model – namely, the identifiability problem and the forecasting of the components of the model in predictive applications. We extend the model beyond the three time dimensions by introducing a behavioural dimension. This allows the model to produce loan-specific estimates of default risk. By replacing the vintage component with either an application risk or a behavioural risk dimension, the model resolves the identifiability problem inherent in the standard model. We show that the same model can be used interchangeably to produce a point-in-time probability forecast, by fitting a time series regression for the exogenous component, and a through-the-cycle probability forecast, by omitting the exogenous component. We investigate the use of the model for regulatory capital and stress-testing under Basel III, as well as impairment provisioning under IFRS 9. We show that when a Gaussian link function is used the portfolio loss follows a Vašíček distribution. Furthermore, the asset correlation coefficient (as defined under Basel III) is shown to be a function of the level of systemic risk (which is measured by the variance of the exogenous component) and the extent to which the systemic risk can be modelled (which is measured by the coefficient of determination of the regression model for the exogenous component). The second theme addresses the problem of deriving a portfolio loss distribution from a loan-level model for loss. In most models (including the Basel-Vašíček regimes), this is done by assuming that the portfolio is infinitely large – resulting in a loss distribution that ignores diversifiable risk. We thus show that, holding all risk parameters constant, this assumption leads to an understatement of the level of risk within a portfolio – particularly for small portfolios. To overcome this weakness, we derive formulae that can be used to partition the portfolio risk into risk that is diversifiable and risk that is systemic. Using these formulae, we derive a loss distribution that better-represents losses under portfolios of all sizes. The third theme is concerned with two separate issues: (a) the problem of model selection in credit risk and (b) the problem of how to accurately measure probability of insolvency in a credit portfolio. To address the first problem, we use the EMV model to study the theoretical properties of the Gini statistic for default risk in a portfolio of loans and derive a formula that estimates the Gini statistic directly from the model parameters. We then show that the formulae derived to estimate the Gini statistic can be used to study the probability of insolvency. To do this, we first show that when capital requirements are determined to target a specific probability of solvency on a through-the-cycle basis, the point-in-time probability of insolvency can be considerably different from the through-the-cycle probability of insolvency – thus posing a challenge from a risk management perspective. We show that the extent of this challenge will be greater for more cyclical loan portfolios. We then show that the formula derived for the Gini statistic can be used to measure the extent of the point-in-time insolvency risk posed by using a through-the-cycle capital regime. The fourth theme considers the problem of survival modelling with time varying covariates. We propose an extension to the Cox regression model, allowing the inclusion of time-varying macroeconomic variables as covariates. The model is specifically applied to estimate the probability of default in a loan portfolio, where the experience is decomposed the experience into three dimensions: (a) a survival time dimension; (b) a behavioural risk dimension; and (c) calendar time dimension. In this regard, the model can also be viewed as an extension of the EMV model – adding a survival time dimension. A model is built for each dimension: (a) the survival time dimension is modelled by a baseline hazard curve; (b) the behavioural risk dimension is modelled by a behavioural risk index; and (c) the calendar time dimension is modelled by a macroeconomic risk index. The model lends itself to application in modelling probability of default under the IFRS 9 regime, where it can produce estimates of probability of default over variable time horizons, while accounting for time-varying macroeconomic variables. However, the model also has a broader scope of application beyond the domains of credit risk and banking. In the fifth and final theme, we introduce the concept of embedded value to a banking context. In longterm insurance, embedded value relates to the expected economic value (to shareholders) of a book of insurance contracts and is used for appraising insurance companies and measuring management's performance. We derive formulae for estimating the embedded value of a portfolio of loans, which we show to be a function of: (a) the spread between the rate charged to the borrower and the cost of funding; (b) the tenure of the loan; and (c) the level of credit risk inherent in the loan. We also show how economic value can be attributed between profits from maturity transformation and profits from credit and liquidity margin. We derive formulae that can be used to analyse the change in embedded value throughout the life of a loan. By modelling the credit loss component of embedded value, we derive a distribution for the economic value of a book of business. The literary contributions made by the thesis are of practical significance. The thesis offers a way for banks and regulators to accurately estimate the value of the asset correlation coefficient in a manner that controls for portfolio size and intertemporal heterogeneity. This will lead to improved precision in determining capital adequacy – particularly for institutions operating in uncertain environments and those operating small credit portfolios – ultimately enhancing the integrity of the financial system. The thesis also offers tools to help bank management appraise the financial performance of their businesses and measure the value created for shareholders.

The paper studies the life cycle optimal consumption-investment problem under a liquidity constraint (the liquid wealth process never becomes negative). For Cobb-Douglas utility, we first derive closed-form expressions for optimal consumption and investment strategy using a stopping time approach and then extend this framework to deal with the fixed leisure choice case. We also pose and solve three alternative models of optimal consumption, leisure and investment with various liquidity constraints. In addition, we obtain analytical comparative statics. We examine whether the cohort effects matter with the presence of liquidity constraints. In particular, we identify individuals who experienced low stock market returns are less willing to invest in equities and express more risk aversion. Finally, we analyze economic cost of the liquidity constraint in terms of certainty equivalent. Implications of liquidity constraints for optimal policies differ considerably from what are shown in the existing literature without liquidity constraints.

Includes bibliographical references. / The aim of this thesis is to explain the cross-section of International Classification Benchmark (ICB) level 4 (sector) index returns. A worldwide study of 48 developed and emerging countries is conducted, considering up to 38 sector indices per country. In cluster and factor analyses of the sector returns all the developed markets are found to cluster together, as are the emerging markets, suggesting diversificationary benefits from investing across the two. The one-month-ahead return forecasting power of 35 sector-specific attributes is investigated over an in-sample period from 31 January 1995 to 31 December 2001 and an out-sample period from 31 January 2002 to 31 December 2005. The data is adjusted for look-ahead bias, outliers, influential observations and non-uniformity across markets. Monthly sector returns are cross-sectionally regressed on the attributes in a similar fashion to Fama and MacBeth (1973). Sector returns are considered both before and after risk adjustment with the Capital Asset Pricing Model (CAPM), the Arbitrage Pricing Theory (APT) model and Solnik's (2000) version of the International CAPM (ICAPM). The ICAPM is found to be the best performing model but, in general, the evidence does not support covariance-based models of asset pricing. Nine attributes are found to be significant and robust over the two sample periods namely cash earnings per share to price (CP), dividend yield (DY), cash earnings to book value (CB), 6 and 12-month growth in cash earnings, to price (C-6P & C-12P), 12 and 24-month growth in dividends, to price (D-12P & D-24P), the payout ratio (PO) and 12-month prior return (MOM-12). All the significant attributes from the univariate regression tests are found to payoff consistently in the positive direction when tested with the nonparametric Sign Test. Nine of the significant attributes namely book value per share to price (BP), dividend yield (DY), earnings yield (EY), 6-month growth in cash earnings, to price (C-6P), cash earnings to book value (CB), 24-month growth in dividends, to price (D-24P), 24-month growth in earnings, to price (E-24P), 12-month and 18-month prior return (MOM-12 & MOM-18) are also found to have significantly low frequencies of changes in payoff direction when assessed with the nonparametric Runs Test. Seven style timing models are developed, all of which produce significantly accurate payoff direction forecasts for most of the significant attributes. The timing models are however generally inaccurate in forecasting the magnitude of the payoffs. Very little seasonality is observed in the payoffs to the significant attributes. Two sets of seven 'stepwise optimal' and 'control' multivariate models are constructed from the significant univariate in-sample attributes in order to forecast the payoffs to the factors in a controlled multifactor setting. The stepwise optimal models are derived from a stepwise procedure, whilst the 'control' models comprise all the attributes which are found to be significant in one or more of the 'optimal' models. The forecasting power of the all the models is found to be below an exploitable level; of the 'control' models the single exponential smoothing model is the most accurate outsample performer. Weighted Least Squares (WLS) models are used to allow for the possibility of heteroskedasticity, which may exist in the cross-section of worldwide sector returns. The WLS models are ineffective in improving forecasting power when the inverse of the 12-month rolling standard deviation of the residuals is used as the weight series.

The objective of this dissertation is to develop and test new theoretical and empirical pricing models for assets such as American-styled derivatives, exotic (non-standard) hybrid debts and oil-related securities. In Chapter 1, we develop a new approximation scheme for the price and exercise policy of American options. The scheme is based on Hermite polynomial expansions of the transition density of the underlying asset dynamics and the early exercise premium representation of the American option price. The advantages of the proposed approach are threefold. First, our approach does not require the transition density and characteristic functions of the underlying asset dynamics to be attainable in closed form. Second, our approach is fast and accurate, while the prices and exercise policy can be jointly produced. Third, our approach has a wide range of applications. We show theoretically that the proposed approximations of the price and optimal exercise boundary converge to the true ones. A efficiency study between popular methods and the presented method is constructed. We also provide a numerical method based on a step function to implement our proposed approach. Applications to nonlinear mean-reverting models, double mean-reverting models, Merton’s and Kou’s jump-diffusion models are discussed. In Chapter 2, we focus on the pricing of one specific asset called contingent convertible bonds (CoCos). CoCos become popular since late 2000s due to the change of regulations in the banking sectors and are viewed as important instruments to fulfill regulatory capitals. We propose a valuation approach for CoCo based on its issuing bank’s bad debt ratio, which is commonly accepted as an indicator of the bank’s current solvency and triggers the default of the CoCo as soon as it breaches some predetermined threshold. We formulate models for the bank’s bad debt ratio and stock price using a jump-diffusion structure with correlated jump risk, which takes into account the typical negative influence of the bad debt ratio on the share price. Both write-down and equity-convertible CoCos are considered, and for the latter we also propose a class of new power mechanisms of conversion that generalize traditional conversion ratios while still remaining analytically tractable. A novel computational algorithm is also proposed. A set of valuation formulas are derived for the CoCos in semi-closed form, and their performance is further illustrated with a case study. In Chapter 3, I develop an empirical framework to provide a precursory analysis on the nexus between prices of oil-related securities, Covid-19 and risk neutral higher moments (RNM). Using daily data of oil future options, I calculate the option-implied RNM and moment contract prices. I then conduct regression analysis between moment prices, daily Covid-19 cases, oil returns and oil future option returns, together with a series of other regressors. Major findings are: 1) the spread of Covid-19 made the risk-neutral skewness more negative, implying an increase in risk aversion in the oil market; 2) return predictability of RNMs increased during the period when the pandemic was severe; and 3) the structure of oil option prices recovers as vaccination popularizes. / 2023-09-22T00:00:00Z

I examine two different types of market data. First, I examine how distress risk is priced. Previous literature finds mixed results when examining if distress risk is priced in the cross section of returns, depending on whether firm specific or market-wide distress risk proxies are used. We use factor mimicking portfolios to create systematic distress risk factors from idiosyncratic variables. We find that distress risk is priced in the cross section of returns when considered as a systematic risk. We then use a Daniel and Titman (1997) style test to determine if positive returns associated with the loadings on the distress factors are best represented as systematic risk factors or shared characteristics but do not find consistent evidence in support of either theory. Second, I examine how goodwill impairment write-offs are priced. Prior studies find a negative stock price reaction after goodwill impairment write-offs both in the short term and in the long term. In 2002 the FASB rules for accounting for goodwill changed. We examine data from after the rule changes and find that investors continue to perceive goodwill write-offs as negative events in the short term, but contrary to previous studies, we find that investors perceive goodwill write-offs as positive news in the long term. We find that the overall firm performance improves significantly post event. However, firm operating performance only slightly improves after the write-off. The overall firm performance improvements are due to decreased non-recurring charges in the years subsequent to the write-off. / A Dissertation submitted to the Department of Finance in partial fulfillment of the Doctor of Philosophy. / Spring Semester, 2015. / March 19, 2015. / asset pricing, distress risk, goodwill, impairments, investments, stock prices / Includes bibliographical references. / David Peterson, Professor Directing Dissertation; Thomas Zuehlke, University Representative; Irena Hutton, Committee Member; Don Autore, Committee Member.

This dissertation studies the role of cultural holidays in equity pricing. In the first essay, we study individual stock returns in eleven major international markets that celebrate six cultural New Year holidays not on January 1st. Our results show that stock markets tend to outperform in days surrounding the cultural New Year. After controlling for firm characteristics, an average stock earns a one to two percentage point higher abnormal return in days surrounding the cultural New Year's day relative to other non-January times of the year. Our further evidence suggests that a positive holiday mood in conjunction with cash infusions prior to the cultural New Year produces elevated stock prices, particularly among the stocks most preferred and traded by individual investors. In the second essay, we find that investors react more favorably to share repurchases, SEOs, acquisitions, and earnings announcements when the announcement is made immediately prior to or on a holiday (i.e. pre-holiday trading days). Corporate events that typically trigger stock price declines are associated with abnormal reactions that are 22 to 49 basis points less negative on pre-holiday trading days, and events that usually result in stock price increases are associated with reactions that are 14 to 78 basis points more positive on these days. The results are not explained by a pre-holiday up market, monthly investor sentiment, short selling, investor limited attention, or adverse selection of firm announcements. Using Gallup survey data, we provide evidence that people are happier and less worried immediately prior to holidays, suggesting that our findings could be explained by an optimistic pre-holiday investor mood. Our study contributes to the literature on the pre-holiday effect by providing novel evidence that investor anticipation of holidays elevates announcement reactions to corporate events. / A Dissertation submitted to the Department of Finance in partial fulfillment of the Doctor of Philosophy. / Spring Semester, 2015. / February 26, 2015. / Behavioral finance, Holidays, Investor mood / Includes bibliographical references. / Danling Jiang, Professor Directing Dissertation; Thomas Zuehlke, University Representative; Don Autore, Committee Member; David Peterson, Committee Member.

This dissertation examines two underdeveloped topics in the field of corporate finance. In the first chapter, I detail the impact of expectations on the performance of firms under the leadership of new CEOs. I seek to answer the heretofore untested question of whether greater pressure motivates new CEOs to succeed, encourages them to engage in manipulative behaviors, or both. I show that new CEOs with greater expectations are significantly more likely to report superior achievement. However, after possible manipulation is accounted for, this superiority is reduced to insignificant levels. I conclude that while a small motivational effect of expectations may exist, spurring some new CEOs to perform, the strongest impact of heightened expectations for new CEOs is an increased likelihood to artificially inflate performance measures for the sake of appearance. In the second chapter, I question whether the market's response to the announcement of significantly increased dividends depends on the future free cash flows, realized by the firm, which may prove to be susceptible to agency costs. I consider the market's reaction to the announcement of substantial dividend hikes and find this reaction is not tied to the future free cash flows of the firm; however, I also find that the reaction is strongly linked to the excess cash balance of the firm in the year of the dividend increase. I contend the market attempts to consider agency costs when evaluating new dividends, but in doing so it fails to look beyond the firm's current cash situation. / A Dissertation submitted to the Department of Finance in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester, 2009. / February 25, 2009. / Dividend Sources, Executive Motivation / Includes bibliographical references. / Xufeng Niu, Outside Committee Member; Yingmei Cheng, Committee Member; Bruce Haslem, Committee Member.

Includes abstract. / Includes bibliographical references. / The success of the Fama and French 3-factor model in explaining empirical anomalies of the Capital Asset Pricing Model (CAPM) suggests that style investing which places portfolios out-of-sync with the broad market has the potential to generate significant alpha. Since momentum abnormal return is the only anomaly that is not explained by the 3-factor model, it could well be the third style-based factor in addition to the size and the value factors to complete the model. With the goal of searching for practical mean-variance efficient allocation mechanisms in the global capital market, this study develops and examines the long-only, long-short leverage and market neutral strategies from the global size, value and momentum proxies along with the Morgan Stanley Capital International World Index over the examination period, 1 January 1991 to 31 December 2008.