This dissertation presents four essays. The first chapter builds a real-options, term structure model of the firm incorporating stochastic volatility and endogenous default to shed new light on the value premium, financial distress, momentum, and credit spread puzzles. The paper uses recently developed methodologies based on asymptotic expansions to solve the model. The second chapter, coauthored with Adam Guren, presents a model that shows how foreclosures can exacerbate a housing bust and delay the housing market's recovery. Quantitatively, the model successfully explains aggregate and retail price declines, the foreclosure share of volume, and the number of foreclosures both nationwide and across MSAs. The third and fourth chapters, coauthored with Stephen W. Salant and Jason Winfree, discuss the economics of untraceable experience goods in a variety of settings. The third chapter drops the "small country" assumption in the trade literature on collective reputation and shows how large exporters like China can address severe problems assuring the quality of its exports. The fourth chapter demonstrates how regulations in the formal sector of developing countries can lead to a quality gap between formal and informal sector goods. It moreover investigates how changes in regulation affect quality, price, aggregate production, and the number of firms in each sector. / Economics

This thesis examines both the long run and the short run impact of Exchange Rate Volatility on Foreign Direct Investment using an unbalanced panel data from three Sub-Saharan African countries of Kenya, Uganda and Tanzania. This is accomplished by generating Exchange Rate Volatility figures by the GARCH(1,1) methodology. The control variables included in this study include GDP, GDP growth, Economic Openness and Exchange rate. In order to capture the impact of economic openness on exchange rate volatility and thus foreign direct investment, different econometric specifications are adopted. The unbalanced panel data used in the analysis ranges for different time period for the specific countries considered in the panel.

The informational content of implied volatility and its prediction power is evaluated for time horizons of one month. The study covers the period of November 2007 to November 2013 for the two indices S&P500 and OMXS30. The findings are put in relation to the corresponding results for past realized volatility. We find results supporting that implied volatility is an efficient, although biased estimator of realized volatility. Our results support the common notion that implied volatility predicts realized volatility better than past realized volatility, and that it also subsumes most of the informational content of past realized volatility.

I find the low volatility anomaly is present in all but the smallest of stocks. Portfolios can be formed on either total or idiosyncratic volatility to take advantage of this anomaly, but I show measures of idiosyncratic volatility are key. Standard risk-adjusted returns suggest that there is no low volatility anomaly from 1996 through 2011, but I find this result arises from model misspecification. Caution must be taken when analyzing high volatility stocks because their returns have a nonlinear relationship with momentum during market bubbles. I then find that mutual funds with low return volatility in the prior year outperform those with high return volatility by about 5.4% during the next year. After controlling for heterogeneity in fund characteristics, I show that a one standard deviation decrease in fund volatility in the prior year predicts an increase in alpha of about 2.5% in the following year. My evidence suggests that this difference in performance is not due to manager skill but is instead caused by the low volatility anomaly. I find no difference in performance or skill between low and high volatility mutual funds after accounting for the returns on low and high volatility stocks.

In this Master thesis, we use a singular and regular perturbation theory to derive an analytic approximation formula for the expected discounted penalty function. Our model is an extension of Cramer–Lundberg extended classical model because we consider a more general insurance risk model in which the compound Poisson risk process is perturbed by a Brownian motion multiplied by a stochastic volatility driven by two factors- which have mean reversion models. Moreover, unlike the classical model, our model allows a ruin to be caused either by claims or by surplus’ fluctuation. We compute explicitly the first terms of the asymptotic expansion and we show that they satisfy either an integro-differential equation or a Poisson equation. In addition, we derive the existence and uniqueness conditions of the risk model with two stochastic volatilities factors.

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A growing concern among investors for social responsibility in relation to the business world and its effect on the environment, society, and government has increased and therefore different types of stock indices and funds that incorporate socially responsible ideals have been developed. However, a literature review revealed that there does not seem to be much information about the volatility of Green Funds or Socially Responsible Investments (SRI). Volatility is an important part of understanding the financial markets and is used by many to understand asset allocation, risk management, option pricing and many other functions. Therefore, the purpose of this thesis is to investigate the volatility performance of SRIs, REFs and Conventional Indices by using different models CAPM, SR, JA and EGARCH, and monthly and daily data from the US, UK, Japan and Eurozone financial markets to compare results.   This thesis has been conducted by following an objective ontological and positivist epistemological position, because the data used for analysis in this thesis is independent from the author and has studied what actually exists, not what the author seeks to interpret. The research approach is functionalist, because this thesis sought to explain how the investments function in relation to volatility comparisons in different financial markets and if this volatility can be predicted through a framework of rules designed by previous researchers. The design is a deductive study of quantitative, longitudinal, secondary data, because hypotheses are derived from theory to test the volatility of time series data between the year 2007 and 2012 through empirical evidence.   Statistical evidence was found to suggest that the EGARCH model for volatility measurement is the best fit to model volatility and daily data can give more information and better consistency between results. SRIs were found to be less volatile than CIs in all financial markets; REFs were found more volatile than CIs in the US and Eurozone markets but not in the UK and Japan markets; REFs were found to be more volatile than SRIs in all markets except the UK; REFs were also found to be more volatile than SRIs and CIs during a recession in all markets except the UK. Evidence also indicated that the correlations between REFs and SRIs in the US and Eurozone were significant, but not significant in the UK and Japan market samples. The correlations were low between the UK and Japan SRIs, Japan and Eurozone SRIs and Japan SRI and Eurozone REF, which suggest that an investor may consider to diversify between these investments. However, all other statistically significant correlations between financial markets were high and could consequentially deliver poor long term investment performance.

There is a large body of research that indicates that international equity markets co-move over time. This co-movement manifests in various instruments, ranging from equities and bonds to soft commodities. However, this co-movement is more prevalent over crisis periods and can be seen in returns and volatility transmission effects. The recent financial crisis demonstrated that no local market is immune to transmission effects from international markets. South African financial market participants, such as investors and policymakers, have a vested interest in understanding how the equity market in particular and the economy in general react to international financial crises. This study aims to contribute an improved understanding of how the South African equity market interacts with international equity markets, by identifying the degree of price and volatility transmission before, during, and after an international financial crisis. This was done by investigating the possibility of changes in price and volatility transmissions from the Asian financial crisis (1997–1998), the dotcom bubble (2000–2001) and the more recent subprime financial crisis (2007–2009). An Exponential Generalized Autoregressive Conditional Heteroskedasticity (E-GARCH) model was employed within the framework of an Aggregate Shock model. The results indicate that during the international financial crises studied, the JSE All Share Index was directly affected through contagion effects inherent in the returns of the originating crisis country. Volatility transmissions during international financial crises came directly from the originating crisis country. Finally, the FTSE 100 Index was the main exporter of price and volatility transmission to the JSE All Share Index. / Thesis (M.Com. (Risk management))--North-West University, Potchefstroom Campus, 2012

This essay investigates three different GARCH-models (GARCH, EGARCH and GJR-GARCH) along with two distributions (Normal and Student’s t), which are used to forecast the Value at Risk (VaR) for different return series. Seven major international equity indices are examined. The purpose of the essay is to answer which of the three models that is better at forecasting the VaR and which distribution is more appropriate.  The results show that the EGARCH(1,1)  is preferred for all indices included in the study.

The Black-Scholes option pricing model has several well recognized deficiencies, one of which is its assumption of a constant and time-homogeneous stock return volatility term. The implied volatility smile has been studied by subsequent researchers and various models have been developed in an attempt to reproduce this phenomenon from within the models. However, few of these models yield closed-form pricing formulas that are easy to implement in practice. In this thesis, we study a Mixture Lognormal model (MLN) for European option pricing, which assumes that future stock prices are conditionally described by a mixture of lognormal distributions. The ability of mixture models in generating volatility smiles as well as delivering pricing improvement over the traditional Black-Scholes framework have been much researched under multi-component mixtures for many derivatives and high-volatility individual stock options. In this thesis, we investigate the performance of the model under the simplest two-component mixture in a market characterized by relative tranquillity and over a relatively stable period for broad-based index options. A careful interpretation is given to the model and the results obtained in the thesis. This di erentiates our study from many previous studies on this subject. Throughout the thesis, we establish the unique advantage of the MLN model, which is having closed-form option pricing formulas equal to the weighted mixture of Black-Scholes option prices. We also propose a robust calibration methodology to fit the model to market data. Extreme market states, in particular the so-called crash-o-phobia effect, are shown to be well captured by the calibrated model, albeit small pricing improvements are made over a relatively stable period of index option market. As a major contribution of this thesis, we extend the MLN model to price exotic options including binary, Asian, and barrier options. Closed-form formulas are derived for binary and continuously monitored barrier options and simulation-based pricing techniques are proposed for Asian and discretely monitored barrier options. Lastly, comparative results are analysed for various strike-maturity combinations, which provides insights into the formulation of hedging and risk management strategies.