This dissertation comprises two essays; the first of which investigates sovereign credit risk interdependencies, while the second examines the reaction of corporate credit risk to sovereign credit risk events. The first essay titled, Characterizing Sovereign Credit Risk Interdependencies: Evidence from the Credit Default Swap Market, investigates the relationships that exist among disparate sovereign credit default swaps (CDS) and the implications on sovereign creditworthiness. We exploit emerging market sovereign CDS spreads to examine the reaction of sovereign credit risk to changes in country-specific and global financial factors. Utilizing aVAR model fitted with DCC GARCH, we find that comovements of spreads generally exhibit significant time-varying correlations, suggesting that spreads are commonly affected by global financial factors. We construct 19 country-specific commodity price indexes to instrument for country terms of trade, obtaining significant results. Our commodity price indexes account for significant variation in CDS spreads, controlling for global financial factors. In addition, sovereign spreads are found to be related to U.S. stock market returns and the VIX volatility risk premium global factors. Notwithstanding, our results suggest that terms of trade and commodity prices have a statistically and economically significant effect on the sovereign credit risk of emerging economies. Our results apply broadly to investors, financial institutions and policy makers motivated to utilize profitable factors in global portfolios. The second essay is titled, Differential Stock Market Returns and Corporate Credit Risk of Listed Firms. This essay explores the information transfer effect of shocks to sovereign credit risk as captured in the CDS and stock market returns of cross-listed and local stock exchange listed firms. Based on changes in sovereign credit ratings and outlooks, we find that widening CDS spreads of firms imply that negative credit events dominate, whereas tightening spreads indicate positive events. Grouping firms into companies with cross-listings and those without, we compare the spillover effects and find strong evidence of contagion across equity and CDS markets in both company groupings. Our findings suggest that the sensitivity of corporate CDS prices to sovereign credit events is significantly larger for non-cross-listed firms. Possible reasons for this finding could in fact be due to cross-listed firms’ better access to external capital and less degree of asymmetric information, relative to non-cross-listed peers with lower level of investor recognition. Our results provide new evidence relevant to investors and financial institutions in determining sovereign credit risk germane to corporate financial risk, for the construction of debt and equity portfolios, and hedging considerations in today’s dynamic environment.

Almost two decades after the burst of the Dot-com bubble, investors are opinionated as to whether a new technology bubble has formed in the equities market. Similar to the late 1990's and early 2000's, many Internet firms today go through initial public offering without yet turning over a dollar of earnings, but boast certain revenue-associated performance metrics to investors promising of future success. However, investors are known to hold sentiments sensitive to earnings announcements (Seok, Cho & Ryu, 2019) and reward firms which meet or beat earnings with higher stock returns (Bartov, Givoly & Hayn, 2002). That raises a question on the content of earnings announcements: Besides earnings and cash flow, are there other factors that may influence investor decisions to trade some Internet stocks? My primary hypothesis is that the voluntary disclosure of specific non-financial key performance indicators (NFKPI) during earnings announcement by Internet firms influences the investors' investing/trading decisions. My motivation for this research is to understand better whether there is a strategic element in the voluntary disclosure of NFKPI in Internet companies and how it may impact investors' decisions. The results could be useful to firms in their evaluations of whether to release NFKPI or similar information and to equity research analysts as well as investors in measuring their expectations and valuations of the firms' stocks. The intention of the study is not to generalize the findings to the full market, as the number of companies with the practice of voluntary disclosure of NFKPI is comparatively few compared to those without the practice. Instead, this study examines the effects of NFKPI on the stock returns of those companies which choose to disclose it. I use event study methodology to test the statistical significance of disclosure of NFKPIs during earnings announcements. By controlling for earnings surprise and other meaningful financial ratios, I also examine how the signaling effect of NFKPI could be distinguished from the signaling effects of important information concurrently released during earnings announcements. I focus on two types of NFKPI within the Internet industry: Gross Bookings for online booking agency services and Daily Active Users for social media. As earnings reports and quarterly filings often do not necessarily come together on the same date, I hand-collected data to estimate the surprise effect of NFKPI per earnings announcement, by using available broker forecasts of the respective NFKPI as a proxy for the investor's NFKPI expectation. The results show that while revenue surprise remains consistently the most influential variable to investors, NFKPI Surprise has a positive, statistically significant relationship with the firm's abnormal returns. Additionally, despite being insignificant when expected earnings is beat or in line with consensus, NFKPI Surprise is found statistically significant with a positive relationship to abnormal returns when expected earnings is missed. In line with existing research on management's motivation to prevent negative earnings surprises (Matsumoto, 2002), these findings imply that if firms could employ the voluntary disclosure of NFKPI to manipulate investors' impression and to cushion their stock prices against potential negative market reactions when earnings is missed.

The objective of this paper is to examine the impact of implementing the static and dynamic volatility interruption rule on idiosyncratic volatility and stock returns in Nasdaq Stockholm. Using EGARCH and GARCH models to estimate the conditional idiosyncratic volatility, we find that the conditional idiosyncratic volatility and stock returns increase as stock prices hit the upper static or dynamic volatility interruption limits. Conversely, we find that the conditional idiosyncratic volatility and stock returns decrease as stock prices hit the lower static or dynamic volatility interruption limit. We also find that the conditional idiosyncratic volatility is higher when stock prices reach the upper dynamic limit than when they reach the upper static limit. Furthermore, we compare the conditional idiosyncratic volatility and stock returns on the limit hit days to the day before and after the limit hit events and find that the conditional idiosyncratic volatility and stock returns are more volatile on the limits hit days. To test the volatility spill-over hypothesis, we set a range of a two-day window after limit hit events and find no evidence for volatility spill-over one or two days after the limit hit event, indicating that the static and dynamic volatility interruption rule is effective in curbing the volatility. Finally, we sort stocks by their size and find that small market cap stocks gain higher returns than larger market cap stocks upon reaching the upper limits, both static and dynamic.

This thesis further investigates the effectiveness of 15 variable moving average strategies that mimic the trading rules used in the study by Brock, Lakonishok, and LeBaron (1992). Instead of applying these strategies to developed markets, unique characteristics of emerging markets offer opportunity to investors that warrant further research. Before transaction costs, all 15 variable moving average strategies outperform the naïve benchmark strategy of buying and holding different emerging market ETF's over the volatile period of 858 trading days. However, the variable moving averages perform poorly in the "bubble" market cycle. In fact, sell signals become more unprofitable than buy signals are profitable. Furthermore, variations of 4 of 5 variable moving average strategies demonstrate significant prospects of returning consistent abnormal returns after adjusting for transaction costs and risk.

This paper examines the capital - asset pricing model (CAPM) which has been extended with a factor for geo-political risk. I use monthly stock return data for all stocks listed on a major US exchange from January 1990 to December 2016 and utilize a Fama-Macbeth Regression with Newey-West standard errors to test the geo-political augmented Sharpe-Lintner CAPM. The paper first determines if increased sensitivity to geopolitical risk lead s to lower average returns and second assesses if geo-political risk as an explanatory variable is a significant enough to expose a failure of the CAPM to capture expected returns fully through beta. The results of our regressions do not confirm the hypothesis that firms with high sensitivities to geo-political risk have expressly different returns in the long run. Furthermore, our Fama-Macbeth regression does not find expressly significant average slopes for geo-political risk as a variable.

Level crossing times and their applications in finance are of importance, given certain threshold levels that represent the "desirable" or "sell" values of a stock. In this thesis, we make use of Wald's lemmas and various deep results from renewal theory, in the context of finance, in modelling the growth of a portfolio of stocks. Several models are employed .

The Cost of Feeling Good attempts to quantify the optimum portfolio returns of Socially Responsible Investment Funds and Dual-Purpose Portfolios. In order to meet the demands of investors who want to create a social impact and generate financial returns, investors can choose two methods. For the purpose of this study, the social returns were quantified and the financial returns were quantified using net present value. In every scenario, the socially responsible investment decision generated higher financial returns. Because of the immediate loss to an investor after choosing the DPP strategy, financially, the SRI fund appears to be the better approach for a financially driver investor. In terms of social returns, the DPP has a more clear impact on society. Measured as the charitable contribution given on an $1,000 investment, the socially responsible fund contributes far less to society on a per investor basis. Therefore, if an investor is interested in generating higher social returns and wants to be selective in terms of their charitable donation, they should choose the DPP model. In terms of tax brackets, investors in higher tax brackets have to generate higher financial returns on socially responsible investments in order to match the returns of a DPP. This is also true with investors who invest less in charity. Therefore, the investors that are in the highest tax bracket and contribute little to charity will need to generate far higher SRI returns according to the constructed theory. This finding is important to the growing millennial trend in sustainable investing.

This study examines the relationship between company management guidance, and ex-ante crash risk over the duration of 2008(Jan 2006-Dec 2009) financial crisis using the implied volatility skew, which is based upon ex-ante volatility implied by the pricing model developed by Black-Scholes (1973). The study finds that over the duration of this crisis period, management guidance decreases with a rise in ex-ante crash risk. Further, the study provides evidence on the relationship of management guidance and earnings volatility, and how that is affected by a firm's industry product concentration based on the Herfindahl-Hirschman Index (HHI) score.

In order to assess the continuing imbalance of top executives between genders, I examine the effects of gender diversity within top management teams on firm risk, performance, and executive compensation. Capitalizing on previous analysis, I apply three unique differentiators. First, I utilize current data from 2012 to 2017 from Compustat, CRSP, and ExecuComp. Second, I provide a unique subset view on a firm and individual performance of female CEOs to examine executive compensation. Third, my scope of analysis expands to S&P Composite 1500 companies. I use separate models to estimate the effect of gender diversity on firm risk by examining a firm’s beta and standard deviation of daily returns, on firm performance by examining a firm’s Tobin’sQ, and lastly on executive compensation by examining an executive’s natural logarithm of total compensation. My findings suggest gender diversity among executives appears to have an immaterial effect on a firm’s risk and performance. In turn, I also find that female executives continue to receive less compensation than their male colleagues. However, I find an average female CEO receives a higher level of compensation than an average male CEO. Lastly, I find as gender diversity increases among executives, specifically CEOs, the compensation differences between genders decreases.

<p>In this thesis we investigate portfolio optimization under Value at Risk, Average Value at Risk and Limited expected loss constraints in a framework, where stocks follow a geometric Brownian motion. We solve the problem of minimizing Value at Risk and Average Value at Risk, and the problem of finding maximal expected wealth with Value at Risk, Average Value at Risk, Limited expected loss and Variance constraints. Furthermore, in a model where the stocks follow an exponential Ornstein-Uhlenbeck process, we examine portfolio selection under Value at Risk and Average Value at Risk constraints. In both geometric Brownian motion (GBM) and exponential Ornstein-Uhlenbeck (O.U) models, the risk-reward criterion is employed and the optimal strategy is found. Secondly, the Value at Risk, Average Value at Risk and Variance is minimized subject to an expected return constraint. By running numerical experiments we illustrate the effect of Value at Risk, Average Value at Risk, Limited expected loss and Variance on the optimal portfolios. Furthermore, in the exponential O.U model we study the effect of mean-reversion on the optimal strategies. Lastly we compare the leverage in a portfolio where the stocks follow a GBM model to that of a portfolio where the stocks follow the exponential O.U model.</p> / Master of Science (MSc)