Thesis advisor: Harold Petersen / Minsky developed a Financial Instability Hypothesis which sought to find an endogenous explanation for a modern economy’s vulnerability to crashes. Specifically, he investigated the ways in which the financial structures of a modern economy might contribute to its instability. The hypothesis rests upon the twin assertions that some financial arrangements are more dangerous than others, and that during economic booms, investors’ incentives are altered to favor these more dangerous arrangements. Essentially, in good times, the profit-seeking motive of investors overrides a diminished risk aversion, as memories of losses fade into the past. This paper empirically tests Minsky’s second assertion, by using econometric techniques to analyze the relationship between risk appetite and market returns. Spreads between the yields of bonds of different credit qualities are used as a proxy for wider investor sentiment toward risk. Regressions demonstrate that changes in risk appetite can be explained at least in part by historical market returns. Such a finding supports Minsky’s proposal that incentives of investors change in response to varying market conditions. It further implies that regulatory authorities might examine the level of risk appetite to determine whether increases in asset prices indicate the formation of speculative bubbles or are rather reflecting developments in the fundamentals underlying said assets. / Thesis (BA) — Boston College, 2010. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Economics Honors Program. / Discipline: College Honors Program. / Discipline: Economics.

I explore the impact financial statement transparency has on the probability of restatement and the effect a restatement announcement has on the levels of future financial statement transparency. Information theory suggests that a strong information environment increases accounting quality. Using financial statement transparency as a proxy for the information environment, I find that transparency is associated with a lower probability of financial statement restatement. There are competing theories to predict how restatement announcements affect future levels of transparency. Skinner’s (1953) theory of operant conditioning, which states that behavior is modified based on positive or negative conditioning suggests that the level of transparency increases after a restatement announcement. However, expectancy theory suggests that firms engage in certain behaviors in order to derive expected rewards or incentives. Motivation is eliminated if the rewards are deemed unobtainable thereby eliminating managers’ incentive to improve their reporting strategy suggesting that the level of transparency decreases after a restatement announcement. I find that restatement announcement has a negative association with the transparency measure and the magnitude of this effect decreases over time compared to non-restatement firms. These results are magnified if the restatement is due to fraud. However, the changes are not significant. Further, the transparency associations are mitigated if there is a change in CEO after the restatement announcement. In addition, using a sample of firms that made a restatement announcement matched with a sample of firms that did not make a restatement announcement, the difference in the transparency measure before and after the restatement announcement is statistically insignificant. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Boston University. University Professors Program Senior theses. / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / 2031-01-02

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Ng Yin Hung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 70-74). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgements --- p.iii / Table of contents --- p.iv / Chapter Chapter 1 . --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Purpose of Study --- p.1 / Chapter 1.3 --- Summary of Results --- p.3 / Chapter 1.4 --- Organization --- p.5 / Chapter Chapter 2. --- Literature Review --- p.6 / Chapter 2.1 --- Tax --- p.6 / Chapter 2.2 --- Agency Costs --- p.7 / Chapter 2.3 --- Asymmetric Information --- p.8 / Chapter 2.4 --- Product Market Interactions --- p.10 / Chapter 2.5 --- Corporate Control --- p.10 / Chapter Chapter 3. --- Data --- p.12 / Chapter 3.1 --- Methodology --- p.12 / Chapter 3.2 --- Data Collection --- p.12 / Chapter 3.3 --- Measures of Leverage --- p.14 / Chapter 3.4 --- An Overview of Corporate Capital Structure in 42 Countries --- p.15 / Chapter 3.5 --- Chapter Summary --- p.16 / Chapter Chapter 4. --- Firm Characteristics Factors in Capital Structure --- p.18 / Chapter 4.1. --- How Firm Characteristics Factors Related with Levearge --- p.18 / Chapter 4.1.1 --- Tangibility --- p.18 / Chapter 4.1.2 --- Market-to-Book Ratio --- p.19 / Chapter 4.1.3 --- Size --- p.19 / Chapter 4.1.4 --- Profitability --- p.20 / Chapter 4.1.5 --- Business Risk --- p.20 / Chapter 4.2. --- What the Data Tells Us --- p.21 / Chapter 4.2.1 --- Regression Analysis of the Effect of Firm Characteristics and Industry Dummy on Corporate Leverage --- p.21 / Chapter 4.2.1.1 --- Tangibility --- p.22 / Chapter 4.2.1.2 --- Market-to-Book Ratio --- p.24 / Chapter 4.2.1.3 --- Size --- p.27 / Chapter 4.2.1.4 --- Profitability --- p.28 / Chapter 4.2.2 --- Regression of Leverage on Firm Characteristics and Industry Dummy with Business Risk Added --- p.30 / Chapter 4.3. --- Chapter Summary --- p.32 / Chapter Chapter 5. --- Country and Firm Characteristics Factors in Capital Structure --- p.34 / Chapter 5.1. --- Regressions of Leverage on Country Dummies --- p.34 / Chapter 5.2. --- Regressions of Leverage on Country Dummies and Firm Characteristics --- p.37 / Chapter 5.2.1 --- Controlling Frim Characteristics --- p.37 / Chapter 5.2.2 --- Controlling Nationality of a Company --- p.39 / Chapter 5.3. --- Chapter Summary --- p.42 / Chapter Chapter 6. --- Macroeconomic and Institutional Factors in Capital Structure --- p.44 / Chapter 6.1. --- Macroeconomic Factors --- p.44 / Chapter 6.1.1 --- Inflation --- p.45 / Chapter 6.1.2 --- Real GDP Growth Rate --- p.47 / Chapter 6.1.3 --- Real GDP per capita --- p.48 / Chapter 6.2. --- Institutional Factors --- p.49 / Chapter 6.2.1 --- Financial Development --- p.51 / Chapter 6.2.1.1 --- Financial Intermediary Devleopment --- p.52 / Chapter 6.2.1.2 --- Stock Market Development --- p.53 / Chapter 6.2.2 --- Financial System Structure --- p.54 / Chapter 6.2.3 --- Legal Instituion Strength --- p.57 / Chapter 6.2.4 --- Investor Rights and Protection --- p.59 / Chapter 6.2.5 --- Entry Regulations --- p.61 / Chapter 6.2.6 --- Tax Codes --- p.63 / Chapter 6.3. --- Chapter Summary --- p.65 / Chapter Chapter 7. --- Conclusion --- p.67 / Chapter 7 1 --- Summary of Results --- p.67 / Chapter 7.2 --- Limitations and Suggestions for Future Studies --- p.68 / References --- p.70 / Tables --- p.75

Doctor of Philosophy / Department of Human Ecology-Personal Financial Planning / Stuart Heckman / Maurice M. MacDonald / There were 19.8 million college students in the U.S. in the fall of 2017 (NCES, 2017). These students face many challenges and opportunities including new social networks, enhanced academic pressures, new living arrangement and new financial responsibilities. Many of these students have had positive role models who have socialized them through discussion and example (Shim, Barber, Card, Xiao, & Serido, 2010). These role models may have instilled positive self-efficacy in these students as well helping to prepare the students for the many challenges and opportunities in college. Some students have not had those role models. This research seeks to understand the impact of positive socialization and self-efficacy on students’ feelings of financial stress and then on their choices of how to cope with that stress. The financial challenges of paying for college are well publicized with 44.2 million Americans currently owing over $1.48 trillion in student loan debt (NCES, 2017). In this study, the impact of these financial challenges is viewed through the lens of the Transactional Model of Stress and Coping Theory which proposes that stress is an individual perception influenced by that individual’s sense of threat, vulnerability, and ability to cope (Lazarus & Folkman, 1984). There are two sets of empirical models; the first examines the influences in the appraisal process on perceptions of financial stress using OLS regression with the second empirical model examining the influences on their coping choices using logistic regression. Both models control for influences on stress and coping choices including demographic, socio-economic and academic factors. The results inform how financial self-efficacy and financial socialization influence financial stress as they suggest the importance of enabling financial self-efficacy by parents, educators and other leaders of children.

This dissertation deals with issues of forecasting in financial markets. The first part of my dissertation is motivated by the observation that most parametric volatility models follow Engle's (1982) original idea of modelling the volatility of asset returns as a function of only past information. However, current returns are potentially quite informative for forecasting, yet are excluded from these models. The first and second chapters of this dissertation try to address this question from both a theoretical and an empirical perspective. The second part of this dissertation deals with the important issue of forecast evaluation and selection in unstable environments, where it is known that the existing methodology can generate spurious and potentially misleading results. In my third chapter, I develop a new methodology for forecast evaluation and selection in such an environment. In the first chapter, $\textit{Real-time GARCH}$, I propose a new parametric volatility model, which retains the simple structure of GARCH models, but models the volatility process as a mixture of past and current information as in the spirit of Stochastic Volatility (SV) models. This provides therefore a link between GARCH and SV models. I show that with this new model I am able to obtain better volatility forecasts than the standard GARCH-type models; improve the empirical fit of the data, especially in the tails of the distribution; and make the model faster in its adjustment to the new unconditional level of volatility. Further, the new model offers a much needed framework for specification testing as it nests the standard GARCH models. This chapter has been published in the $\textit{Journal of Financial Econometrics}$ (Smetanina E., 2017, Real-time GARCH, $\textit{Journal of Financial Econometrics}$, 15(4), 561-601.) In chapter 2, $\textit{Asymptotic Inference for Real-time GARCH(1,1) model}$, I investigate the asymptotic properties of the Gaussian Quasi-Maximum-Likelihood estimator (QMLE) for the Real-time GARCH(1,1) model, developed in the first chapter of this dissertation. I establish the ergodicity and $\beta$-mixing properties of the joint process for squared returns and the volatility process. I also prove strong consistency and asymptotic normality for the parameter vector at the usual $\sqrt{T}$ rate. Finally, I demonstrate how the developed theory can be viewed as a generalisation of the QMLE theory for the standard GARCH(1,1) model. In chapter 3, $\textit{Forecast Evaluation Tests in Unstable Environments}$, I develop a new methodology for forecast evaluation and selection in the situations where the relative performance between models changes over time in an unknown fashion. Out-of-sample tests are widely used for evaluating models' forecasts in economics and finance. Underlying these tests is often the assumption of constant relative performance between competing models, however this is invalid for many practical applications. In a world of changing relative performance, previous methodologies give rise to spurious and potentially misleading results, an example of which is the well-known ``splitting point problem''. I propose a new two-step methodology designed specifically for forecast evaluation in a world of changing relative performance. In the first step I estimate the time-varying mean and variance of the series for forecast loss differences, and in the second step I use these estimates to construct new rankings for models in a changing world. I show that the new tests have high power against a variety of fixed and local alternatives.

A dissertation submitted in fulfillment of the requirements of the degree of Master of Science in the School of Computer Science and Applied Mathematics March 22, 2017 / Agent-based models, particularly those applied to financial markets, demonstrate the ability to produce realistic, simulated system dynamics, comparable to those observed in empirical investigations. Despite this, they remain fairly difficult to calibrate due to their tendency to be computationally expensive, even with recent advances in technology. For this reason, financial agent-based models are frequently validated by demonstrating an ability to reproduce well-known log return time series and central limit order book stylized facts, as opposed to being rigorously calibrated to transaction data. We thus apply an established financial agent-based model calibration framework to a number of intraday agent-based models employing realistic order matching procedures and demonstrate that while the parameters of these models rooted in market microstructure can indeed be meaningfully calibrated, those exclusively related to agent behaviors and incentives remain problematic, due to the presence of parameter degeneracies not identified by stylized fact-centric validation. We further argue that the observed parameter degeneracies are likely a consequence of the realistic matching processes employed in these models, which suggests that alternative approaches to linking data, phenomenology and market structure may be necessary and that the stylized fact-centric validation of intraday agent-based models is insufficient. / MT 2017

In 2007, the United States suffered what is known as the "Subprime Mortgage Crisis". This took an enormous toll on the United States Economy. However, nearby country, Canada did not experience this situation. The objective of this thesis is to determine why such different outcomes were seen in order for future economic stability. This research will examine mortgage processes, mortgage management, foreclosures on mortgages of both countries. It will then paint the economic picture that each country faced in 2007, while providing an explanation as to why the United States fared much worse than Canada during this time.

The growth rate of chief executive officers' (CEOs) compensation has dramatically outpaced average employees' pay increases. Scholars have not been able to reach a consensus on whether the financial performance of firms has a positive influence on CEOs' compensation. Also, boards of directors lack a clear understanding of the relationship between financial performance of firms and CEOs' incentive compensation in the U.S. banking industry. The purpose of this correlational study was to examine the predictive relationship between financial performance of firms (measured by return on equity [ROE] and annual revenue) and CEOs' total compensation in the U.S. banking industry. According to agency theory, which was the theoretical framework for this study, failing to understand such a relationship could cause a misalignment between CEOs' compensation and the performance of firms. Hence, the research question was, does a predictive relationship exist between ROE, annual revenues of firms, and CEOs' total compensation? Archival data from publicly traded U.S. banking firms were collected and analyzed. Multiple regression techniques were used to identify a statistically significant predictive model, F (2, 121) = 95.691, p < .000, R2 = .613. Changes in annual revenue were found to be significantly more sensitive than changes of ROE relative to the impact on changes in CEOs' total compensation. This study may contribute to positive social change by raising individuals' awareness of the importance of maintaining CEOs' equitable compensation. Additionally, compensation committees of banking firms can use the findings from this study to evaluate their compensation strategies and make necessary adjustments.