The following dissertation contains two distinct empirical essays which contribute to the overall field of Financial Economics. Chapter 1, entitled “The Determinants of Dynamic Dependence: An Analysis of Commodity Futures and Equity Markets,” examines the determinants of the dynamic equity-commodity return correlations between five commodity futures sub-sectors (energy, foods and fibers, grains and oilseeds, livestock, and precious metals) and a value-weighted equity market index (S&P 500). The study utilizes the traditional DCC model, as well as three time-varying copulas: (i) the normal copula, (ii) the student’s t copula, and (iii) the rotated-gumbel copula as dependence measures. Subsequently, the determinants of these various dependence measures are explored by analyzing several macroeconomic, financial, and speculation variables over different sample periods. Results indicate that the dynamic equity-commodity correlations for the energy, grains and oilseeds, precious metals, and to a lesser extent the foods and fibers, sub-sectors have become increasingly explainable by broad macroeconomic and financial market indicators, particularly after May 2003. Furthermore, these variables exhibit heterogeneous effects in terms of both magnitude and sign on each sub-sectors’ equity-commodity correlation structure. Interestingly, the effects of increased financial market speculation are found to be extremely varied among the five sub-sectors. These results have important implications for portfolio selection, price formation, and risk management. Chapter 2, entitled, “US Community Bank Failure: An Empirical Investigation,” examines the declining, but still pivotal role, of the US community banking industry. The study utilizes survival analysis to determine which accounting and macroeconomic variables help to predict community bank failure. Federal Deposit Insurance Corporation and Federal Reserve Bank data are utilized to compare 452 community banks which failed between 2000 and 2013, relative to a sample of surviving community banks. Empirical results indicate that smaller banks are less likely to fail than their larger community bank counterparts. Additionally, several unique bank-specific indicators of failure emerge which relate to asset quality and liquidity, as well as earnings ratios. Moreover, results show that the use of the macroeconomic indicator of liquidity, the TED spread, provides a substantial improvement in modeling predictive community bank failure.

Dynamic analysis of binary files is an area of computer science that has many purposes. It is useful when it comes to debugging software in a development environment and the developer needs to know which statements affected the value of a specific variable. But it is also useful when analyzing a software for potential vulnerabilities, where data controlled by a malicious user could potentially result in the software executing adverse commands or executing malicious code. In this thesis a tool has been developed to perform dynamic analysis of x86 binaries in order to generate dynamic control-dependence graphs over the execution. These graphs can be used to determine which conditional statements that resulted in a certain outcome. The tool has been developed for x86 Linux systems using the dynamic binary instrumentation framework PIN, developed and maintained by Intel. Techniques for utilizing the additional information about the control flow for a program available during the dynamic analysis in order to improve the control flow information have been implemented and tested. The basic theory of dynamic analysis as well as dynamic slicing is discussed, and a basic overview of the implementation of a dynamic analysis tool is presented. The impact on the performance of the dynamic analysis tool for the techniques used to improve the control flow graph is significant, but approaches to improving the performance are discussed.

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