This dissertation contains two essays that study the implications of information arrival on asset prices. In the first essay, I study an important aspect of the firm-level information structure - the quantity of information - and its effect on the cross-section of stock returns. The main contribution of this essay is to propose a new proxy for information intensity (monthly information quantity) and establish a link between information intensity and stock returns. I find that higher information intensity reduces expected uncertainty and leads to a lower expected return, after controlling for a variety of traditional risk factors and asset pricing anomalies. An information-intensity-based long-short portfolio generates an abnormal return of 4.44% per year. My findings suggest that, as a key component of information structure, information quantity is of first order importance in determining stock returns, and more generally, that investor learning plays an important role in financial markets with incomplete information. The second essay, based on a joint work with John Maheu and Tom McCurdy, studies the asset-pricing implication of market-level information arrival, which can lead to large movements (jumps) in the market index. Deviating from the literature that studies the impact of jumps through option pricing and motivated by a nonlinear pricing kernel associated with general preferences, we focus on the pricing impact of jumps through the pricing of higher-order moments. We find that three components of a modeling device, including: a 2-component GARCH model for diffusive volatility, an autoregressive model for jump intensity, and a higher order moment specification of the equity premium, are particularly important for asset pricing with jumps. This modeling device enables us to be the first to uncover significant pricing of both diffusive risk and jump risk, using only a time series of equity return data. We find that the risk premium due to jumps is a significant part of the overall equity premium. Our results also suggest the existence of a significant skewness premium and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. Furthermore, taking jumps into account improves the out-of-sample performance of a portfolio allocation application.

This dissertation contains two essays that study the implications of information arrival on asset prices. In the first essay, I study an important aspect of the firm-level information structure - the quantity of information - and its effect on the cross-section of stock returns. The main contribution of this essay is to propose a new proxy for information intensity (monthly information quantity) and establish a link between information intensity and stock returns. I find that higher information intensity reduces expected uncertainty and leads to a lower expected return, after controlling for a variety of traditional risk factors and asset pricing anomalies. An information-intensity-based long-short portfolio generates an abnormal return of 4.44% per year. My findings suggest that, as a key component of information structure, information quantity is of first order importance in determining stock returns, and more generally, that investor learning plays an important role in financial markets with incomplete information. The second essay, based on a joint work with John Maheu and Tom McCurdy, studies the asset-pricing implication of market-level information arrival, which can lead to large movements (jumps) in the market index. Deviating from the literature that studies the impact of jumps through option pricing and motivated by a nonlinear pricing kernel associated with general preferences, we focus on the pricing impact of jumps through the pricing of higher-order moments. We find that three components of a modeling device, including: a 2-component GARCH model for diffusive volatility, an autoregressive model for jump intensity, and a higher order moment specification of the equity premium, are particularly important for asset pricing with jumps. This modeling device enables us to be the first to uncover significant pricing of both diffusive risk and jump risk, using only a time series of equity return data. We find that the risk premium due to jumps is a significant part of the overall equity premium. Our results also suggest the existence of a significant skewness premium and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. Furthermore, taking jumps into account improves the out-of-sample performance of a portfolio allocation application.

The primary objective of this dissertation is to examine the role of corporate governance in the performance of publicly listed corporations. The normative research suggests that stronger corporate governance should lead to better market performance and a firm’s governance practice should have a positive effect on its market value. This research focuses on Chinese capital markets because of their unique characteristics with respect to elements of corporate governance.

This thesis groups three papers examining the role of multi-location firms in the geographic diffusion of knowledge. The first chapter examines whether a firm's headquarters can tap into the knowledge pool in a remote location through FDI. Using U.S. patent data, I show that an R&D headquarters in location “A” cites third party patents from location “B” disproportionately (relative to a control group also from location “A”) when the firm has an R&D satellite in location “B”. This “satellite effect” on knowledge diffusion is economically significant, representing 47% of the knowledge flow premium associated with collocation. Furthermore, the effect is particularly strong for new knowledge, as well as in areas of satellite technological specialization. In addition, the results show that firms with stronger cross-location, intra-firm networks experience a larger satellite effect on knowledge diffusion. The second chapter studies the effects of remote satellites on outward knowledge flow with an international development focus. I find that the presence of a foreign MNC subsidiary increases the flow of knowledge from the MNC's headquarters to local firms. This effect is largest in countries and sectors with strong but not world-class capabilities, having both the motivation and absorptive capacity to learn from foreign parties. The results suggest that emerging country governments should promote inward FDI since the knowledge brought by multinationals spills over to local firms and boosts innovative capacity. The third chapter offers a theoretical foundation for thinking about the exchange of knowledge and ideas, and the role of remote satellites. I present a model where ideas are shared through social networks as modeled by repeated agent interactions. The mechanism at once explains three broad empirical findings: why the diffusion of ideas is highly localized, why ideas flow more easily within the firm, and why firms can access remote knowledge by establishing a presence in the remote location. A firm endogenously decides whether to establish a presence in a remote location and if so how much autonomy to award the remote agent. The relative importance of external vs. internal knowledge in the innovative process is a key determinant of the firm's organizational structure.

This thesis groups three papers examining the role of multi-location firms in the geographic diffusion of knowledge. The first chapter examines whether a firm's headquarters can tap into the knowledge pool in a remote location through FDI. Using U.S. patent data, I show that an R&D headquarters in location “A” cites third party patents from location “B” disproportionately (relative to a control group also from location “A”) when the firm has an R&D satellite in location “B”. This “satellite effect” on knowledge diffusion is economically significant, representing 47% of the knowledge flow premium associated with collocation. Furthermore, the effect is particularly strong for new knowledge, as well as in areas of satellite technological specialization. In addition, the results show that firms with stronger cross-location, intra-firm networks experience a larger satellite effect on knowledge diffusion. The second chapter studies the effects of remote satellites on outward knowledge flow with an international development focus. I find that the presence of a foreign MNC subsidiary increases the flow of knowledge from the MNC's headquarters to local firms. This effect is largest in countries and sectors with strong but not world-class capabilities, having both the motivation and absorptive capacity to learn from foreign parties. The results suggest that emerging country governments should promote inward FDI since the knowledge brought by multinationals spills over to local firms and boosts innovative capacity. The third chapter offers a theoretical foundation for thinking about the exchange of knowledge and ideas, and the role of remote satellites. I present a model where ideas are shared through social networks as modeled by repeated agent interactions. The mechanism at once explains three broad empirical findings: why the diffusion of ideas is highly localized, why ideas flow more easily within the firm, and why firms can access remote knowledge by establishing a presence in the remote location. A firm endogenously decides whether to establish a presence in a remote location and if so how much autonomy to award the remote agent. The relative importance of external vs. internal knowledge in the innovative process is a key determinant of the firm's organizational structure.

The primary objective of this dissertation is to examine the role of corporate governance in the performance of publicly listed corporations. The normative research suggests that stronger corporate governance should lead to better market performance and a firm’s governance practice should have a positive effect on its market value. This research focuses on Chinese capital markets because of their unique characteristics with respect to elements of corporate governance.

Master of Agribusiness / Department of Agricultural Economics / Vincent Amanor-Boadu / Cargill Animal Nutrition is a global manufacturer and distributor of animal nutrition products. They operate in the United States through 6 separately managed regions that control a number of facilities throughout the entire United States. Cargill Animal Nutrition Southeast Region manages a network of eleven plants and two warehouses in the southeast part of the United States. The purpose of this thesis is to explain the current supply chain design including the relationships that exists between facilities, analyze the costs associated with the current design and relationships, and assess the feasibility of alternative designs of supply chain strategies available. A brief description of each facility along with production characteristics specific to each facility is given. Due to certain production characteristics, dependent relationships exist between certain plants. These relationships create restrictions to which our supply chain is subject. Other relationships are not as rigid and thus can be manipulated in pursuit of lowering overall supply chain costs. The model resulting from this thesis will facilitate the assessment of the feasibility of these changes. There are many costs associated with the supply chain; however, costs included in this analysis are limited to the costs that could vary when changing suppliers. The price of the product, transportation costs, and certain warehouse fees deemed relevant to this research are applied to the expected annual sales tons to reach a total cost of supply chain considering the assumptions made. The base scenario was defined according to known facts regarding the current design of our supply chain, which included identification of suppliers, supplier prices, transportation costs, and associated handling/warehouse fees, as well as determining the quantity of product that would need to flow throughout our supply chain. Then the total cost associated with the current supply chain design was assessed according to our analytical model. Once the total cost of the base scenario was determined, comparison to alternative scenarios could take place. Changing the relationships between locations of the supply chain results in alternative scenarios to which the analytical model and decision rule developed can be applied to determine feasibility of the alternative supply chain designs. Operating within the confines of the research, the total cost of the current supply chain design was determined to be $15,697,426. That total cost then serves as a base figure which can be used in comparison with the overall cost of alternative scenario #1. Scenario #1 resulted in a total cost of $15,447,597 – an annual savings of $249,828. Scenarios #2 through #4 were evaluated against the total cost of scenario #1. The total cost of scenario #2 is $15,421,364 which results in annual savings of $26,234. Scenario #3 results in a total supply chain cost of $15,347,888 which equates to annual savings of $9,710 in comparison to scenario #1. The final scenario in this study results in a total cost of $15,443,547. The annual savings generated by scenario #4 in comparison to scenario #1 are $4,050. The results indicate that there are alternative configurations of Cargill Animal Nutrition’s Southeast supply chain that can be developed to increase the competitiveness of operations and improve operational excellence through cost savings. These results are used to inform management in the implementation of the new goals that have been established for the organization. Further utilization of the tool developed will result in increased knowledge of the costs associated with supply chain design. This will allow the company to be able to understand the cost of their supply chain so they can benefit from decreased supply chain costs by reacting to changing market factors.

Master of Science / Department of Statistics / Haiyan Wang / Estimating unpaid liabilities for insurance companies is an extremely important aspect of insurance operations. Consistent underestimation can result in companies requiring more reserves which can lead to lower profits, downgraded credit ratings, and in the worst case scenarios, insurance company insolvency. Consistent overestimation can lead to inefficient capital allocation and a higher overall cost of capital. Due to the importance of these estimates and the variability of these unpaid liabilities, a multitude of methods have been developed to estimate these amounts. This paper compares several actuarial and statistical methods to determine which are relatively better at producing accurate estimates of unpaid liabilities. To begin, the Chain Ladder Method is introduced for those unfamiliar with it. Then a presentation of several Generalized Linear Model (GLM) methods, various Generalized Additive Model (GAM) methods, the Bornhuetter-Ferguson Method, and a Bayesian method that link the Chain Ladder and Bornhuetter-Ferguson methods together are introduced, with all of these methods being in some way connected to the Chain Ladder Method. Historical data from multiple lines of business compiled by the National Association of Insurance Commissioners is used to compare the methods across different loss functions to gain insight as to which methods produce estimates with the minimum loss and to gain a better understanding of the relative strengths and weaknesses of the methods. Key

Master of Agribusiness / Department of Agricultural Economics / Brian Niehoff / The purpose of this thesis was to examine the relative efficacy of the incentive plan for loan officers within Farm Credit of the Virginia’s, ACA (FCV). The purpose of FCV’s incentive plan includes promoting firm financial growth and stability, employee retention, and encouraging teamwork. Incentive plans are important financial decisions for companies and these plans have upside potential and downside risk that should be considered in the decision making process. A literature review was conducted to analyze incentive practices and management theory in addition to a review incentive plans from other Farm Credit associations. A survey was also conducted to understand loan officer perceptions of the current incentive plan at FCV. The results of the survey provide insight into employee perceptions about job satisfaction, intrinsic motivation, extrinsic motivation, organizational commitment, understanding of the incentive plan, and timing of incentives. Finally, observations with regards to potential improvement in the incentive plan were provided.

Pricing and capacity allocation are two important decisions that a service provider needs to make to maximize service quality and profit. This thesis attempts to address the pricing and capacity planning problems in operations management from the following three aspects. We first study a capacity planning and short-term demand management problem faced by firms with industrial customers that are insensitive to price incentives when placing orders. Industrial customers usually have downstream commitments that make it too costly to instantaneously adjust their schedule in response to price changes. Rather, they can only react to prices set at some earlier time. We propose a hierarchical planning model where price decisions and capacity allocation decisions must be made at different points of times. Customers first sign a service contract specifying how capacity at different times will be priced. Then, when placing an order, they choose the service time that best meets their needs. We study how to price the capacity so that the customers behave in a way that is consistent with a targeted demand profile at the order period. We further study how to optimally allocate capacity. Our numerical computations show that the model improves the operational revenue substantially. Second, we explore how a profit maximizing firm is to locate a single facility on a general network, to set its capacity and to decide the price to charge for service. Stochastic demand is generated from nodes of the network. Customers demand is sensitive to both the price and the time they expect to spend on traveling and waiting. Considering the combined effect of location and price on the firm's profit while taking into account the demand elasticity, our model provides managerial insights about how the interactions of these decision variables impact the firm's profit. Third, we extend this single facility problem to a multiple facility problem. Customers have multiple choices for service. The firm maximizes its profit subject to customers' choice criteria. We propose a system optimization model where customers cooperate with the firm to choose the facility for service and a user equilibrium model where customers choose the facilities that provide the best utility to them. We investigate the properties of the optimal solutions. Heuristic algorithms are developed for the user equilibrium model. Our results show that capacity planning and location decisions are closely related to each other. When customers are highly sensitive to waiting time, separating capacity planning and location decisions could result in a highly suboptimal solution.