Insider trading may convey information to the market and promote accurate pricing of stocks. In this dissertation, I investigate insider trading at the turn of the century. In the first essay, I investigate insider trading activity in technology stocks during the high price - high volatility period of the late 1990s. I document that insiders of technology firms were heavy sellers during the ten month pre-peak period in which stock prices more than doubled. The technology stocks that were sold by insiders more extensively in the pre-peak period had lower returns in the post-peak period. I furthermore investigate the relation between the net order flows (buyer initiated minus seller initiated trades) and abnormal insider trading activity. I document that the net order flow is positively related to abnormal insider trading activity. However, this positive relation becomes weaker in the peak period; which implies less price discovery through insider trading during the rise of technology stock prices. In the second essay, I document that disclosure requirements significantly affect insider trading behavior. The Sarbanes-Oxley Act of 2002 requires expedited and on-line disclosure of insider transactions. This increase in the visibility of insider trading reduces informational advantage of insiders and increases the likelihood of facing legal sanctions for insiders. I document that insider purchases significantly declined after the Sarbanes- Oxley Act. In addition, the incidences of insider purchases (sales) prior to positive (negative) earnings surprises declined after the Act. Finally, I document that the earnings announcements become more informative after the Act, which is consistent with less price discovery through insider trading prior to earnings announcements. However, the evidence that the decline in insider trading contributes to more informative earnings announcements is pronounced for insider purchases but not for insider sales.

This paper measures the channels by which private information is incorporated in prices in the equity and option markets. Using a mispricing events approach and conditioning on the option market being the cause of the mispricing event, I analyse the subsequent behaviour of both the options and equity markets and I find that options markets play an important role in the price discovery process. When conditioning on option caused mispricing events, the equity price adjusts towards the options price to reconcile the prices. I find that around 40% of the option caused mispricing events contain information, and the equity prices adjust 35-40%, depending on the exchange, of the maximum discrepancy before prices reconcile. When the equity market causes the mispricing, the option market follows due to the autoquote mechanism. Additionally, I use Monte Carlo to assess the suitability of the Hasbrouck (1995) Information Share and Gonzalo-Granger (1995) Component Share measures in the option-equity context. I find that neither metric is suitable, however the Putnins (2013) Information Leadership metric is and the options market has on average a 35% information leadership share.

This study shows that investor sentiment plays an important role in affecting the pricing dynamics between the spot and futures markets. The empirical evidence suggests that investor sentiment has a positive impact on price volatility and the bid–ask spread on both the spot and futures markets, which induces higher arbitrage risk and trading costs during high sentiment periods. As a consequence, during high sentiment periods, informed traders become less willing to leverage their information advantages on the futures market, which diminishes the futures markets’ leading informational role and contributions to price discovery. My findings provide support for the theory of limits to arbitrage.

Foreign exchange market is the most active market in today’s global financial domains. While the consensus on several aspects of this market is fairly established, the informational efficiency in this market is still unsettled, particularly during unexpected interruptions and unusual or unstable periods. The financial crisis of 2008 is the most recent example of such a period. This dissertation focuses on the efficiency of the foreign exchange market during a unique, turbulent period using the six most actively traded currencies: the Australian dollar, Canadian dollar, Swiss franc, Euro, British pound, and Japanese yen. Considering nine months before the peak of the financial crisis to nine months thereafter, the entire sample is divided into three sub-samples: full-, non-crisis-, and crisis-periods. Both daily and minute-by-minute data are used. A variety of instruments are analyzed, including spot, forward, and exchange traded funds on the currencies. The methodologies that are employed range from standard econometric tests of efficiency to estimation of vector error correction models to identify price discovery, or leadership positions, in each of the currency markets. The findings indicate behavioral similarities and differences. The patterns of the volatility of the currencies are mixed: two-humped for the AUD, CAD, and EUR; W-shaped for the CHF; three-humped for the GBP, and flat U-shaped for the JPY. The daily results from several methodologies provide mixed evidence on market efficiency. Over the entire sample period, the estimated forward premium coefficients from the GARCH (1, 1) model are not significant for all currencies, while the null hypotheses of zero and one cointegrating vectors cannot be rejected for all currencies, except for the AUD. These findings are consistent with some of the previous studies, concluding that the efficiency tests in the foreign exchange market would depend on the methodology and the time period of the study. The high frequency data results show different degrees of price discovery between pair-wise instruments. Specifically, the spot exchange market shows a greater contribution to price discovery than the corresponding exchange traded funds. A possible explanation is the current size of the market and its increased transparency through the use of electronic trading.

Theoretical models suggest that ownership structure may be an important determinant of securities' market characteristics. For example, the presence of informed traders leads to greater bid-ask spreads (Copeland and Galai (1983), and Glosten and Milgrom (1985)), and strategic trading of informed and discretionary liquidity traders leads to intertemporal variation in both trading volume and trading costs (Admati and Pfleiderer (1988), and Foster and Viswanathan (1990)). However, the empirical studies on the effect of ownership structure on market characteristics are limited. Prior studies focus on either one type of market characteristics or one type of owners, and usually do not address the potential endogeneity problem between market characteristics and ownership structure. This dissertation extends existing literature with two essays on ownership and market characteristics. The first essay broadly examines the effect of ownership structure (inside ownership, institutional ownership, and individual ownership) on market characteristics such as order flow, price impact of trade, quoted spread and quoted depth. For each market characteristic examined, I establish an empirical model based on existing theories and empirical evidence. My results indicate that stocks with greater inside ownership have lower order flow, greater price impact of trade, greater quoted spread and lower quoted depth, while stocks with greater active institutional ownership and greater individual shareholders have greater order flow, smaller price impact of trade, lower spread and greater depth. These results may have implications for corporate governance. For example, while agency theory suggests managerial ownership may align interests of managers and shareholders, this essay finds that this comes with a liquidity cost. Further, my results suggest there are liquidity benefits of individual and institutional ownership. If as suggested by Amihud and Mendelson (1989), investors require a higher rate of return for illiquid stocks, firms can target their shares to specific types of investors (for example, active institutions and individuals) to improve liquidity, and reduce their cost of capital. The second essay is a specific application of the first essay and examines the effect of institutional ownership on price discovery around earnings announcements. I select earnings announcements as the event for my analysis because there are three well-documented regularities about earnings announcements. First, market participants anticipate the forthcoming earnings announcements. Second, the announcements of earnings news are usually accompanied by abnormal price changes and abnormal volume. Third, there is evidence that stock price continues to move in the direction of earnings surprise after the announcements of earnings news. Since results from the first essay suggest that institutional investors affect market characteristics such as price impact of trade and quoted spread, I expect that institutional participation would also affect the price discovery process around earnings announcements. My results indicate that institutional ownership is associated with greater anticipation of earnings news. Further, stocks with greater institutional ownership have a greater price response to announcements of earnings news. Finally, institutional investors have no significant effect on post-announcement drift. The results of the second essay suggest that institutional investors contribute to the price discovery process. / Ph. D.

No / We examine how information risk and transaction costs influence the initial and subsequent market reaction to earnings news. We find that the initial market reaction is higher per unit of earnings surprise for higher information risk firms (information content effect). Furthermore, it is information risk that induces transaction costs that limit the initial market reaction and lead to higher subsequent drift (transaction costs effect). Information risk does not have an effect on drift beyond that achieved through transaction costs. Our findings highlight the importance of understanding the linkage between information risk and transaction costs in price discovery around public disclosure.

El risc de crèdit s'associa a l'eventual incompliment de les obligacions de pagament per part dels creditors. En aquest cas, l'interès principal de les institucions financeres és mesurar i gestionar amb precisió aquest risc des del punt de vista quantitatiu. Com a resposta a l'interès esmentat, aquesta tesi doctoral, titulada "Structural Credit Risk Models: Estimation and Applications", se centra en l'ús pràctic dels anomenats "models estructurals de risc de crèdit". Aquests models es caracteritzen perquè estableixen una relació explícita entre el risc de crèdit i diverses variables fonamentals, la qual cosa permet un ventall ampli d'aplicacions. Concretament, la tesi analitza el contingut informatiu tant del mercat d'accions com del mercat de CDS sobre la base dels models estructurals esmentats.El primer capítol, estudia la velocitat distinta amb què el mercat d'accions i el mercat de CDS incorporen nova informació sobre el risc de crèdit. L'anàlisi se centra a respondre dues preguntes clau: quin d'aquests mercats genera una informació més precisa sobre el risc de crèdit i quins factors determinen el diferent contingut informatiu dels indicadors respectius de risc, és a dir, les primes de crèdit implícites en el mercat d'accions enfront del de CDS. La base de dades utilitzada inclou 94 empreses (40 d'europees, 32 de nordamericanes i 22 de japoneses) durant el període 2002-2004. Entre les conclusions principals destaquen la naturalesa dinàmica del procés de price discovery, una interconnexió més gran entre ambdós mercats i un major domini informatiu del mercat d'accions, associat a uns nivells més elevats del risc de crèdit, i, finalment, una probabilitat més gran de lideratge informatiu del mercat de CDS en els períodes d'estrès creditici.El segon capítol se centra en el problema de l'estimació de les variables latents en els models estructurals. Es proposa una nova metodologia, que consisteix en un algoritme iteratiu aplicat a la funció de versemblança per a la sèrie temporal del preu de les accions. El mètode genera estimadors de pseudomàxima versemblança per al valor, la volatilitat i el retorn que s'espera obtenir dels actius de l'empresa. Es demostra empíricament que aquest nou mètode produeix, en tots els casos, valors raonables del punt de fallida. A més, aquest mètode és contrastat d'acord amb les primes de CDS generades. S'observa que, en comparació amb altres alternatives per fixar el punt de fallida (màxima versemblança estàndard, barrera endògena, punt d'impagament de KMV i nominal del deute), l'estimació per pseudomàxima versemblança proporciona menys divergències.El tercer i darrer capítol de la tesi tracta la qüestió relativa a components distints del risc de crèdit a la prima dels CDS. Més concretament, estudia l'efecte del desequilibri entre l'oferta i la demanda, un aspecte important en un mercat on el nombre de compradors (de protecció) supera habitualment el de venedors. La base de dades cobreix, en aquest cas, 163 empreses en total (92 d'europees i 71 de nord-americanes) per al període 2002- 2008. Es demostra que el desequilibri entre l'oferta i la demanda té, efectivament, un paper important a l'hora d'explicar els moviments a curt termini en els CDS. La influència d'aquest desequilibri es detecta després de controlar l'efecte de variables fonamentals vinculades al risc de crèdit, i és més gran durant els períodes d'estrès creditici. Aquests resultats il·lustren que les primes dels CDS reflecteixen no tan sols el cost de la protecció, sinó també el cost anticipat per part dels venedors d'aquesta protecció per tancar la posició adquirida. / El riesgo de crédito se asocia al potencial incumplimiento por parte de los acreedores respecto de sus obligaciones de pago. En este sentido, el principal interés de las instituciones financieras es medir y gestionar con precisión dicho riesgo desde un punto de vista cuantitativo. Con objeto de responder a este interés, la presente tesis doctoral titulada "Structural Credit Risk Models: Estimation and Applications", se centra en el uso práctico de los denominados "Modelos Estructurales de Riesgo de Crédito". Estos modelos se caracterizan por establecer una conexión explícita entre el riesgo de crédito y diversas variables fundamentales, permitiendo de este modo un amplio abanico de aplicaciones. Para ser más explícitos, la presente tesis explora el contenido informativo tanto del mercado de acciones como del mercado de CDS sobre la base de los mencionados modelos estructurales.El primer capítulo de la tesis estudia la distinta velocidad con la que el mercado de acciones y el mercado de CDS incorporan nueva información sobre el riesgo de crédito. El análisis se centra en contestar dos preguntas clave: cuál de estos mercados genera información más precisa sobre el riesgo de crédito, y qué factores determinan en distinto contenido informativo de los respectivos indicadores de riesgo, esto es, primas de crédito implícitas en el mercado de acciones frente a CDS. La base de datos utilizada engloba a 94 compañías (40 europeas, 32 Norteamericanas y 22 japonesas) durante el periodo 2002-2004. Entre las principales conclusiones destacan la naturaleza dinámica del proceso de price discovery, la mayor interconexión entre ambos mercados y el mayor dominio informativo del mercado de acciones asociados a mayores niveles del riesgo de crédito, y finalmente la mayor probabilidad de liderazgo informativo del mercado de CDS en los periodos de estrés crediticio.El segundo capítulo se centra en el problema de estimación de variables latentes en modelos estructurales. Se propone una nueva metodología consistente en un algoritmo iterativo aplicado a la función de verosimilitud para la serie temporal del precio de las acciones. El método genera estimadores pseudo máximo verosímiles para el valor, volatilidad y retorno esperado de los activos de la compañía. Se demuestra empíricamente que este nuevo método produce en todos los casos valores razonables del punto de quiebra. El método es además contrastado en base a las primas de CDS generadas. Se observa que, en comparación con otras alternativas para fijar el punto de quiebra (máxima verosimilitud estándar, barrera endógena, punto de impago de KMV, y nominal de la deuda), la estimación por pseudo máxima verosimilitud da lugar a las menores divergencias.El tercer y último capítulo de la tesis aborda la cuestión relativa a componentes distintos al riesgo de crédito en la prima de los CDS. Se estudia más concretamente el efecto del desequilibrio entre oferta y demanda, un aspecto importante en un mercado donde el número de compradores (de protección) supera habitualmente al de vendedores. La base de datos cubre en este caso un total de 163 compañías (92 europeas y 71 norteamericanas) para el periodo 2002-2008. Se demuestra que el desequilibrio entre oferta y demanda tiene efectivamente un papel importante a la hora de explicar los movimientos de corto plazo en los CDS. La influencia de este desequilibrio se detecta una vez controlado el efecto de variables fundamentales ligadas al riesgo de crédito, y es mayor durante los periodos de estrés crediticio. Estos resultados ilustran que las primas de los CDS reflejan no sólo el coste de la protección, sino el coste anticipado por parte de los vendedores de tal protección de cerrar la posición adquirida. / Credit risk is associated with potential failure of borrowers to fulfill their obligations. In that sense, the main interest of financial institutions becomes to accurately measure and manage credit risk on a quantitative basis. With the intention to respond to this task this doctoral thesis, entitled "Structural Credit Risk Models: Estimation and Applications", focuses on practical usefulness of structural credit risk models that are characterized with explicit link with economic fundamentals and consequently allow for a broad range of application possibilities. To be more specific, in essence, the thesis project explores the information on credit risk embodied in the stock market and market for credit derivatives (CDS market) on the basis of structural credit risk models. The issue addressed in the first chapter refers to relative informational content of stock and CDS market in terms of credit risk. The overall analysis is focused on answering two crucial questions: which of these markets provides more timely information regarding credit risk, and what are the factors that influence informational content of credit risk indicators (i.e. stock market implied credit spreads and CDS spreads). Data set encompasses international set of 94 companies (40 European, 32 US and 22 Japanese) during the period 2002-2004. The main conclusions uncover time-varying behaviour of credit risk discovery, stronger cross market relationship and stock market leadership at higher levels of credit risk, as well as positive relationship between the frequency of severe credit deterioration shocks and the probability of the CDS market leadership.Second chapter concentrates on the problem of estimation of latent parameters of structural models. It proposes a new, maximum likelihood based iterative algorithm which, on the basis of the log-likelihood function for the time series of equity prices, provides pseudo maximum likelihood estimates of the default barrier and of the value, volatility, and expected return on the firm's assets. The procedure allows for credit risk estimation based only on the readily available information from stock market and is empirically tested in terms of CDS spread estimation. It is demonstrated empirically that, contrary to the standard ML approach, the proposed method ensures that the default barrier always falls within reasonable bounds. Moreover, theoretical credit spreads based on pseudo ML estimates offer the lowest credit default swap pricing errors when compared to the other options that are usually considered when determining the default barrier: standard ML estimate, endogenous value, KMV's default point, and principal value of debt.Final, third chapter of the thesis, provides further evidence of the performance of the proposed pseudo maximum likelihood procedure and addresses the issue of the presence of non-default component in CDS spreads. Specifically, the effect of demand-supply imbalance, an important aspect of liquidity in the market where the number of buyers frequently outstrips the number of sellers, is analyzed. The data set is largely extended covering 163 non-financial companies (92 European and 71 North American) and period 2002-2008. In a nutshell, after controlling for the fundamentals reflected through theoretical, stock market implied credit spreads, demand-supply imbalance factors turn out to be important in explaining short-run CDS movements, especially during structural breaks. Results illustrate that CDS spreads reflect not only the price of credit protection, but also a premium for the anticipated cost of unwinding the position of protection sellers.

Master of Science / Department of Agricultural Economics / Ted C. Schroeder / Very rapid growth in the ethanol industry has led to a void of information regarding price dynamics and utilization of distiller's grains. Understanding market conditions is essential for livestock producers to make informed decisions in the procurement of feedstuffs, especially as grain price levels have recently increased substantially. In this study, distiller's grain price discovery dynamics are evaluated to develop an understanding of spatial price relationships. The knowledge of price relationships reveals that users of distiller's grain should shop around when procuring the feedstuff. Additionally, because animal performance may be altered with increased inclusion of distiller's grains, regional competitive advantages could shift fed cattle production to geographic regions characterized by high of ethanol production plants. Therefore, the cost of current grain processing methods are evaluated to enhance the awareness of regional competitiveness and long term sustainability. The combination of these two objectives allows producers to better realize the implications of the ethanol industry on their ability to maintain their operations into the near future.

In Chapter 1, I hypothesize that there is a differential response by agents to changes in sovereign credit or default risk in both quiet (low default risk) and turbulent markets (high default risk). These market conditions create two different states of the market (world) or regimes. Investors and policy makers respond differently in the two regimes but the response in the turbulent market condition is amplified as policy makers attempt to smoothen the fluctuations and uncertainty while investors rebalance their portfolios in an attempt to hedge against downside risk of wealth loss. In the two regimes, the short run and long run dynamic relationships between any two cointegrated assets may change. To capture this phenomenon, this study tests for nonlinearities that may characterize the regimes, how cointegration relationships, short term dynamic interaction and price discovery (speed of adjustment to new information between two assets) may change in alternative regimes. To this end, I employ threshold cointegration, threshold vector error correction model (TVECM) asymmetrical return spillover modeling for sovereign credit default swaps (CDS), bonds and equity markets of seventeen emerging markets from four geographical regions. I find that there is non-linear cointegration and momentum in long-run adjustment process in 43/51 spreads analyzed. All countries analyzed have at least 2/6 possible regime specific asymmetric price discovery process. The study also finds evidence in support of asset substitution hypothesis and news-based hypothesis of financial contagions in sovereign CDS, bond and equity markets. The findings have important implications for asset allocation and portfolio rebalancing decisions by investors, policy intervention in financial markets, risk management and regime specific short and/or long term dynamic interactions among assets held in a portfolio as well as nonlinear speed of adjustment to new information. In chapter 2, I hypothesize that financial intermediaries can be categorized into bank-based institutions (BBIs) and market-based institutions (MBIs). MBIs and BBIs are under different regulatory agencies. Traditionally, only BBIs, regulated by the Fed, are used as conduits of transmitting liquidity and monetary policy into real economy and financial markets yet MBIs also play important role in providing liquidity and stability in financial markets. I use two tools of monetary policy (Federal fund rate and monetary aggregate) under two monetary policy regimes to investigate the impact of monetary policy under each regime on the liquidity of MBIs and BBIs. I investigate whether MBIs be used as conduits of transmitting monetary policy and liquidity in the market and if they should, under what economic and financial conditions (Regimes) should they be used. Moreover, what monetary policy tool is more effective for MBIs relative to BBIs under different regimes? Using Threshold vector auto-regressions and regime specific impulse response functions, I find that liquidity of BBIs and MBIs respond differently to different monetary policy tools under different regimes. Moreover, monetary policies are uncertain and vary over time. The Fed cannot continue to ignore MBIs in formulating and implementing monetary policy. Moreover, monetary aggregate policy is more effective when used on MBIs during contractionary monetary policy intervention (economic downturn) while Federal fund rate is more effective when used on BBIs under expansionary monetary policy.

abstract: 中医药是中华文明的瑰宝，中药材是中医药文化和产业的核心。随着近年来国家相关政策出台，中药材产业的发展备受瞩目。由于中药材产业链条长，层级多，各层级间信息不对称，因而中药材市场普遍具有“假”、“乱”、“杂”的问题。 A公司的中药材全产业链服务商模式，通过对上游各主要专营商的整合，形成一定的平台综合集采能力，并开始得到下游医药厂家、药店认可，在市场逐步形成品牌号召力。本文实证研究A公司商业模式的转型对中药材市场价格的影响，进而分析中药材全产业链服务商模式在中药材行业健康发展中所发挥的积极作用。研究结果表明，上下游产销结合的中药材全产业链服务商模式，只有在形成一定收购规模，对市场价格产生一定影响的时候，才能充分释放药材质量的信号，润滑药材交易市场，提高收购价格，增加市场波动率，发挥价格发现作用。由于中药材市场的信息不对称程度较高，如果产销结合模式仍处于初级开创阶段，产销结合模式释放的药材质量信号则不足以全面改善信息不对称的状况。 / Dissertation/Thesis / Doctoral Dissertation Business Administration 2019