Yes / We study liquidity on the London Stock Exchange. We find that the average bid-ask spread declines, but that the skewness of the spread increases. These results are robust to firm size, trading volume and price level. Our findings hold when the bid-ask spread is estimated utilising high frequency data. We find that the bid-ask spread prior to earnings announcements dates is significantly higher than that of post earnings announcements, suggesting that asymmetric information has driven the increase in liquidity skewness. We also find that the effect of earnings announcements is more pronounced in the 2007 global financial crisis, consistent with the notion that extreme market downturns amplify asymmetric information. Our overall evidence also implies that increased competition and transparent trading environments limit market makers' abilities to cross-subsidize bid-ask spreads between periods of high and low levels of asymmetric information. / National Natural Science Foundation of China (No. 71571197)

Cette thèse étudie le choix de portefeuille et l'évaluation d'actifs avec des préférences qui vont au-Delà des préférences d'espérance d'utilité et de moyenne-Variance standard. La première partie de cette thèse porte sur un modèle de décision dans lequel le décideur forme des croyances endogènes compte tenu de son utilité d'anticipation et de sa déception à posteriori. Les implications du modèle en termes de choix de portefeuille et d'évaluation d'actifs sont dérivées et comparées aux implications du modèle d'espérance d'utilité standard. La deuxième partie de cette thèse porte sur des investisseurs qui dérivent l'utilité des trois premiers moments du rendement de leur portefeuille. Nous dérivons et testons les conditions sous lesquelles des actifs supplémentaires peuvent améliorer l'univers d'investissement des investisseurs avec des préférences moyenne-variance-skewness. Les implications de ces préférences pour les rendements d'actifs à l'équilibre sont ensuite analysées et testées avec des rendements boursiers. / This thesis studies portfolio choice and asset pricing with preferences which go beyond the standard expected utility and mean-Variance preferences. The first part of this thesis analyses a decision model in which the decision maker forms endogenous beliefs given his anticipation utility and his ex-Post disappointment. Portfolio choice and asset pricing implications of the model are derived and compared to the implications of the standard expected utility framework. The second part of this thesis analyses investors choice when preferences are derived from the first three moments of portfolio returns. We derive and test the conditions under which additional assets can improve the investment opportunity set of investors with mean-Variance-Skewness preferences. The implications of these preferences for the equilibrium cross-Section of asset returns are then analyzed and tested with stock returns.

No description available.

Master of Science / Department of Electrical and Computer Engineering / Steven Warren / Handgrip contractions are a useful exercise for assessing muscle fatigue in the forearm musculature. Most conventional hand-forearm ergometer systems require the researcher to manually guide subject activity, collect subject data, and assess subject fatigue after it has occurred. Since post-processing tools are not standardized for this type of experiment, researchers resort to building their own tools. This process can make comparing results between research groups difficult. This thesis presents updates to a hand-forearm ergometer system that automate the control, data-acquisition, and data-analysis mechanisms. The automated system utilizes a LabVIEW virtual instrument as the system centerpiece; it provides the subject/researcher interfaces and coordinates data acquisition from both traditional and new sensors. The system also processes the hand-forearm data within the LabVIEW environment as the data are collected. This allows the researcher to better understand the onset of subject fatigue while an experiment is in progress. System upgrades relative to prior work include the addition of new parameters to the researcher display, a change in the subject display from a binary up-down display to a sliding bar for better control over subject grip state, and a software update from a simple data acquisition and display system to a real-time processing system. The toolset has proven to be a viable support resource for experimental studies performed in the Kansas State University Human Exercise Physiology Laboratory that target muscle fatigue in human forearms. Initial data acquired during these tests indicate the viability of the system to acquire consistent and physiologically meaningful data while providing a useable toolset for follow-on data analyses.

This thesis examines the performance of different models of conditional betas and higher comoments in the context of the cross-section of expected stock returns, both in-sample and out-of-sample. I first examine the performance of different conditional market beta models by using monthly returns of the Fama-French 25 portfolios formed by the quintiles of size and book-to-market ratio in Chapter 3. This is a cross-sectional test of the conditional CAPM. The models examined include simple OLS regressions, the macroeconomic variables model, the state-space model, the multivariate GARCH model and the realized beta model. The results show that the state-space model performs best in-sample with significant betas and insignificant intercepts. For the out-of-sample performance, however, none of the models examined can explain returns of the 25 portfolios. Next, I examine the recently proposed realized beta model, which is based on the realized volatility literature, by using individual stocks listed in the US market in Chapter 4. I extend the realized market beta model to betas of multi-factor asset pricing models. Models tested are the CAPM, the Fama-French three-factor model and a four-factor model including the three Fama-French factors and a momentum factor. Realized betas of different models are used in the cross-section regressions along with firm-level variables such as size, book-to-market ratio and past returns. The in-sample results show that market beta is significant and additional betas of multi-factor models can reduce although not eliminate the effects of firm-level variables. The out-of-sample results show that no betas are significant. The results are robust across different markets such as NYSE, AMEX and NASDAQ. In Chapter 5, I test if realized coskewness and cokurtosis can help explain the cross-section of stock returns. I add coskewness and cokurtosis to the factor pricing models tested in Chapter 4. The results show that the coefficients of coskewness and cokurtosis have the correct sign as predicted by the higher-moment CAPM theory but only cokurtosis is significant. Cokurtosis is significant not only in-sample but also out-of-sample, suggesting cokurtosis is an important risk. However, the effects of firm-level variables remain significant after higher moments are included, indicating a rejection of higher-moment asset pricing models. The results are also robust across different markets such as NYSE, AMEX and NASDAQ. The overall results of this thesis indicate a rejection of the conditional asset pricing models. Models of systematic risks, i.e. betas and higher comoments, cannot explain the cross-section of expected stock returns.

We examine the economic behavior of the regret-averse firm under price uncertainty. We show that the global and marginal effects of price uncertainty on production are both positive (negative) when regret aversion prevails if the random output price is positively (negatively) skewed. In this case, high (low) output prices are much more likely to be seen than low (high) output prices. To minimize regret, the firm is induced to raise (lower) its output optimal level. The skewness of the price distribution as such plays a pivotal role in determining the regret-averse firm\'s production decision.

In this thesis we study models, which search for an optimal portfolio from a set of stocks. On the contrary to the classical approach focusing only on expected return and variance, we examine models where an additional crite- rion of skewness is included. Furthermore we formulate a model for measuring performance of a portfolio defined as the distance from the Pareto efficient frontier. In numerical experiments we apply the models on historical prices and stock data from the electronic stock market NASDAQ. We analyze the stock data from companies listed in the index NASDAQ-100. We conclude by comparing of optimal portfolios created using different models among each other, with trivial single-stock portfolios and the with NASDAQ-100 index itself.

This thesis analyzes the use of realized moments in asset pricing. The analysis is done using dataset containing log-returns for 29 of the most traded stocks and covering 10 years of data. The dataset is split into training set covering 7 years and test set covering 3 years of data. For each of the stocks a separate time series model is estimated. In evaluation of the quality of the models, metrics such as RMSE, MAD, accuracy in forecasting the sign of future returns, and returns achievable by executing trades based on the recommendations from the model are used. Even though the inclusion of realized moments does not provide significant improvements in terms of RMSE, it is found that realized skewness and kurtosis significantly contribute to explaining the returns of individual stocks as they lead to consistent improvements in identifying future positive, as well as negative, returns. Moreover, the recommendations from the models using realized moments can help us achieve significantly higher returns from trading stocks. Inclusion of the interaction terms for variance and returns, skewness and returns, and kurtosis and variance, provides additional improvement of forecasting accuracy, as well as improvements in returns achievable by executing transactions based on recommendations from the model....

A utilização do modelo de Black-Scholes e suas extensões na precificação de opções é bastante difundida tanto na academia quanto no mercado financeiro. O objetivo deste trabalho foi avaliar o desempenho de um modelo alternativo de precificação de opções em relação ao do modelo de Black na precificação de opções sobre futuro de dólar. Mais especificamente, a partir de hipóteses sobre o comportamento agregado da economia, da trajetória de preços de ativos e das preferências a risco dos agentes econômicos, é possível reconciliar uma condição de equilíbrio parcial, necessária para a precificação de opções, com uma condição de equilíbrio geral da economia. Essa reconciliação é obtida a partir da escolha cuidadosa de pares de preferências a risco e distribuições e possibilita a obtenção do preço de equilíbrio livre de preferências de um derivativo lançado sobre um dado ativo-objeto. O presente estudo utiliza os resultados de uma generalização recente feita por Câmara (2003), que demonstrou como distribuições e preferências podem ser combinadas de forma que se obtenham fórmulas fechadas para precificação de opções. Particularmente, assume-se que os preços do contrato futuro de dólar possuem distribuição lognormal com assimetria negativa, hipótese que resulta em uma fórmula alternativa de precificação de opções lançadas sobre esse contrato. O modelo obtido foi matematicamente contrastado com o modelo de Black, o que possibilitou que as implicações nos preços das opções, resultantes da premissa de assimetria negativa, fossem evidenciadas. Os desempenhos dos modelos foram comparados com base nos preços de mercado das opções. Os resultados alcançados sugerem que , em geral, o modelo de Black apresenta desempenho melhor que o modelo alternativo na precificação de opções sobre futuro de dólar. / The utilization of the Black-Scholes option pricing model is widespread, in both the academe and the market. Additionally, the literature related to its generalizations and adaptations is vast. Of particular importance are works concerning new sufficient conditions for existing risk-neutral option pricing equations. Under a new set of propositions on distributions and preferences, Câmara (2003) derived new analytical solutions for the price of European-style contingent claims. The objective of the present study was to adapt and test an option pricing model that was derived by Câmara (2003). Particularly, the tested model assumes that the underlying asset, in this case the US dollar futures contract traded on the Brazilian Mercantile & Futures Exchange, follows a negatively skew lognormal distribution. The performance of the alternative model was compared to that of the Black model, the standard model used in the market to price such options. More specifically, the performances of both models were measured against the market prices of US dollar futures options. Also, considerations about the validity of the negative skew lognormal hypothesis were made and a mathematical analysis of the differences in the prices generated by the two models was carried out. In the end, although the alternative model produces, in some cases, prices that are closer to the market’s, the evidences suggest that, in general, the Black model performs better than the alternative one.

O Objetivo deste trabalho é usar uma ferramenta matemática conhecida como expansão de Edgeworth em conjunto com a moderna teoria de análise de derivativos financeiros que utilizam o método de precificação neutra ao risco. Tal expansão permite obter uma função densidade de probabilidade com assimetria e curtose arbitrárias a partir de uma densidade normal. Desta forma, podemos usar esta nova distribuição como a state price density do ativo-objeto procurando corrigir o sorriso da volatilidade através da definição de funções de probabilidade com assimetrias positivas ou negativas e curtose maior de que três. Além disso esperamos também chegar a uma nova maneira de realizar o delta hedge de uma carteira de replicação de modo mais eficiente do que a de Black-Scholes. / There is a well-developed framework, the Black?Scholes theory, for the pricing of contracts based on the future prices of certain assets, called options. This theory assumes that the probability distribution of the returns of the underlying asset is a Gaussian distribution. However, it is observed in the market that this hypothesis is 2awed, leading to the introduction of a fudge factor, the so-called volatility smile. Therefore, it would be interesting to explore extensions of the Black?Scholes theory to non-Gaussian distributions. In this paper, we provide an explicit formula for the price of an option when the distributions of the returns of the underlying asset is parametrized by an Edgeworth expansion, which allows for the introduction of higher independent moments of the probability distribution, namely skewness and kurtosis. We test our formula with options in the Brazilian and American markets, showing that the volatility smile can be reduced. We also check whether our approach leads to more e6cient hedging strategies of these instruments.