No description available.

No description available.

No description available.

No description available.

Abstract This thesis project is divided in two parts. The first part examines the possibility that correlation matrix estimates based on an outlier sample would contain information about extreme events. According to my findings, such methods do not perform better than simple shrinkage methods where robust shrinkage targets are used. The method tested is especially outperformed when it comes to the extreme events, where a shrinkage of the correlation matrix towards the identity matrix seems to give the best result. The second part is about valuation of skewness in marginal distributions and the penalizing of heavy tails. I argue that it is reasonable to use a degrees of freedom parameter instead of kurtosis and a certain regression parameter, that I develop, instead of skewness due to robustness issues. When minimizing the one period draw-down is our target, the "value" of skewness seems to have a linear relationship with expected returns. Re-valuing of expected returns, in terms of skewness, in the standard Markowitz framework will tend to lower expected shortfall (ES), increase skewness and lower the realized portfolio variance. Penalizing of heavy tails will most times in the same way lower ES, lower kurtosis and realized portfolio variance. The results indicate that the parameters representing higher order moments in some way characterize the assets and also reflect their future behavior. These properties can be used in a simple optimization framework and seem to have a positive impact even on portfolio level

Les barres sableuses pré-littorales ont un rôle fondamental en morphodynamique des plages soumises à l’action des vagues. Le déséquilibre permanent entre les flux sédimentaires induits vers laplage par les non linéarités des vagues et ceux induits vers le large par le courant de retour gouverne lamigration transversale des barres. Dans cette thèse, un nouveau modèle morphodynamique de profilde plage intégrant l’état de l’art des processus hydro-sédimentaires a été développé. Le faible coûten temps de calcul de ce modèle permet de réaliser des simulations à long terme, O(mois/années),de la morphologie de plages réelles ayant des caractéristiques variées (pente, type de déferlement,granularité). La simulation sur plusieurs jeux de données, de plages réelles et expérimentales, a permisd’identifier la contribution respective des principaux processus hydro-sedimentaires dans la dynamiquede la plage suivant les conditions de houle (e.g. Tempête, temps calme). Ces avancées scientifiques ontété intégrées à un modèle 2DH, ce qui a notamment permis de simuler pour la première fois sur des casacadémiques la formation d’une barre sableuse rectiligne à partir d’une plage parfaitement plane, suiviedu développement de corps sableux tridimensionnels. Ces résultats ouvrent la voie vers l’applicationde ce type de modèle aux plages naturelles soumises à une large variabilité de régimes de houle. / Sandbars are ubiquitous patterns along wave-dominated sandy coastlines and are key elementsin the global evolution of beaches. Cross-shore sandbar migrations are the result of the permanentimbalance between sediment flux driven by wave non-linearity and mean return current. In this thesis,we developed a new process-based beach profile model integrating the recent scientific advancesin term of hydrodynamics and sediment transport developed for beach morphodynamics. The lowcomputing time allows for long-term morphodynamic simulations (O months/years) of natural beachprofiles of diverse characteristics (beach slope, sediment grain size or type of wave breaking). Modelvalidations on several data sets, encompassing natural and experimental beach profile evolutions,highlight the respective contribution of the main hydrodynamic and sediment transport processesinvolved in specific cross-shore sandbar evolution relative to various wave conditions. Finally, all thecross-shore physical processes were integrated in a 2DH morphodynamic model, resulting for the firsttime in the simulation of a quasi-complete down state sequence showing alongshore bar generationwith subsequent spontaneous formation of transverse bar and rip morphology. These very encouragingresults pave the way for using this model to simulate 3-Dimensional evolutions of natural beachesforced by irregular wave conditions

The work presented in this dissertation can be grouped around three major themes. The first theme relates to risk, the second theme relates to asset pricing, whereas the third theme relates to serial correlation of asset returns. The three chapters of this dissertation investigate these themes Chapter Two analyses the behavior over time of market risk, aggregate idiosyncratic risk and correlations in portfolio of Taiwan listing stocks and studied pattern of aggregate correlation between the 3 most important Taiwan stock index and Taiwan value-weighted index. We find (1) Idiosyncratic risk is trended upwards; (2) The conditional stock returns correlation process is asymmetric. The implication of our finding is (1) It takes more stocks to achieve a given level of diversification; (2) Diversification strategies perform poorly in bear markets. Chapter Three investigates the role of the asset co-skewness and conditioning information in asset pricing. First, I estimate long-run predictive regressions of asset returns to test whether aggregate idiosyncratic risk is a price factor of industrial returns. Then I use data on Taiwan 19 industry portfolios to fit various assets pricing models. I find (1) the cross-sectional ctional correlation between 2 i £] (the gamma coefficient from the 3M-CAPM equation) and 3 i ϕ (the interaction coefficient from the CCAPM equation) is positive and fairly large. (2) The firm-level volatility is a good proxy for cay as conditioning information variable. (3) The gamma coefficient can pick up the extent of beta co-vary with the market wide excess-return over the business cycle. (4)among 19 industrial returns, the 2 industrial returns can be explained by 3M-CAPM; the 7 industrial returns can be explained by CCAPM; the 5 industrial returns can be explained by 3M-CAPM+CCAPM, Others can¡¦t be explained by either of three models. Chapter Four examines the impact of positive feedback trading behavior of the investors on the short-term dynamics of return for four Taiwan index futures contracts by utilizing the framework of the model developed by Sentana & Wadhwani(1992). Use of the Asymmetric Nonlinear Smooth Transition GARCH Model demonstrates that positive feedback trading of investors is the main determinant of short-term dynamics of return for Taiwan index futures contracts. Moreover, it shows that positive trading is more intense during market declines than it is during market advances due to extensive use of spot-loss trading for investors. Finally it is shown that the sophisticated professional investors intend to take positive feedback trades wave so that they lead to increase positive feedback trading in Taiwan index futures since the government opened the enterprises for managed futures.

The purpose of this thesis is to propose some test statistics for testing the skewness and kurtosis parameters of a distribution, not limited to a normal distribution. Since a theoretical comparison is not possible, a simulation study has been conducted to compare the performance of the test statistics. We have compared both parametric methods (classical method with normality assumption) and non-parametric methods (bootstrap in Bias Corrected Standard Method, Efron’s Percentile Method, Hall’s Percentile Method and Bias Corrected Percentile Method). Our simulation results for testing the skewness parameter indicate that the power of the tests differs significantly across sample sizes, the choice of alternative hypotheses and methods we chose. For testing the kurtosis parameter, the simulation results suggested that the classical method performs well when the data are from both normal and beta distributions and bootstrap methods are useful for uniform distribution especially when the sample size is large.

This thesis makes a number of contributions in the derivative pricing and risk management literature and to the growing literature that exploits information embedded in option prices. First, it develops an effective numerical scheme for importance sampling scheme of Fouque and Tullie (2002) based on a 2-dimensional lookup table of stock price and time to maturity that dramatically improves the speed of this importance sampling scheme. Second, the thesis presents an application of this importance sampling scheme in a Multi-Level Monte Carlo simulation. Such combination yields greater variance reduction compared to Multi-Level Monte Carlo or importance sampling alone. Third, it demonstrates how the Greeks can be computed using the Likelihood Ratio Method based on characteristic function, and how combining it with importance sampling leads to a significant variance reduction for the Greeks. Finally, it documents the positive relationship between the risk-neutral skewness (RNS) and future realized stock returns that is driven by the underperformance of highly negative RNS portfolio. The results provide strong evidence that the underperformance of stocks with the lowest RNS is driven by those stocks that are associated with a higher hedging demand, relative overvaluation and are also too costly or too risky to sell short. Moreover, by decomposing RNS into its systematic and idiosyncratic components, this thesis shows that the latter drives the positive relationship with future realized stock returns.

Military aircraft generate high-amplitude noise which can cause injury to attending personnel. Efforts to mitigate the effects of this noise require a detailed understanding of the propagation of the noise, which was shown previously to be nonlinear. This thesis presents an analysis of high-amplitude noise propagation, emphasizing measures used to quantify the importance of considering nonlinearity. Two measures of the importance of nonlinearity are compared. These measures are the wave steepening factor and a skewness estimate. The wave steepening factor is a measure of how much nonlinear waveform steepening has occurred in a waveform. The skewness estimate is the skewness of the first time-derivatives of the pressure amplitudes, and can be considered a measure of the shock content in a waveform. These two measures are analyzed analytically in terms of the Earnshaw, Fubini, Fay, and Khokhlov solutions to the Burgers equation. In addition, an analysis of how discrete sampling affects the estimation of these quantities is also presented. It is determined that the wave steepening factor is robust with respect to low sampling rates, but the skewness of the first time-derivatives of the pressure amplitudes is not robust, and requires very large sampling rates to be adequately estimated. Using numerical and experimental techniques, the two nonlinearity measures are applied to more complicated waveforms, such as Gaussian noise and noise with jet noise-like statistics. It is found that the evolution of the two nonlinearity measures discussed above for noise signals is distinctive in various ways. In particular, the skewness of the first time derivative of the pressure amplitudes suggest that noise waveforms experience nonlinear phenomena faster than initially sinusoidal signals, while the wave steepening factor suggests that they occur at approximately the same rate. The measures are then applied to full-scale military aircraft. By comparing these nonlinearity metrics with the results of the analytical, numerical, and experimental results found in this thesis, it is determined that nonlinearity is likely to be significant in the near field of a military aircraft at military and afterburner engine conditions.