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Ces travaux de thèse s’intéressent aux outils de simulation rapide de la fabrication d’un pneumatique. L'objectif est de prédire le mouvement et la position des éléments constitutifs du pneumatique, lors de leur mise en conformation, en prenant en compte les déformations induites par les actions mécaniques associées. Ces travaux s’appuient sur la mise en place d’un algorithme visant à modéliser le gonflement d’un outillage et la mise en place d’un modèle de déformation d’un système de formes géométriques aux caractéristiques mécaniques différentes. L'algorithme de gonflement de l’outillage se base sur la théorie des membranes inextensibles et son industrialisation est validée pour des dimensions standards de pneumatiques. La méthode Masse-Ressort est retenue pour réaliser la déformation de formes géométriques afin d’obtenir des résultats de déformation en temps réel. Dans ces travaux, cette méthode est adaptée aux matériaux d’un pneumatique à partir de travaux de caractérisations géométrique et mécanique validés par comparaison aux Éléments Finis. En conclusion, la modélisation développée permet une description à chaque étape du procédé de fabrication. / This thesis deals with fast simulation tools used to manufacture of a tire. The goal is to predict the displacement and position of the components of a tire taking into account the deformations induced by the associated mechanical actions. This work is based on the implementation of an algorithm for modeling the inflation of a tool and the development of a deformation model in order to compute the deformation of geometric shapes taking into account different mechanical properties. The algorithm to model the inflation of the tool is based on the theory of inextensible membranes and its industrialization is validated for standard sizes of tires. Mass-Spring method is used to achieve the deformation of geometric shapes in order to compute deformation in real time. In this work, this method is suitable for materials of a tire from geometric and mechanical characterizations validated by comparison with FEM. To conclude, the developed modelization allows a description for each step of the manufacturing process.

本文旨在探討具有捕捉交易密集度特性的波動率測度模型是否能幫助投資者改 善其資產配置的決策。因此，本文分別考量了利用兩種不同價格抽樣方式所計算 出來的實現波動率 (realized volatility) 模型： (1) 日曆時間抽樣法 (calendar time sampling scheme) 與 (2) 交易次數時間抽樣法 (transaction time sampling scheme)。相較於另一廣為應用的一般化自我迴歸條件異質變異 (Generalized Autoregressive Conditional Heteroskedasticity) 模型而言，這兩種實現波動率模型的優點除了在於它們可以捕捉日內資產報酬率的動態變化之外，交易次數時間抽樣法更可以另外捕捉市場的交易密集度。因此利用交易次數間抽樣法所計算出的實現波動率相對提供給投資者較多的訊息。本文利用了West, Edison and Cho (1993) 所提出的資產組合期望效用模型衡量三種波動率測度的預測績效：(1) 實現波動率 - 日曆時間抽樣法 (2) 實現波動率 - 交易次數時間抽樣法 (3) 指數型一般化自我迴歸條件異質變異 (Exponential Generalized Autoregressive Conditional Heteroskedasticity)。我們的實證結果發現，只有在投資者風險趨避係數越小的條件下，此三種波動率測度模型兩兩之間才有較大的期望效用差距；另外，有趣的是，當市場存在異常的交易波動現象時，交易次數時間抽樣法下的實現波動率所產生的期望效用值總是不輸給另外兩種波動率測度模型的結果。 / This paper examines whether volatility measures that account for trading intensity would help investors make better decisions in their asset allocation. Specifically, we consider two versions of realized volatility (RV), namely, one (RV-C) constructed by regular calendar time sampling, and the other one (RV-T) constructed by transaction time sampling. Comparing to models in the GARCH family, both of these two RVs can capture intraday variations of asset return dynamics. In particular, the RV-T incorporates intraday trading intensity, and hence provides even more valuable information for investors. With the utility-based approach developed by West, Edison, and Cho (1993), we compare the predictive performance of RV-C, RV-T, and the EGARCH model in terms of utility generated with each of these three volatility measures. Our empirical results show that the three measures differ from each other mostly when investors are less risk-averse. Most interestingly, the time-deformed RV-T weakly dominates the RV-C and the EGARCH model when the markets are extremely volatile.