Les stratégies de volatilité ont connu un rapide essor suite à la crise financière de 2008. Or, les récentes performances catastrophiques de ces instruments indiciels ont remis en question leurs contributions en couverture de portefeuille. Mes travaux de thèse visent à repenser, réinventer la philosophie des stratégies de volatilité. Au travers d'une analyse empirique préliminaire reposant sur la théorie de l'utilité espérée, le chapitre 1 dresse le diagnostic des stratégies traditionnelles de volatilité basées sur la couverture de long-terme par la réplication passive de la volatilité implicite. Il montre que, bien que ce type de couverture bat la couverture traditionnelle, elle s'avère inappropriée pour des investisseurs peu averses au risque.Le chapitre 2 ouvre la voie à une nouvelle génération de stratégies de volatilité, actives, optionnelles et basées sur l'investissement factoriel. En effet, notre décomposition analytique et empirique du smile de volatilité implicite en primes de risque implicites, distinctes et investissables permet de monétiser de manière active le portage de risques d'ordres supérieurs. Ces primes de risques mesurent l'écart de valorisation entre les distributions neutres au risque et les distributions physiques.Enfin, le chapitre 3 compare notre approche investissement factoriel avec les stratégies de volatilité employées par les hedge funds. Notre essai montre que nos stratégies de primes de risque d'assurance sont des déterminants importants dans la performance des hedge funds, tant en analyse temporelle que cross-sectionnelle. Ainsi, nous mettons en évidence dans quelle mesure l'alpha provient en réalité de la vente de stratégies d'assurance contre le risque extrême. / Volatility strategies have flourished since the Great Financial Crisis in 2008. Nevertheless, the recent catastrophic performance of such exchange-traded products has put into question their contributions for portfolio hedging and diversification. My thesis work aims to rethink and reinvent the philosophy of volatility strategies.From a preliminary empirical study based on the expected utility theory, Chapter 1 makes a diagnostic of traditional volatility strategies, based on buy-and-hold investments and passive replication of implied volatility. It exhibits that, although such portfolio hedging significantly outperforms traditional hedging, it appears strongly inappropriate for risk-loving investors.Chapter 2 paves the way for a new generation of volatility strategies, active, option-based and factor-based investing. Indeed, our both analytical and empirical decomposition of implied volatility smiles into a combination of implied risk premia, distinct and tradeable, enables to harvest actively the compensation for bearing higher-order risks. These insurance risk premia measure the pricing discrepanciesbetween the risk-neutral and the physical probability distributions.Finally, Chapter 3 compares our factor-based investing approach to the strategies usually employed in the hedge fund universe. Our essay clearly evidences that our tail risk premia strategies are incremental determinants in the hedge fund performance, in both the time-series and the cross-section of returns. Hence, we exhibit to what extent hedge fund alpha actually arises from selling crash insurance strategies against tail risks.

本研究利用美國芝加哥商品交易所針對 18 個城市發行之冷氣指數／暖氣指數衍生性商品與相對應之日均溫進行分析與評價。研究成果與貢獻如下：一、延伸 Alaton, Djehince, and Stillberg (2002) 模型，引入跳躍風險、隨機波動度、波動跳躍等因子，提出新模型以捕捉更多溫度指數之特徵。二、針對不同模型，分別利用最大概似法、期望最大演算法、粒子濾波演算法等進行參數估計。實證結果顯示新模型具有較好之配適能力。三、利用 Esscher 轉換將真實機率測度轉換至風險中立機率測度，並進一步利用　Feynman-Kac 方程式與傅立葉轉換求出溫度模型之機率分配。四、推導冷氣指數／暖氣指數期貨之半封閉評價公式，而冷氣指數／暖氣指數期貨之選擇權不存在封閉評價公式，則利用蒙地卡羅模擬進行評價。五、無論樣本內與樣本外之定價誤差，考慮隨機波動度型態之模型對於溫度衍生性商品皆具有較好之評價績效。六、實證指出溫度市場之市場風險價格為負，顯示投資人承受較高之溫度風險時會要求較高之風險溢酬。本研究可給予受溫度風險影響之產業，針對衍生性商品之評價與模型參數估計上提供較為精準、客觀與較有效率之工具。 / This study uses the daily average temperature index (DAT) and market price of the CDD/HDD derivatives for 18 cities from the CME group. There are some contributions in this study: (i) we extend the Alaton, Djehince, and Stillberg (2002)'s framework by introducing the jump risk, the stochastic volatility, and the jump in volatility. (ii) The model parameters are estimated by the MLE, the EM algorithm, and the PF algorithm. And, the complex model exists the better goodness-of-fit for the path of the temperature index. (iii) We employ the Esscher transform to change the probability measure and derive the probability density function of each model by the Feynman-Kac formula and the Fourier transform. (iv) The semi-closed form of the CDD/HDD futures pricing formula is derived, and we use the Monte-Carlo simulation to value the CDD/HDD futures options due to no closed-form solution. (v) Whatever in-sample and out-of-sample pricing performance, the type of the stochastic volatility performs the better fitting for the temperature derivatives. (vi) The market price of risk differs to zero significantly (most are negative), so the investors require the positive weather risk premium for the derivatives. The results in this study can provide the guide of fitting model and pricing derivatives to the weather-linked institutions in the future.

L'approche traditionnelle des produits dérivés consiste, sous certaines hypothèses bien définies, à construire des stratégies de couverture à risque strictement nul. Cependant,dans le cas général ces stratégies de couverture "parfaites" n'existent pas,et la théorie doit plutôt s'appuyer sur une idée de minimisation du risque. Dans ce cas, la couverture optimale dépend de la quantité du risque à minimiser. Dans lecadre des options, on considère dans ce travail une nouvelle mesure du risque vial'approche de l'utilité espérée qui tient compte, à la fois, du moment d'ordre quatre,qui est plus sensible aux grandes fluctuations que la variance, et de l'aversion aurisque de l'émetteur d'une option vis-à-vis au risque. Comparée à la couverture endelta, à l'optimisation de la variance et l'optimisation du moment d'ordre quatre,la stratégie de couverture, via l'approche de l'utilité espérée, permet de diminuer lasensibilité de la couverture par rapport au cours du sous-jacent. Ceci est de natureà réduire les coûts des transactions associées / The traditional approach of derivatives involves, under certain clearly defined hypothesis, to construct hedging strategies for strictly zero risk. However, in the general case these perfect hedging strategies do not exist, and the theory must be rather based on the idea of risk minimization. In this case, the optimal hedging strategy depends on the amount of risk to be minimized. Under the options approach, we consider here a new measure of risk via the expected utility approach that takes into account both, the moment of order four, which is more sensitive to fluctuations than large variance, and risk aversion of the investor of an option towards risk. Compared to delta hedging, optimization of the variance and maximizing the moment of order four, the hedging strategy, via the expected utilitiy approach, reduces the sensitivy of the hedging approach reported in the underlying asset price. This is likely to reduce the associated transaction costs.

We consider a class of periodic preventive maintenance (PM) optimization problems, for a single piece of equipment that deteriorates with time or use, and can be repaired upon failure, through corrective maintenance (CM). We develop analytical and simulation-based optimization models that seek an optimal periodic PM policy, which minimizes the sum of the expected total cost of PMs and the risk-averse cost of CMs, over a finite planning horizon. In the simulation-based models, we assume that both types of maintenance actions are imperfect, whereas our analytical models consider imperfect PMs with minimal CMs. The effectiveness of maintenance actions is modeled using age reduction factors. For a repairable unit of equipment, its virtual age, and not its calendar age, determines the associated failure rate. Therefore, two sets of parameters, one describing the effectiveness of maintenance actions, and the other that defines the underlying failure rate of a piece of equipment, are critical to our models. Under a given maintenance policy, the two sets of parameters and a virtual-age-based age-reduction model, completely define the failure process of a piece of equipment. In practice, the true failure rate, and exact quality of the maintenance actions, cannot be determined, and are often estimated from the equipment failure history. We use a Bayesian approach to parameter estimation, under which a random-walk-based Gibbs sampler provides posterior estimates for the parameters of interest. Our posterior estimates for a few datasets from the literature, are consistent with published results. Furthermore, our computational results successfully demonstrate that our Gibbs sampler is arguably the obvious choice over a general rejection sampling-based parameter estimation method, for this class of problems. We present a general simulation-based periodic PM optimization model, which uses the posterior estimates to simulate the number of operational equipment failures, under a given periodic PM policy. Optimal periodic PM policies, under the classical maximum likelihood (ML) and Bayesian estimates are obtained for a few datasets. Limitations of the ML approach are revealed for a dataset from the literature, in which the use of ML estimates of the parameters, in the maintenance optimization model, fails to capture a trivial optimal PM policy. Finally, we introduce a single-stage and a two-stage formulation of the risk-averse periodic PM optimization model, with imperfect PMs and minimal CMs. Such models apply to a class of complex equipment with many parts, operational failures of which are addressed by replacing or repairing a few parts, thereby not affecting the failure rate of the equipment under consideration. For general values of PM age reduction factors, we provide sufficient conditions to establish the convexity of the first and second moments of the number of failures, and the risk-averse expected total maintenance cost, over a finite planning horizon. For increasing Weibull rates and a general class of increasing and convex failure rates, we show that these convexity results are independent of the PM age reduction factors. In general, the optimal periodic PM policy under the single-stage model is no better than the optimal two-stage policy. But if PMs are assumed perfect, then we establish that the single-stage and the two-stage optimization models are equivalent. / text