臺灣的男女死亡率皆呈現逐年遞減的趨勢，自1993年進入高齡化社會後，預計將會在2018年進入高齡社會；人口不斷老化的結果讓社會上不論人民或是如保險公司等年金提供者皆面臨愈來愈嚴重的長壽風險；目前現有文獻提出了許多方式以解決長壽風險，其中多數的方法皆需使用到對未來死亡率之預估。 本研究為了能夠更準確的預估未來死亡率的趨勢，參考了Lee Carter (1992)所提出之模型以及Li and Lee (2005)、Li (2013)提出之共同改善趨勢效果，提出考慮商品與商品間以及商品與整體人口間共同改善趨勢之死亡率模型；本研究利用臺灣之保險公司壽險及年金業務經驗死亡率和Human Mortality Database之臺灣人口資料對模型進行配適，並以MAE、MAPE、RMSE三項指標比較與Lee Carter模型之優劣。 最後，本研究利用所配適之模型進行預測，模擬自然避險之效果，檢視臺灣保險業進行自然避險的可能效益，並對決策者在於決定是否要進行自然避險方面給出建議。 / Taiwan became an aging society in 1993 and is expected to become an aged society in 2018. The progressive decrease in Taiwan mortality since the 20th century for both genders has made longevity risk a serious problem for both people and annuity provider in Taiwan. So far, the literature has discussed about how to deal with longevity risk and came out with several solutions which can be categorize as “industry self-insurance”, “ mortality projection improvement” and “capital market solutions” , most of them are related to the projection of mortality. In order to provide a more precise projection of future mortality trend, this article designs several models which collaborates Lee Carter Model (1992) and the common improvement trend suggested by Li and Lee (2005). Based on our models, the Taiwan insurance industry experience mortality data and the Taiwan population mortality data, we test the performance of our models and make comparison. Lastly, we use the model we find to project future mortality trend and try to make a simulation of natural hedging strategy in Taiwan. The purpose we do this is to test the performance of natural hedging method and give suggestion for the decision-maker when they are considering whether to execute a natural hedging strategy.

人之性格與行為到底是由與生俱來的先天因素（nature）抑或環境行為等後天因素（nurture）決定呢？這方面的爭議是心理學家數十年來的興趣。然而，近十年中工業與組織心理學家才開始注意到，工作滿意與工作價值觀之氣質（disposition）源起與影響程度。本研究之目的，即在探討「五大人格特質」、「工作價值觀」、「工作滿意」三者間的關係。 本研究所使用的樣本乃為台灣之某一國營企業員工，有效樣本共568位。研究結果發現：五大人格特質與工作滿意是有所關係的，其中嚴謹自律性、外傾支配性、和善性分別對工作滿意具有預測力。五大人格特質對於內在滿意的影響則高於外在滿意；此外，研究者亦提出實徵數據佐證五大人格特質是可以有效地預測工作價值觀，解釋量約為45%；而且工作價值觀也會影響工作滿意且關係密切，與西方或是東方之台灣與韓國的研究相當一致。最重要的是本研究也發現工作價值觀(之工作目的性價值觀與工作手段價值觀均)為五大人格中之嚴謹自律性與內在滿意以及外向性與一般滿意之中介變項。此外，工作手段價值觀僅為五大人格中之和善性與一般滿意之中介變項。 綜合本研究結果與發現，研究者指出本研究之限制與未來研究方向，嘗試整合工作滿意之人格氣質緣起的架構並建立模式。以供工業與組織心理學家以及組織行為學者作為參考。 關鍵字：五大人格特質、工作價值觀、工作滿意、中介變項、氣質 / For decades, the debate over the issue of whether personalities and behaviors of human beings are determined by Nature or Nurture has been one of the major research interests of psychologists. However, it was not until the past ten years that industrial/organizational psychologists started to notice the dispositional sources of and their effects on job satisfaction and work values. In line with this trend, the present study aimed to investigate the relationships between the Five Factor Model of Personality (FFM, also known as the Big Five), work values, and job satisfaction. The study sampled 568 employees from one of the state-operated enterprises in Taiwan, and the Big Five was found to be related to job satisfaction, which could be predicted by Conscientiousness, Extraversion, and Agreeableness, respectively. The influence of the Big Five over intrinsic satisfaction was higher than that over extrinsic satisfaction. In addition, the researcher provided empirical data to substantiate the notion that the Big Five could predict work values effectively, accounting for 45% of the variance. The finding of a strong association between work values and job satisfaction was consistent not only with other research results obtained from eastern countries such as Taiwan and Korea, but also with those obtained in the West. Most important of all, terminal and instrumental work values were found to be the mediator between Conscientiousness and intrinsic satisfaction, as well as that between Extraversion and general satisfaction. However, only terminal work values served as the mediator between Agreeableness and general satisfaction. Summing up the results and discoveries of the present study, the limitations of it were pointed out, and directions for further investigation were suggested. Trying to construct a model by integrating the dispositional sources of job satisfaction and work values into a framework, the researcher wished to provide a footstone of future research for other industrial/organizational psychologists as well as organizational behaviorists. Keywords：Five Factor Model of Personality；FFM；Big Five；disposition；work values；job satisfaction；mediator

La présente recherche a pour objectif d’étudier les effets que peuvent exercer la conception du travail sur le type de conflit qui émerge en milieu de travail. La notion de conception du travail se divise en trois dimensions, soit les caractéristiques reliées à la tâche, les caractéristiques reliées aux connaissances et les caractéristiques sociales. Ces dimensions sont mises en relation avec les deux types de conflit en milieu de travail, soit le conflit relié à la tâche et le conflit relié à la relation. Cette recherche vise également à vérifier l’effet modérateur des traits de personnalités sur les relations entre les dimensions de la conception du travail et celles du conflit en milieu de travail. Cette recherche est basée sur 473 participants qui occupent un emploi rémunéré et qui ont vécu une situation de conflit en milieu de travail allant jusqu’à 6 mois avant la période de sondage, allant du 14 au 18 janvier 2012. Les résultats indiquent qu’il n’y a pas de relations particulières entre la conception du travail et le type de conflit en milieu de travail. En ce qui a trait aux effets des traits de personnalité, les résultats indiquent que ces variables n’ont aucuns effets modérateurs sur la relation entre la conception du travail et le type de conflit en milieu de travail. Globalement, les résultats ne démontrent aucune relation entre la conception du travail et les types de conflit en milieu de travail, ou les effets modérateurs que les traits de personnalités peuvent avoir sur ces relations. / The goal of this research is to study the effect of work design on the type of conflict that emerges in the workplace. The concept of work design is divided in two three dimensions, namely task, knowledge and social characteristics. These dimensions are linked to the two dimensions of workplace conflict, that is, task conflict and relationship conflict. This research is also intended to verify the moderating effect of personality traits on the association between work design and workplace conflict. This study is based on 473 employed participants who have experienced workplace conflict up to 6 months prior to the canvass period, which was from January 14th to the 18th 2012. The results indicate that there is no particular association between work design and conflict in the workplace. With regards to the moderating effect of personality traits, results indicate that these variables do not moderating the association between the dimensions of work design and the type of workplace conflict. Overall, results do not show a relation between work design and types of workplace conflict, or the moderating effect that personality traits can have on these relations.

Cette thèse développe des méthodes bootstrap pour les modèles à facteurs qui sont couram- ment utilisés pour générer des prévisions depuis l'article pionnier de Stock et Watson (2002) sur les indices de diffusion. Ces modèles tolèrent l'inclusion d'un grand nombre de variables macroéconomiques et financières comme prédicteurs, une caractéristique utile pour inclure di- verses informations disponibles aux agents économiques. Ma thèse propose donc des outils éco- nométriques qui améliorent l'inférence dans les modèles à facteurs utilisant des facteurs latents extraits d'un large panel de prédicteurs observés. Il est subdivisé en trois chapitres complémen- taires dont les deux premiers en collaboration avec Sílvia Gonçalves et Benoit Perron. Dans le premier article, nous étudions comment les méthodes bootstrap peuvent être utilisées pour faire de l'inférence dans les modèles de prévision pour un horizon de h périodes dans le futur. Pour ce faire, il examine l'inférence bootstrap dans un contexte de régression augmentée de facteurs où les erreurs pourraient être autocorrélées. Il généralise les résultats de Gonçalves et Perron (2014) et propose puis justifie deux approches basées sur les résidus : le block wild bootstrap et le dependent wild bootstrap. Nos simulations montrent une amélioration des taux de couverture des intervalles de confiance des coefficients estimés en utilisant ces approches comparativement à la théorie asymptotique et au wild bootstrap en présence de corrélation sérielle dans les erreurs de régression. Le deuxième chapitre propose des méthodes bootstrap pour la construction des intervalles de prévision permettant de relâcher l'hypothèse de normalité des innovations. Nous y propo- sons des intervalles de prédiction bootstrap pour une observation h périodes dans le futur et sa moyenne conditionnelle. Nous supposons que ces prévisions sont faites en utilisant un ensemble de facteurs extraits d'un large panel de variables. Parce que nous traitons ces facteurs comme latents, nos prévisions dépendent à la fois des facteurs estimés et les coefficients de régres- sion estimés. Sous des conditions de régularité, Bai et Ng (2006) ont proposé la construction d'intervalles asymptotiques sous l'hypothèse de Gaussianité des innovations. Le bootstrap nous permet de relâcher cette hypothèse et de construire des intervalles de prédiction valides sous des hypothèses plus générales. En outre, même en supposant la Gaussianité, le bootstrap conduit à des intervalles plus précis dans les cas où la dimension transversale est relativement faible car il prend en considération le biais de l'estimateur des moindres carrés ordinaires comme le montre une étude récente de Gonçalves et Perron (2014). Dans le troisième chapitre, nous suggérons des procédures de sélection convergentes pour les regressions augmentées de facteurs en échantillons finis. Nous démontrons premièrement que la méthode de validation croisée usuelle est non-convergente mais que sa généralisation, la validation croisée «leave-d-out» sélectionne le plus petit ensemble de facteurs estimés pour l'espace généré par les vraies facteurs. Le deuxième critère dont nous montrons également la validité généralise l'approximation bootstrap de Shao (1996) pour les regressions augmentées de facteurs. Les simulations montrent une amélioration de la probabilité de sélectionner par- cimonieusement les facteurs estimés comparativement aux méthodes de sélection disponibles. L'application empirique revisite la relation entre les facteurs macroéconomiques et financiers, et l'excès de rendement sur le marché boursier américain. Parmi les facteurs estimés à partir d'un large panel de données macroéconomiques et financières des États Unis, les facteurs fortement correlés aux écarts de taux d'intérêt et les facteurs de Fama-French ont un bon pouvoir prédictif pour les excès de rendement. / This thesis develops bootstrap methods for factor models which are now widely used for generating forecasts since the seminal paper of Stock and Watson (2002) on diffusion indices. These models allow the inclusion of a large set of macroeconomic and financial variables as predictors, useful to span various information related to economic agents. My thesis develops econometric tools that improves inference in factor-augmented regression models driven by few unobservable factors estimated from a large panel of observed predictors. It is subdivided into three complementary chapters. The two first chapters are joint papers with Sílvia Gonçalves and Benoit Perron. In the first chapter, we study how bootstrap methods can be used to make inference in h-step forecasting models which generally involve serially correlated errors. It thus considers bootstrap inference in a factor-augmented regression context where the errors could potentially be serially correlated. This generalizes results in Gonçalves and Perron (2013) and makes the bootstrap applicable to forecasting contexts where the forecast horizon is greater than one. We propose and justify two residual-based approaches, a block wild bootstrap (BWB) and a dependent wild bootstrap (DWB). Our simulations document improvement in coverage rates of confidence intervals for the coefficients when using BWB or DWB relative to both asymptotic theory and the wild bootstrap when serial correlation is present in the regression errors. The second chapter provides bootstrap methods for prediction intervals which allow relaxing the normality distribution assumption on innovations. We propose bootstrap prediction intervals for an observation h periods into the future and its conditional mean. We assume that these forecasts are made using a set of factors extracted from a large panel of variables. Because we treat these factors as latent, our forecasts depend both on estimated factors and estimated regression coefficients. Under regularity conditions, Bai and Ng (2006) proposed the construction of asymptotic intervals under Gaussianity of the innovations. The bootstrap allows us to relax this assumption and to construct valid prediction intervals under more general conditions. Moreover, even under Gaussianity, the bootstrap leads to more accurate intervals in cases where the cross-sectional dimension is relatively small as it reduces the bias of the ordinary least squares estimator as shown in a recent paper by Gonçalves and Perron (2014). The third chapter proposes two consistent model selection procedures for factor-augmented regressions in finite samples.We first demonstrate that the usual cross-validation is inconsistent, but that a generalization, leave-d-out cross-validation, selects the smallest basis of estimated factors for the space spanned by the true factors. The second proposed criterion is a generalization of the bootstrap approximation of the squared error of prediction of Shao (1996) to factor-augmented regressions which we also show is consistent. Simulation evidence documents improvements in the probability of selecting the smallest set of estimated factors than the usually available methods. An illustrative empirical application that analyzes the relationship between expected stock returns and macroeconomic and financial factors extracted from a large panel of U.S. macroeconomic and financial data is conducted. Our new procedures select factors that correlate heavily with interest rate spreads and with the Fama-French factors. These factors have strong predictive power for excess returns.

Le résonateur matriochka est conçu à partir de résonateurs coaxiaux ré-entrants créant ainsi des sauts d’impédances (SIR). La thèse développe alors des innovations théoriques sur la technologie matriochka en proposant des modèles analytiques précis sur le comportement fréquentiel et du facteur de qualité du résonateur. Les modélisations mettent en relief l’existence de degrés de liberté au sein du résonateur matriochka induisant une flexibilité du rapport de forme du résonateur. Les degrés de liberté créent ainsi une multitude de configurations du résonateur matriochka pour une fréquence fondamentale et un facteur de qualité donnés. Par conséquent, une optimisation en volume est réalisée pour concevoir deux filtres en bande L et C afin de minimiser leur encombrement. Une étude de la tenue en puissance dans le vide est également effectuée pour le filtre en bande L. Une méthode conjointe d’optimisation de la tenue en puissance et de minimisation en volume est alors proposée pour ce filtre. Ainsi, les modélisations et les optimisations sont employées afin de concevoir et de fabriquer deux filtres hyperfréquences. Le premier est un filtre de transmission en bande L conçu pour l’application de navigation Galileo qui propose une alternative d’encombrement et une tenue en puissance dans le vide élevée. Enfin, le second est un filtre de réception en bande C conçu, fabriqué et mesuré pour l’application de télémesure qui propose de meilleures performances en réjection et un volume réduit par rapport à l’existant. Finalement, la technologie matriochka est une alternative de résonateur par rapport à l’état de l’art en proposant, selon les configurations, un rejet élevé des harmoniques et un volume réduit pour une fréquence fondamentale et un facteur de qualité donnés. / The matriochka resonator is based on reentrant coaxial Stepped Impedance Resonator (SIR). So, the thesis develops theoretical innovations on the matriochka technology offering accurate analytical models on the frequency and the quality factor behaviors of the resonator. The models prove the existence of degrees of freedom within the matriochka resonator which allows to get different form factors of the resonator. The degrees of freedom create many configurations of the matriochka resonator for a fundamental frequency and a quality factor. Consequently, a volume optimization is realized to design a L-band filter and a C-band filter. A multipactor study is also carried out for the L-band filter. So, a joint optimization method of the multipactor and the volume minimization is proposed for this filter. Thus, the models and optimisations are used in the order to to design and fabricate the microwave filters. The first one is a transmission L-band filter for the navigation application Galileo which offers a volume alternative and a high power in the vaccum. Then, the second one is a reception C-band filter for the telemetry application which offers wide spurious free-performance and a low volume compared to the state of the art. Finally, for a frequency and a quality factor and depending on the configurations, the matriochka technology offers an alternative of the resonator volume, and it offers a wide spurious free- performance and a low volume compared to the state of the art.

商業銀行是以借貸為主的金融機構，銀行獲利的主要來源，是從存款大眾手中取得短期資金，再將資金貸放給政府或企業進行長期投資。銀行「借短貸長」的業務，常使得其資產與負債產生存續期間不一致的問題，當利率非預期變動時，會改變資產與負債的真實價值，進而影響到銀行的淨值及股票報酬率。此外，匯率變動的風險也是銀行常常面臨的問題，尤其是當銀行涉足國際業務時，匯率的變動常常會使銀行所持有的外幣部位價值改變，進而影響到銀行的真實價值。另外一個會影響到銀行資產與負債價值的因素，就是信用風險的問題，總體經濟環境的信用品質變動，常常會影響銀行放款的還款機率，進而改變銀行放款的實質價值。 本文採用過去學者們所研究過的銀行股價三因子模型，即市場因子、債券因子、匯率因子，並加入代表總體信用風險的第四個因子，以及代表抵押品價值變動的第五個因子，成為銀行股價五因子模型。以日本銀行業的股價報酬為研究對象，實證結果顯示:新加入的總體信用風險因子，對於銀行股價報酬率的確產生顯著的負向影響，也就是當借貸市場信用品質愈差（信用風險越高）時，整體銀行股價的報酬率下降。且在四種類型的銀行中，地方銀行所估計出的信用風險顯著的比例最高，代表資產規模較小、放款業務較集中的地方銀行，其信用風險確實較其他類型的銀行為高。另外，在日本泡沫經濟破滅以後的銀行危機時期，以股價多因子模型來衡量的銀行信用風險也有上升的現象。

Examensarbetet genomfördes av Philip Wockatz utan stöd och handledning. Detta ledde fram till att Kip Smith tog över som handledare strax innan presentationen.

Literature reveals studies on mutual fund performance analysis and persistency, with various results. Some studies support hort term performance persistence, while the rest claiming no such persistency among the portfolios. This thesis is an attempt to analyze the performances of Turkish open-end mutual funds for the period of 2003-2010 and search for persistency by extending the time period to June 2011. For performance evaluation, single factor CAPM and ama-French&rsquo / s Three Factor Model are applied. Persistency analysis is done by tracking the relative fund performances on a monthly basis. The results of this study indicate that for the sample period, Turkish A Type mutual funds neither overperform nor underperform the overall market. Nearly all Jensen&rsquo / s alphas are found to be zero, statistically significant. This is also an implication that the mutual funds are earning their expected returns in an efficient mutual fund market in Turkey. The Fama-French&rsquo / s three factor model shows slightly better performance, on the other hand. The size and book to market equity factors are not found significant in general, however they are found jointly significant in all regressions. Persistency is analyzed by tracking the mutual fund erformances on monthly basis. When some mutual funds showed negative or positive performance persistency during the period individually, but the overall picture demonstrates a balanced distribution of performance groups. The number Loser-Loser performances is slightly more than the other three groups, resulting in a tendency for short term negative persistency for the sample analyzed between the period of January 2003 to June 2011.

本篇論文使用了LHP的近似方法去評價擔保債權憑證，並推導出漸進極值因子模型，又稱單因子copula模型，單因子copula模型被廣泛運用在CDO之風險管理與一些風險因子模擬之應用，但由於2008年之金融海嘯造成市場標準模型Gaussian copula model會有評價上的誤差，所以為了能在市場不穩定時能更精確的求算出分券價差，我們必須找到一個更簡單且快速捕捉到市場不穩定性的模型。在這篇論文中，我們引用了Anna Schloesser在2009年所提出以NIG copula model為基礎的兩個延伸，讓模型更穩健和且擁有良好的性質去進行模擬，NIG Regime-Switch 模型有兩大特色: (i)可以用一致的方法去評價不同到期日的分券，放寬了同一分券必須是相同到期日的假設，和(ii)有不同的相關係數狀態，對於金融風暴來說，狀態轉換可以有效地降低市場不穩定所帶來的評價誤差。本文也對不同模型下的CDO進行風險分析與避險，分券的期望損失廣泛被信評公司視為一項審定信用評等重要的風險衡量指標，但是並無法真實反映出擔保債權憑證分券之間相對風險之大小，因此本文採用期望損失率的觀念，利用期望損失佔本金的比例來比較各分券之相對風險，且本文也求算出CDO之避險參數，讓投資人了解對合成行擔保債權憑證分券避險時所需之避險部位，分券持有人也可依據所要規避的風險類型，選擇市場上現有的信用違約交換指數或是單一資產之信用違約交換(single-name credit default swap)來進行避險。 / This paper presents the Large Homogeneous Portfolio (LHP) approach to the pricing of CDOs and we derive the one-factor copula model. It is popular that the one-factor copula models are very useful for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors. However, since the financial crisis in 2008 induces some errors in the valuation by Gaussian copula model, which is originally adopted by credit rating firms, it is necessary to have a simple and fast model that can capture the market unstableness. In this paper we apply two extensions of the NIG copula model, which are first present by Anna Schloesser (2009), since they make the model well defined and powerful for scenario simulation. The NIG Regime-Switch copula model allows for two important features: (i) tranches with different maturities modeled in a consistent way, and (ii) different correlation regimes. The regime-switching component of the NIG copula model is especially important in view of the financial crisis. This paper also targets on different models to conduct risk analysis and hedging strategy. The expected loss of tranches is widely used by credit rating organizations as one of the important indicators for risk measurement. However, it can’t reflect the relative risk level between CDO’s tranches. Therefore, our research adopts the concept of expected loss rate, which use the proportion of expected loss to total principal amount to compare the relative risk of each tranche. Moreover, when we want to hedge the spread risk of synthetic CDO tranches, the holders of tranches can choose the existing CDS index or the single-name CDS based on different risks types to hedge. The employment of the NIG Regime-Switch copula model not only has more precise estimation for the spread of tranches but also possess more stable hedge ratio to hedge.

In the first part of this thesis, we introduce a new methodology for stress-test exercises. Our approach allows to consider richer stress-test exercises, which assess the impact of a modification of the whole distribution of asset prices' factors, rather than focusing as the common practices on a single realization of these factors, and take into account the potential reaction to the shock of the portfolio manager. The second part of the thesis is devoted to the pricing of bonds with very long-term time-to-maturity (more than ten years). Modeling the volatility of very long-term rates is a challenge, due to the constraints put by no-arbitrage assumption. As a consequence, most of the no-arbitrage term structure models assume a constant limiting rate (of infinite maturity). The second chapter investigates the compatibility of the so-called "level" factor, whose variations have a uniform impact on the modeled yield curve, with the no-arbitrage assumptions. We introduce in the third chapter a new class of arbitrage-free term structure factor models, which allows the limiting rate to be stochastic, and present its empirical properties on a dataset of US T-Bonds.