The work explores ways to generate the OFDM signal and LDPC channel coding methods. Describes the creation of basic modules of the communication system in Matlab and simulation methods for atmospheric transmission environment, including effects of turbulence, attenuation along the route and weather conditions on the transmitted signal.

Studier av livslängder och dödssannolikheter är avgörande för livförsäkring. Betalningar gällande livförsäkringar är helt beroende av om en individ lever eller ej, eller befinner sig i olika hälsotillstånd. För att kunna prissätta premier korrekt och avsätta reserver är det därför av stort intresse att modellera livslängden på ett så korrekt sätt som möjligt. Försäkringsbranschen använder idag historiskt beprövade och välfungerande modeller som går så långt bak i tiden som 200 år. Det finns modeller ännu längre bak i tiden, men de modeller som används idag är främst Gompertz (1826), Makeham (1860) och Lee-Carter (1992). Även om dessa modeller presterar bra är det alltid nödvändigt att undersöka om det kan finnas alternativa modeller som modellerar dödligheten bättre. I detta examensarbete tillämpas affina korträntemodeller för modellering av dödlighetsintensiteten som ligger till grund för flertalet intressanta aktuariella storheter. Då dessa modeller introducerar stokastisk dödlighet kan osäkerheten och beroendet över tid därmed beskrivas. De korträntemodeller som undersöks i arbetet och som är vanligt förekommande inom den finansiella teorin; är Ornstein-Uhlenbeck, Feller och Hull-White. Dessa modeller jämförs sedan mot varandra vad gäller modellerad dödlighetsintensitet samt förväntad återstående livslängd och ettårig dödssannolikhet. En aspekt av stokastisk dödlighetsmodellering som ej återfinns i befintlig litteratur men som undersöks i detta examensarbete är modellering av dödlighet över tid då detta är en av de mest väsentliga aspekterna inom det livförsäkringsmatematiska arbetet. Till sist i valideringssyfte utvärderas samtliga korträntemodeller genom back-testing. Den andra huvudsakliga delen av arbetet består i att generera resultat för samma storheter som ovan baserat på DUS-metoden för att på så sätt jämföra en kommersiell metod mot en mer teoretisk mindre beprövad sådan. Resultaten visar på en stor potential hos flera av korträntemodellerna kontra DUS både vad gäller modellering över åldrar och kalenderår. Däremot är inte resultaten helt felfria för enstaka kalenderår där stora spikar uppstår på grund av parametermässig felanpassning. Modelleringen av korträntemodellerna över tid var över förväntan då modellerna inte är konstruerade för att fånga avtagande trender. Detta är något som kan betraktas som en stor flexibilitet hos korträntemodellerna då de står sig väl mot Lee-Cartermodellen som används i DUS, både vad gäller ålders- och tidsmodellering av dödlighet. / Studies of life expectancy and death probabilities are crucial for life insurance. Payments for life insurance are completely dependent on whether an individual is alive or not, or is in various health conditions. In order to be able to price premiums correctly and set aside reserves, it is therefore of great importance to model life expectancy in the most accurate way possible. The insurance industry today uses historically proven well-functioning models that go as far back in time as 200 years. There are models even further back in time, but the models used today are mainly Gompertz (1826), Makeham (1860) and Lee-Carter (1992). Although these models perform well, it is always necessary to investigate whether there may be alternative models that model mortality better. In this thesis, affine short-term interest rate models are applied for modeling the force of mortality that forms the basis for most interesting actuarial variables. As these models introduce stochastic mortality, the uncertainty and dependence over time can thus be described. The three short-term interest rate models examined in this project, which are common in financial theory; are Ornstein-Uhlenbeck, Feller and Hull-White. These models are then compared against each other in terms of the modeled force of mortality as well as the expected remaining life expectancy and the one-year probability of death. One aspect of stochastic mortality modeling that is not found in the existing literature but which is examined in this thesis is the modeling of mortality over time as this is one of the most important aspects in the life insurance mathematical industry. Finally, for validation purposes, all short-term interest rate models are evaluated using back-testing. The second main part of the work consists of generating results for the same quantities as above based on the DUS method in order to compare a commercial method with more theoretical and less approved ones. The results show a great potential in several of the short-term interest rate models versus DUS both in terms of modeling over ages and calendar years. However, the results are not completely impeccable for individual calendar years where large spikes occur due to inaccurate parameter calibration. The satisfactory modeling of the short-term interest rate models over time was above the expectations as the models are not designed to capture decreasing trends. This is something that can be considered a great flexibility of the short-term interest rate models as they are more or less as accurate as the Lee-Carter model used in DUS, both in terms of age and time modeling of mortality.

This study applies the Vasicek stochastic interest rate model in order to determine optimal capital structures for listed firms. A Swedish interest rate data set is used to estimate Vasicek model parameter that are reliable and independent of initial start values. These interest rate parameters are then used in a capital structure model which is evaluated through a sensitivity analysis and a firm-specific analysis which is applied to listed Swedish firms. The tax benefits of debt must be balanced against transaction costs and bankruptcy costs when determining optimal leverage ratio and optimal debt maturity. The results imply that firms should primarily focus on the long-term mean parameter of the interest rate process, the volatility of its firm value, the transaction cost of issuing debt and the effective corporate tax rate when choosing a capital structure. The capital structure model is well-founded in previous research and yields results which align with empirical data quite well. The conclusions of this study has implications for corporate finance, as the Vasicek model provides a better understanding of the stochastic nature of interest rates and its influence in determining optimal capital structures. / Denna studie tillämpar Vasiceks stokastiska räntemodell för att bestämma optimala kapitalstrukturer för noterade företag. Vasicekmodellen anpassas till ett Svensk dataset över räntor för att estimera parametrar. Dessa parametrar används sedan i en kapitalstruktursmodell för att analysera modellens känslighet för variationer i parametrar samt för att härleda optimala kapitalstrukturer för en rad Svenska noterade bolag. Skattefördelarna av skuld måste balanseras mot transaktionskostnader av skuldemissioner och konkurskostnader vid bestämning av optimal skuldsättningsgrad och optimal skuldlöptid. Resultaten antyder att företag bör primärt fokusera på det långsiktiga medelvärdet av den stokastiska ränteprocessen, volatiliteten av bolagsvärdet, transaktionskostnaden av skuldemissioner och effektiva bolagsskatten när de väljer en kapitalstruktur. Denna studie har implikationer för finansieringsteori då Vasiceks modell närmare modellerar räntors stokastiska dynamiker och dess påverkan på bestämning av bolags kapitalstrukturer.

The original intention of the recommender system is to solve the problem of information explosion, hoping to help users find the content they need more efficiently. In an e-commerce platform, users typically interact with items that they are interested in or need in a variety of ways. For example, buying, browsing details, etc. These interactions are recorded as time-series information. How to use this sequential information to predict user behaviors in the future and give an efficient and effective recommendation is a very important problem. For content providers, such as merchants in e-commerce platforms, more accurate recommendation means higher traffic, CTR (click-through rate), and revenue. Therefore, in the industry, the CTR model for recommendation systems is a research hotspot. However, in the fine ranking stage of the recommendation system, the existing models have some limitations. No researcher has attempted to predict multiple behaviors of one user simultaneously by processing sequential information. We define this problem as the multi-task sequential recommendation problem. In response to this problem, we study the CTR model, sequential recommendation, and multi-task learning. Based on these studies, this paper proposes AMBSN (Attention-based Multi-Behavior Sequential Network). Specifically, we added a transformer layer, the activation unit, and the multi-task tower to the traditional Embedding&MLP (multi-layer perceptron) model. The transformer layer enables our model to efficiently extract sequential behavior information, the activation unit can understand user interests, and the multi-task tower structure makes the model give the prediction of different user behaviors at the same time. We choose user behavior data from Taobao for recommendation published on TianChi as the dataset, and AUC as the evaluation criterion. We compare the performance of AMBSN and some other models on the test set after training. The final results of the experiment show that our model outperforms some existing models. / L’intenzione originale del sistema di raccomandazione è risolvere il problema dell’esplosione delle informazioni, sperando di aiutare gli utenti a trovare il contenuto di cui hanno bisogno in modo più efficiente. In una piattaforma di e-commerce, gli utenti in genere interagiscono con gli articoli a cui sono interessati o di cui hanno bisogno in vari modi. Ad esempio, acquisti, dettagli di navigazione, ecc. Queste interazioni vengono registrate come informazioni di serie temporali. Come utilizzare queste informazioni sequenziali per prevedere i comportamenti degli utenti in futuro e fornire una raccomandazione efficiente ed efficace è un problema molto importante. Per i fornitori di contenuti, come i commercianti nelle piattaforme di e-commerce, una raccomandazione più accurata significa traffico, CTR (percentuale di clic) ed entrate più elevati. Pertanto, nel settore, il modello CTR per i sistemi di raccomandazione è un hotspot di ricerca. Tuttavia, nella fase di classificazione fine del sistema di raccomandazione, i modelli esistenti presentano alcune limitazioni. Nessun ricercatore ha tentato di prevedere più comportamenti di un utente contemporaneamente elaborando informazioni sequenziali. Definiamo questo problema come il problema di raccomandazione sequenziale multi-task. In risposta a questo problema, studiamo il modello CTR, la raccomandazione sequenziale e l’apprendimento multi-task. Sulla base di questi studi, questo documento propone AMBSN (Attention-based Multi-Behavior Sequential Network). In particolare, abbiamo aggiunto uno strato trasformatore, l’unità di attivazione e la torre multi-task al tradizionale modello Embedding&MLP (multi-layer perceptron). Il livello del trasformatore consente al nostro modello di estrarre in modo efficiente le informazioni sul comportamento sequenziale, l’unità di attivazione può comprendere gli interessi degli utenti e la struttura della torre multi-task fa sì che il modello fornisca la previsione di diversi comportamenti degli utenti contemporaneamente. Scegliamo i dati sul comportamento degli utenti da Taobao per la raccomandazione pubblicata su TianChi come set di dati e l’AUC come criterio di valutazione. Confrontiamo le prestazioni di AMBSN e di alcuni altri modelli sul set di test dopo l’allenamento. I risultati finali dell’esperimento mostrano che il nostro modello supera alcuni modelli esistenti.

Les gérants de portefeuille pour compte de tiers sont souvent jugés par leur performance relative à celle d'un portefeuille benchmark. A ce titre, ils sont amenés très fréquemment à utiliser des modèles internes de "risk management" pour contrôler le risque de sous-performer le benchmark. Par ailleurs, ils sont de plus en plus nombreux à adopter une politique de rémunération incitative, en percevant une commission de sur-performance par rapport au benchmark. En effet, cette composante variable de leur rémunération leur permet d'augmenter leur revenu en cas de sur-performance sans contrepartie en cas de sous-performance. Or de telles pratiques ont fait récemment l'objet de nombreuses polémiques : la période récente de crise financière mondiale a fait apparaître certaines carences de plusieurs acteurs financiers en terme de contrôle de risque ainsi que des niveaux de prise de risque et de rémunération jugés excessifs. Cependant, l'étude des implications de ces pratiques reste un thème encore relativement peu exploré dans le cadre de la théorie classique des choix dynamiques de portefeuille en temps continu. Cette thèse analyse, dans ce cadre théorique, les implications de ces pratiques de "benchmarking" sur le comportement d'investissement de l'asset manager. La première partie étudie les propriétés de la stratégie dynamique optimale pour l'asset manager concerné par l'écart entre la rentabilité de son portefeuille et celle d'un benchmark fixe ou stochastique (sur ou sous-performance). Nous considérons plusieurs types d'asset managers, caractérisés par différentes fonctions d'utilité et qui sont soumis à différentes contraintes de risque de sous-performance. Nous montrons en particulier quel est le lien entre les problèmes d'investissement avec prise en compte de l'aversion à la sous-performance et avec contrainte explicite de "risk management". Dans la seconde partie, on s'intéresse à l'asset manager bénéficiant d'une rémunération incitative (frais de gestion variables, bonus de sur-performance ou commission sur encours additionnelle). On étudie, selon la forme de ses incitations financières et son degré d'aversion à la sous-performance, comment sa stratégie d'investissement s'écarte de celle de l'investisseur (ou celle de l'asset manager sans rémunération incitative). Nous montrons que le changement de comportement de l'asset manager peut se traduire soit par une réduction du risque pris par rapport à la stratégie sans incitation financière soit au contraire par une augmentation de celui-ci. Finalement, nous montrons en quoi la présence de contraintes de risque de sous-performance, imposées au gérant ou traduisant son aversion à la sous-performance, peut être bénéfique à l'investisseur donnant mandat de gestion financière. / It is common practice to judge third-party asset managers by looking at their financial performance relative to a benchmark portfolio. For this reason, they often choose to rely on internal risk-management models to control the downside risk of their portfolio relative to the benchmark. Moreover, an increasing number are adopting an incentive-based scheme, by charging an over-performance commission relative to the benchmark. Indeed, including this variable component in their global remuneration allows them to increase their revenue in case of over-performance without any penalty in the event of underperforming the benchmark. However, such practices have recently been at the heart of several polemics: the recent global financial crisis has uncovered some shortcomings in terms of internal risk control as well as excessive risk-taking and compensation levels of several financial players. Nevertheless, it appears that analyzing the impact of these practices remains a relatively new issue in continuous time-dynamic asset allocation theory. This thesis analyses in this theoretical framework the implications of these "benchmarking" practices on the asset manager's investment behavior. The first part examines the properties of the optimal dynamic strategy for the asset manager who is concerned by the difference of return between their portfolio and a fix or stochastic benchmark (over- or under-performance). Several asset manager types are considered, defined by different utility functions and different downside-risk constraints. In particular, the link between investment problems with aversion to under-performance and risk management constraints is shown. In the second part, the case of the asset manager who benefits from an incentive compensation scheme (variable asset management fees, over-performance bonuses or additional commission on asset under management), is investigated. We study how, depending on the choice of financial inventive structure and loss aversion level, the asset manager's strategy differs from that of the investor (or the strategy of the asset manager receiving no incentive remuneration). This study shows that the change in investment behavior of the asset manager can lead to both a reduction in the risk taken relative to the strategy without financial incentives or conversely an increase thereof. Finally we show that the existence of downside risk constraints, imposed on the asset manager or corresponding to their aversion for under-performance, can be beneficial to the investor mandating financial management.

本文針對躉繳保費的附保證變額壽險進行評價，保單形式為生死合險，假設投保人可將期初的投資金額連結到兩種投資標的：股價指數及債券型基金，並以BGM模型描述利率的動態過程，然後分別計算不含解約權及含解約權的附保證變額壽險躉繳保費，進而求算出隱含在保單中的保證價值和解約權價值。針對含解約權的附保證變額壽險，以Longstaff and Schwartz(2001)提出的最小平方蒙地卡羅法處理解約的問題。最後，我們求算不同年齡下的男性保費，並且在投資比例、起始最低保證、最低保證給付成長率、針對解約的保證給付成長率和第一個允許的解約時點變動下，分別討論對於保證價值和解約權價值的影響。 結果顯示：(1)當起始最低保證給付等於期初投資金額時，投資在股票的比例越大，越能凸顯保證價值和解約權價值佔保費的比重。以30歲男性為例，保證價值佔不含解約權之附保證變額壽險的比例，由全部投資在債券型基金的0.03%，成長到全部投資在股票的13.86%；而解約權價值佔含解約權之附保證變額壽險的比例，由全部投資在債券型基金的0.05%，成長到全部投資在股票的9.12%。(2)投資比例、起始最低保證給付和最低保證給付成長率越大，保證價值越高。(3)起始最低保證給付和針對解約的保證給付成長率越大，解約權價值越大；而最低保證給付成長率和第一個允許的解約時點越大，解約權價值越小。(4)投資比例隨著最低保證給付不同對解約權價值有不同的影響。 關鍵字：附保證變額壽險、BGM利率模型、解約選擇權、最小平方蒙地卡羅法 / This study emphasizes on the pricing of variable life insurance with minimum guarantees. As an endowment policy in a single premium form, in this paper, it is assumed that the insured can distribute the initial investment amount into two underlying assets: the stock index fund and bond fund. Simulating the interest rate under a BGM model, computational procedures are performed for the single premium of the variable life insurance policy without surrender option and embedding a surrender option, and further, the guarantee value and surrender value embedded in the insurance policy. For the variable life insurance policy embedding a surrender option, the Least Square Monte-Carlo method proposed by Longstaff and Schwartz (2001) is applied to solve the surrender conditions. Finally, we calculate the premium for a male at different ages, and respectively analyze the variations of the guarantee value and surrender value under the influence of the investment portfolio, the initial minimum guaranteed amount, the growth rate of the minimum guarantee, the growth rate of the minimum guarantee for surrender and the first permitted surrender time. The results show that: (1) when the initial minimum guaranteed amount equals the initial investment amount, higher proportion invested in stock will result in larger percentage of the guarantee value and surrender value to total premium. Take a 30-year old male as an example: the percentage of guarantee value to the premium of variable life insurance with minimum guarantee and without a surrender option, which is 0.03% when the initial investment amount thoroughly goes to bond fund, rises up to 13.86% with the entire amount invested in stock index fund. Likewise, the percentage of surrender value to the premium of variable life insurance with minimum guarantee and surrender option is 0.05% with total amount invested in bond fund, while it is 9.12% with the entire amount invested in stock index fund. (2) The higher proportion invested in stock, the initial minimum guaranteed amount and the growth rate of minimum guaranteed amount, the larger guarantee value. (3) Larger initial minimum guaranteed amount and the growth rate of the minimum guaranteed amount for surrender would contribute to a higher surrender value. The higher growth rate of the minimum guaranteed amount and the first permitted surrender time, the lower surrender value. (4) The influence of the investment portfolio to surrender value depends on the initial minimum guaranteed amount. Key words: Variable life insurance with minimum guaranteed amount, BGM interest rate model, surrender option, least squares Monte Carlo approach.

En général, le métabolisme des poissons est estimé à des valeurs de température constantes, mais les effets de fluctuations journalières de température similaires à celles retrouvées en milieu naturel semblent peu connus. Les objectifs du présent mémoire sont de quantifier les effets de la température moyenne d’acclimatation et d’évaluer les effets de l’historique thermique des individus, sur les réponses métaboliques de tacons de saumon Atlantique (Salmo salar) aux fluctuations journalières de la température. Des tacons provenant de deux rivières, une fraîche et une chaude, ont été acclimatés à un maximum de quatre régimes thermiques (constant 15 °C ou 20 °C, fluctuant 15 °C ± 2.5 °C ou 20 °C ± 2.5 °C) et leur taux métabolique standard estimés par respirométrie par débit-intermittent. Les fluctuations journalières de température (15 °C ± 2.5 °C) près de l’optimum thermique pour cette espèce (16 °C) n’affectent pas le taux métabolique standard. À l’opposé, les fluctuations journalières de température plus chaudes (20 °C ± 2.5 °C) augmentent de 35.4% le taux métabolique standard des tacons de la rivière plus chaude, mais pas ceux des poissons de la rivière fraîche. Ainsi, la température moyenne à laquelle sont acclimatés les poissons peut affecter leur réponse métabolique aux fluctuations journalières de température, mais cette réponse peut varier entre populations provenant de rivières présentant des régimes thermiques différents. Enfin, grâce aux données de métabolisme précédemment estimées, un modèle de métabolisme standard a été développé pour des tacons de saumon Atlantique soumis à des fluctuations journalières de température. / Usually, fish metabolism is evaluated under constant values of temperature, but the effects of daily temperature fluctuations similar to those found in natural environment on metabolism seems to be much less understood. The goals of this study are to quantify the effects of the mean acclimation temperature and to assess the effects of the thermal history on the metabolic response of Atlantic salmon (Salmo salar) parr to daily fluctuations of water temperature. Atlantic salmon parr originating from two rivers, one cool and one relatively warm, were acclimated to up to four thermal regimes (constant 15 °C or 20 °C, daily fluctuating 15 °C ± 2.5 °C or 20 °C ± 2.5 °C) and their standard metabolic rate was estimated using intermittent-flow respirometry. Daily temperature fluctuations (15 °C ± 2.5 °C) near this species’ thermal optimum (16 °C) do not influence standard metabolic rate. In contrast, daily fluctuations of higher temperature (20 °C ± 2.5 °C) do increase standard metabolic rate by 35.4% for fish from the warmer river, but not for fish from the cooler river. Therefore, the mean temperature to which fish are acclimated may affect their responses to daily fluctuations of water temperature, but this response may vary between populations originating from rivers having different thermal regimes. Using standard metabolic rates previously estimated, a standard metabolic rate model was developed for Atlantic salmon parr exposed to daily fluctuations of temperature.

可轉換公司債是一種在持有期間內，投資人可以在規定的時間內將債券轉換為股票，或是到期時得到債券報酬的一種複合式證券。因此，可轉債除了具有債券性質之外，還包含另一部份可視為一美式選擇權的股票選擇權。 本篇論文將可轉換債券評價結合數值分析中的最小蒙地卡羅法(Least square monte carlo)，使得在評價可轉債時，能夠具有更多的彈性處理發行公司自行設計的贖回條款與其他各種不同的契約情況。 此外，本篇論文針對股價考慮跳躍的性質，使用Compound Poisson 過程模擬發生跳躍的次數，導入Merton的跳躍模型(Jump-diffusion Model)，在Merton的假設下，模擬未來股價的動態變化。 信用風險方面，本文採用Duffie提出的風險CIR模型評價。考慮存活函數(Survival Function)和違約強度(Hazard Rate Function)，使用CIR模型描述信用違約強度在可轉債持有期間的動態變化，最後模擬出違約的時點，結合LSMC下的可轉債評價評價法。 最後利率部份，雖然Brennan and Schwartz(1980)認為隨機利率對於可轉換債券的評價，並沒有明顯的效果，反而會降低評價時的效率，但是為了符合評價過程的合理性，本文使用CIR短期利率模型。

Les gérants de portefeuille pour compte de tiers sont souvent jugés par leur performance relative à celle d'un portefeuille benchmark. A ce titre, ils sont amenés très fréquemment à utiliser des modèles internes de "risk management" pour contrôler le risque de sous-performer le benchmark. Par ailleurs, ils sont de plus en plus nombreux à adopter une politique de rémunération incitative, en percevant une commission de sur-performance par rapport au benchmark. En effet, cette composante variable de leur rémunération leur permet d'augmenter leur revenu en cas de sur-performance sans contrepartie en cas de sous-performance. Or de telles pratiques ont fait récemment l'objet de nombreuses polémiques : la période récente de crise financière mondiale a fait apparaître certaines carences de plusieurs acteurs financiers en terme de contrôle de risque ainsi que des niveaux de prise de risque et de rémunération jugés excessifs. Cependant, l'étude des implications de ces pratiques reste un thème encore relativement peu exploré dans le cadre de la théorie classique des choix dynamiques de portefeuille en temps continu. Cette thèse analyse, dans ce cadre théorique, les implications de ces pratiques de "benchmarking" sur le comportement d'investissement de l'asset manager. La première partie étudie les propriétés de la stratégie dynamique optimale pour l'asset manager concerné par l'écart entre la rentabilité de son portefeuille et celle d'un benchmark fixe ou stochastique (sur ou sous-performance). Nous considérons plusieurs types d'asset managers, caractérisés par différentes fonctions d'utilité et qui sont soumis à différentes contraintes de risque de sous-performance. Nous montrons en particulier quel est le lien entre les problèmes d'investissement avec prise en compte de l'aversion à la sous-performance et avec contrainte explicite de "risk management". Dans la seconde partie, on s'intéresse à l'asset manager bénéficiant d'une rémunération incitative (frais de gestion variables, bonus de sur-performance ou commission sur encours additionnelle). On étudie, selon la forme de ses incitations financières et son degré d'aversion à la sous-performance, comment sa stratégie d'investissement s'écarte de celle de l'investisseur (ou celle de l'asset manager sans rémunération incitative). Nous montrons que le changement de comportement de l'asset manager peut se traduire soit par une réduction du risque pris par rapport à la stratégie sans incitation financière soit au contraire par une augmentation de celui-ci. Finalement, nous montrons en quoi la présence de contraintes de risque de sous-performance, imposées au gérant ou traduisant son aversion à la sous-performance, peut être bénéfique à l'investisseur donnant mandat de gestion financière. / It is common practice to judge third-party asset managers by looking at their financial performance relative to a benchmark portfolio. For this reason, they often choose to rely on internal risk-management models to control the downside risk of their portfolio relative to the benchmark. Moreover, an increasing number are adopting an incentive-based scheme, by charging an over-performance commission relative to the benchmark. Indeed, including this variable component in their global remuneration allows them to increase their revenue in case of over-performance without any penalty in the event of underperforming the benchmark. However, such practices have recently been at the heart of several polemics: the recent global financial crisis has uncovered some shortcomings in terms of internal risk control as well as excessive risk-taking and compensation levels of several financial players. Nevertheless, it appears that analyzing the impact of these practices remains a relatively new issue in continuous time-dynamic asset allocation theory. This thesis analyses in this theoretical framework the implications of these "benchmarking" practices on the asset manager's investment behavior. The first part examines the properties of the optimal dynamic strategy for the asset manager who is concerned by the difference of return between their portfolio and a fix or stochastic benchmark (over- or under-performance). Several asset manager types are considered, defined by different utility functions and different downside-risk constraints. In particular, the link between investment problems with aversion to under-performance and risk management constraints is shown. In the second part, the case of the asset manager who benefits from an incentive compensation scheme (variable asset management fees, over-performance bonuses or additional commission on asset under management), is investigated. We study how, depending on the choice of financial inventive structure and loss aversion level, the asset manager's strategy differs from that of the investor (or the strategy of the asset manager receiving no incentive remuneration). This study shows that the change in investment behavior of the asset manager can lead to both a reduction in the risk taken relative to the strategy without financial incentives or conversely an increase thereof. Finally we show that the existence of downside risk constraints, imposed on the asset manager or corresponding to their aversion for under-performance, can be beneficial to the investor mandating financial management.

本文之信用風險模型屬於簡約模型(Reduced Form Model)之範疇，以COX過程解釋違約過程，解釋為何企業會發生連帶倒閉的現象。在考慮信用風險後，各期所產生之現金流量變得具不確定性，因此在計算現金流量之現值時，折現因子就必須考慮信用風險溢酬，本文選用信用風險模型中的一大分支-約簡模型，將信用風險量化(包含系統風險及非系統風險)，進而估計出信用價差期間結構；就如同無風險利率期間結構對固定收益商品之重要性，在估計出公司之信用價差期間結構後，即可針對該公司發行之各種商品進行評價分析。本文並以花旗所羅門美邦控股公司為例進行實證，利用公司債理論價格與市價之誤差平方和，求解違約過程之參數估計值及信用價差期間結構；接著，針對花旗所羅門美邦控股公司所發行之連動債券〝TRAGETS〞，進行評價分析並比較考慮信用風險與否是否有助於理論價格與市價之配適。