Option Valuation with Conditional Heteroskedasticity and Non-Normality

We provide results for the valuation of European style contingent claims for a large class of specifications of the underlying asset returns. Our valuation results obtain in a discrete time, infinite state-space setup using the no-arbitrage principle and an equivalent martingale measure. Our approach allows for general forms of heteroskedasticity in returns, and valuation results for homoskedastic processes can be obtained as a special case. It also allows for conditional non-normal return innovations, which is critically important because heteroskedasticity alone does not suffice to capture the option smirk. We analyze a class of equivalent martingale measures for which the resulting risk-neutral return dynamics are from the same family of distributions as the physical return dynamics. In this case, our framework nests the valuation results obtained by Duan (1995) and Heston and Nandi (2000) by allowing for a time-varying price of risk and non-normal innovations. We provide extensions of these results to more general equivalent martingale measures and to discrete time stochastic volatility models, and we analyze the relation between our results and those obtained for continuous time models. Nous présentons les résultats d’une étude portant sur l’évaluation de créances éventuelles de style européen pour une grande variété de caractéristiques liées au rendement des actifs sous-jacents. Les résultats de notre évaluation proposent en temps discret une formule état-espace infinie, à partir du principe de non-arbitrage et d’une mesure de martingale équivalente. Notre approche permet de tenir compte de formes générales d’hétéroscédasticité dans les rendements et d’obtenir, dans des cas spéciaux, des résultats d’évaluation liés aux processus homoscédastiques. Elle permet aussi de considérer les innovations conditionnellement non normales en matière de rendement, ce qui représente un facteur critique, compte tenu du fait que l’hétéroscédasticité ne permet pas, à elle seule, de saisir pleinement le caractère ironique de l’option. Nous analysons une catégorie de mesures de martingale équivalentes dont la dynamique du rendement risque-neutre obtenu est de la même famille de distribution que la dynamique du rendement physique. Dans ce cas, notre cadre d’étude soutient les résultats d’évaluation obtenus par Duan (1995) et par Heston et Nandi (2000) et tient compte du coût du risque variant dans le temps et des innovations non normales. Nous étendons ces résultats aux mesures de martingale équivalentes plus générales et aux modèles de volatilité stochastique en temps discret et analysons aussi la relation entre nos résultats et ceux obtenus dans le cas des modèles en temps continu.GARCH, risk-neutral valuation, no-arbitrage, non-normal innovations, GARCH (hétéroscédasticité conditionnelle autorégressive généralisée), évaluation du risque neutre, absence d’arbitrage, innovations non normales

Model-based Purchase Predictions for Large Assortments

Being able to accurately predict what a customer will purchase next is of paramount importance to successful online retailing. In practice, customer purchase history data is readily available to make such predictions, sometimes complemented with customer characteristics. Given the large assortments maintained by online retail- ers, scalability of the prediction method is just as important as its accuracy. We study two classes of models that use such data to predict what a customer will buy next: A novel approach that uses latent Dirichlet allocation (LDA), and mixtures of Dirichlet-Multinomials (MDM). A key benefit of a model-based approach is the potential to accommodate observed customer heterogeneity through the inclusion of predictor variables. We show that LDA can be extended in this direction while retaining its scalability. We apply the models to purchase data from an online re- tailer and contrast their predictive performance with that of a collaborative filter and a discrete choice model. Both LDA and MDM outperform the other meth- ods. Moreover, LDA attains performance similar to that of MDM while being far more scalable, rendering it a promising approach to purchase prediction in large assortments

Marketing Analytics for High-Dimensional Assortments

Over the past two decades online retailing has become ubiquitous and today’s large online retailers enable customers to purchase virtually any product. As a consequence product assortments at such retailers are of a different order of magnitude compared to the traditional brick-and-mortar stores. In this dissertation model-based methods are presented that can be used to model purchase decisions in such high-dimensional product assortments. These methods are able to accurately predict at the individual customer level which product will be purchased next out of the large assortment. In addition, the methods provide substantive insights in the patterns that underlie the observed purchase behavior. The applicability of such methods in practice hinges on their scalability and this holds especially true for online retailers. Model results should be rapidly obtained and the estimation time should not significantly increase in case the customer base or product assortment expands. Scalability is therefore a focal point in this dissertation. The methods introduced are adaptations and extensions of fast scalable methods from the machine learning literature that make these methods also suitable for the online retailing context. This ensures that estimation times remain feasible even if the size of the retailer increases and opens the way for advanced model-based marketing analytics in high-dimensional assortments

Access to medicines from a health system perspective

Most health system strengthening interventions ignore interconnections between systems components. In particular, complex relationships between medicines and health financing, human resources, health information and service delivery are not given sufficient consideration. As a consequence, populations' access to medicines (ATM) is addressed mainly through fragmented, often vertical approaches usually focusing on supply, unrelated to the wider issue of access to health services and interventions. The objective of this article is to embed ATM in a health system perspective. For this purpose, we perform a structured literature review: we examine existing ATM frameworks, review determinants of ATM and define at which level of the health system they are likely to occur; we analyse to which extent existing ATM frameworks take into account access constraints at different levels of the health system. Our findings suggest that ATM barriers are complex and interconnected as they occur at multiple levels of the health system. Existing ATM frameworks only partially address the full range of ATM barriers. We propose three essential paradigm shifts that take into account complex and dynamic relationships between medicines and other components of the health system. A holistic view of demand-side constraints in tandem with consideration of multiple and dynamic relationships between medicines and other health system resources should be applied; it should be recognized that determinants of ATM are rooted in national, regional and international contexts. These are schematized in a new framework proposing a health system perspective on AT

Using XDAQ in Application Scenarios of the CMS Experiment

XDAQ is a generic data acquisition software environment that emerged from a rich set of of use-cases encountered in the CMS experiment. They cover not the deployment for multiple sub-detectors and the operation of different processing and networking equipment as well as a distributed collaboration of users with different needs. The use of the software in various application scenarios demonstrated the viability of the approach. We discuss two applications, the tracker local DAQ system for front-end commissioning and the muon chamber validation system. The description is completed by a brief overview of XDAQ.Comment: Conference CHEP 2003 (Computing in High Energy and Nuclear Physics, La Jolla, CA

The CMS Event Builder

The data acquisition system of the CMS experiment at the Large Hadron Collider will employ an event builder which will combine data from about 500 data sources into full events at an aggregate throughput of 100 GByte/s. Several architectures and switch technologies have been evaluated for the DAQ Technical Design Report by measurements with test benches and by simulation. This paper describes studies of an EVB test-bench based on 64 PCs acting as data sources and data consumers and employing both Gigabit Ethernet and Myrinet technologies as the interconnect. In the case of Ethernet, protocols based on Layer-2 frames and on TCP/IP are evaluated. Results from ongoing studies, including measurements on throughput and scaling are presented. The architecture of the baseline CMS event builder will be outlined. The event builder is organised into two stages with intelligent buffers in between. The first stage contains 64 switches performing a first level of data concentration by building super-fragments from fragments of 8 data sources. The second stage combines the 64 super-fragments into full events. This architecture allows installation of the second stage of the event builder in steps, with the overall throughput scaling linearly with the number of switches in the second stage. Possible implementations of the components of the event builder are discussed and the expected performance of the full event builder is outlined.Comment: Conference CHEP0

5,6,7,8-Tetra­hydro­quinoline 1-oxide hemihydrate

In the title compound, C9H11NO·0.5H2O, the asymmetric unit contains two similar mol­ecules of 5,6,7,8-tetra­hydro­quinoline 1-oxide and one water mol­ecule. The water mol­ecule links the two O atoms of both independent N-oxides into dimers via O—H⋯O hydrogen bonds, forming a three-dimensional network along [101], which is additionally stabilized by weak C—H⋯O inter­molecular inter­actions. In each mol­ecule, the saturated six-membered rings exist in a conformation inter­mediate between a half-chair and sofa