financial risk modelling and portfolio optimization with r statistics in practice

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Financial Risk Modelling And Portfolio Optimization With R

Author : Bernhard Pfaff
ISBN : 9781119119685
Genre : Mathematics
File Size : 86. 7 MB
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Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.

Crossover Designs

Author : Kung-Jong Lui
ISBN : 9781119114680
Genre : Mathematics
File Size : 37. 31 MB
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Crossover Designs: Testing, Estimation and Sample Size Kung-Jong Lui, Department of Mathematics and Statistics, San Diego State University, USA A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible. As evidenced by extensive research publications, crossover design can be a useful and powerful tool to reduce the number of patients needed for a parallel group design in studying treatments for non-curable chronic diseases. This book introduces commonly-used and well-established statistical tests and estimators in epidemiology that can easily be applied to hypothesis testing and estimation of the relative treatment effect for various types of data scale in crossover designs. Models with distribution-free random effects are assumed and hence most approaches considered here are semi-parametric. The book provides clinicians and biostatisticians with the exact test procedures and exact interval estimators, which are applicable even when the number of patients in a crossover trial is small. Systematic discussion on sample size determination is also included, which will be a valuable resource for researchers involved in crossover trial design. Key features: l Provides exact test procedures and interval estimators, which are especially of use in small-sample cases. l Presents most test procedures and interval estimators in closed-forms, enabling readers to calculate them by use of a pocket calculator or commonly-used statistical packages. l Each chapter is self-contained, allowing the book to be used a reference resource. l Uses real-life examples to illustrate the practical use of test procedures and estimators l Provides extensive exercises to help readers appreciate the underlying theory, learn other relevant test procedures and understand how to calculate the required sample size. Crossover Designs: Testing, Estimation and Sample Size will be a useful resource for researchers from biostatistics, as well as pharmaceutical and clinical sciences. It can also be used as a textbook or reference for graduate students studying clinical experiments.

Optionsbewertung Und Portfolio Optimierung

Author : Ralf Korn
ISBN : 9783322968883
Genre : Mathematics
File Size : 29. 29 MB
Format : PDF
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Der Erwartungswert-Varianz-Ansatz nach Markowitz - Das zeitstetige Marktmodell (Wertpapierpreise, vollständige Märkte, Ito-Integral und Ito-Formel, Variation der Konstanten, Martingaldarstellungsatz) - Das Optionsbewertungsproblem (Duplikationsprinzip, Satz von Girsanov, Darstellungssatz von Feynman und Kac) - Das Portfolio-Problem in stetiger Zeit (Martingalmethode, HJB-Gleichung, stochastische Steuerung)

Flash Boys

Author : Michael Lewis
ISBN : 9783593424026
Genre : Business & Economics
File Size : 48. 40 MB
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Mit diesem Buch erhalten Sie das E-Book inklusive! Ein Buch, das die Börse zum Beben bringt Michael Lewis, begnadeter Sachbuchautor, lüftet mit seinem neuen Buch "das dunkelste Geheimnis der Börse". Wer an Börse denkt, hat oft ein Bild im Kopf: wild gestikulierende Makler, die unter immensem Zeitdruck Dinge kaufen, um sie gleich wieder zu verkaufen. Doch das ist Geschichte. Die Realität an der Börse sieht anders aus - das Parkett hat längst neue Regeln. Michael Lewis, Wirtschaftsjournalist und begnadeter Sachbuchautor, sorgte mit seinem neuen Buch für ein Erdbeben. Der Erzähler unter den Sachbuchautoren enthüllt die Geschichte einer Gruppe genialer Wall-Street-Außenseiter. Sie haben herausgefunden, wie die Börse zum Vorteil von Insidern manipuliert wird, die ohne Risiko Milliarden absahnen und abends ohne eine einzige Aktie nach Hause gehen. Ein Buch über die neuen "Helden" an der Börse Der Entschluss der "Helden": Sie schaffen ein paralleles System, das sich den raffgierigen "Flash Boys" in den Weg stellt. Lewis bringt Licht in die dunkelste Ecke der Börse. Seine filmreife Geschichte über den Kampf um Geschwindigkeit - auf einem Markt, den zwar keiner sieht, der unsere Wirtschaft aber ernsthaft bedroht - bringt die Wall Street zum Beben. Dieses Buch lässt die Börsenwelt erzittern. Einen Tag nach seinem Erscheinen kündigten FBI und amerikanisches Justizministerium an, sie würden Untersuchungen gegen den von Lewis gegeißelten Hochfrequenzhandel an den Börsen einleiten. Lewis ... - "... hat eine neue Ebene der Aufmerksamkeit erreicht". (FAZ) - ... lässt den "The Wolf of Wall Street" wie ein Lamm wirken. - ... ist der derzeit packendste (Reality-)Thriller über die Finanzwelt gelungen. - ... enthüllt, wie Märkte und Privatanleger manipuliert werden. Links: http://www.faz.net/aktuell/feuilleton/buecher/rezensionen/sachbuch/rezension-flash-boys-von-michael-lewis-12899266.html http://www.handelsblatt.com/finanzen/fonds/nachrichten/hochfrequenzhandel-staatsfonds-fluechtet-vor-den-flash-boys/10019622.html http://www.manager-magazin.de/finanzen/boerse/hochfrequenzhandel-lewis-gefahr-jedermannn-flashcrash-a-973311.html

Modeling Techniques In Predictive Analytics

Author : Thomas W. Miller
ISBN : 9780133886191
Genre : Computers
File Size : 67. 86 MB
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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Einf Hrung In Die Statistik Der Finanzm Rkte

Author : Jürgen Franke
ISBN : 9783642170492
Genre : Business & Economics
File Size : 41. 70 MB
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Modern Portfolio Optimization With Nuopttm S Plus And S Bayestm

Author : Bernd Scherer
ISBN : 9780387275864
Genre : Business & Economics
File Size : 37. 50 MB
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In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.

Zeitreihenmodelle

Author : Andrew C. Harvey
ISBN : 9783486786743
Genre : Business & Economics
File Size : 48. 47 MB
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Gegenstand des Werkes sind Analyse und Modellierung von Zeitreihen. Es wendet sich an Studierende und Praktiker aller Disziplinen, in denen Zeitreihenbeobachtungen wichtig sind.

Lebensversicherungsmathematik

Author : Hans U. Gerber
ISBN : 9783642713101
Genre : Business & Economics
File Size : 73. 36 MB
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Programmieren Mit R

Author : Uwe Ligges
ISBN : 9783540267324
Genre : Mathematics
File Size : 77. 37 MB
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R ist eine objekt-orientierte und interpretierte Sprache und Programmierumgebung für Datenanalyse und Grafik - frei erhältlich unter der GPL. Ziel dieses Buches ist es, nicht nur ausführlich in die Grundlagen der Sprache R einzuführen, sondern auch ein Verständnis der Struktur der Sprache zu vermitteln. Leicht können so eigene Methoden umgesetzt, Objektklassen definiert und ganze Pakete aus Funktionen und zugehöriger Dokumentation zusammengestellt werden. Die enormen Grafikfähigkeiten von R werden detailliert beschrieben. Das Buch richtet sich an alle, die R als flexibles Werkzeug zur Datenenalyse und -visualisierung einsetzen möchten: Studierende, die Daten in Projekten oder für ihre Diplomarbeit analysieren möchten, Forschende, die neue Methoden ausprobieren möchten, und diejenigen, die in der Wirtschaft täglich Daten aufbereiten, analysieren und anderen in komprimierter Form präsentieren.

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