Analyzing Financial Data and Implementing Financial Models Using R

Author: Clifford Ang
Publisher: Springer
ISBN: 3319140752
Format: PDF, Docs
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This book is a comprehensive introduction to financial modeling that teaches advanced undergraduate and graduate students in finance and economics how to use R to analyze financial data and implement financial models. This text will show students how to obtain publicly available data, manipulate such data, implement the models, and generate typical output expected for a particular analysis. This text aims to overcome several common obstacles in teaching financial modeling. First, most texts do not provide students with enough information to allow them to implement models from start to finish. In this book, we walk through each step in relatively more detail and show intermediate R output to help students make sure they are implementing the analyses correctly. Second, most books deal with sanitized or clean data that have been organized to suit a particular analysis. Consequently, many students do not know how to deal with real-world data or know how to apply simple data manipulation techniques to get the real-world data into a usable form. This book will expose students to the notion of data checking and make them aware of problems that exist when using real-world data. Third, most classes or texts use expensive commercial software or toolboxes. In this text, we use R to analyze financial data and implement models. R and the accompanying packages used in the text are freely available; therefore, any code or models we implement do not require any additional expenditure on the part of the student. Demonstrating rigorous techniques applied to real-world data, this text covers a wide spectrum of timely and practical issues in financial modeling, including return and risk measurement, portfolio management, options pricing, and fixed income analysis.

Versicherungs konomie

Author: Peter Zweifel
Publisher: Springer-Verlag
ISBN: 3662107848
Format: PDF, Mobi
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Das Buch macht den Leser mit den zentralen Fragestellungen und dem analytischen Werkzeug der Versicherungsökonomik vertraut. Es führt Beiträge zur Nachfrage nach Versicherung, zum Angebot an Versicherung und der Versicherungsregulierung sowie zur Sozialversicherung in einer vereinheitlichten Darstellung zusammen, die bisher nur verstreut in Zeitschriften und Sammelbänden verfügbar waren. Es werden empirisch überprüfbare Voraussagen der Theorie abgeleitet und den Ergebnissen internationaler empirischer Forschung gegenübergestellt. Ausformulierte Folgerungen fassen den Stoff zusammen und erleichtern die Kontrolle des Wissensstands.

Statistical Analysis of Financial Data in S Plus

Author: René Carmona
Publisher: Springer Science & Business Media
ISBN: 9780387202860
Format: PDF
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This book develops the use of statistical data analysis in finance, and it uses the statistical software environment of S-PLUS as a vehicle for presenting practical implementations from financial engineering. It is divided into three parts. Part I, Exploratory Data Analysis, reviews the most commonly used methods of statistical data exploration. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. Part II, Regression, introduces modern regression concepts with an emphasis on robustness and non-parametric techniques. The applications include the term structure of interest rates, the construction of commodity forward curves, and nonparametric alternatives to the Black Scholes option pricing paradigm. Part III, Time Series and State Space Models, is concerned with theories of time series and of state space models. Linear ARIMA models are applied to the analysis of weather derivatives, Kalman filtering is applied to public company earnings prediction, and nonlinear GARCH models and nonlinear filtering are applied to stochastic volatility models. The book is aimed at undergraduate students in financial engineering, master students in finance and MBA's, and to practitioners with financial data analysis concerns.

Zeitreihenmodelle

Author: Andrew C. Harvey
Publisher: De Gruyter Oldenbourg
ISBN: 9783486230062
Format: PDF, Mobi
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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.

Statistical Analysis of Financial Data in R

Author: René Carmona
Publisher: Springer Science & Business Media
ISBN: 1461487889
Format: PDF, Docs
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Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns of risk management are addressed by the study of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Principal component analysis (PCA), smoothing, and regression techniques are applied to the construction of yield and forward curves. Time series analysis is applied to the study of temperature options and nonparametric estimation. Nonlinear filtering is applied to Monte Carlo simulations, option pricing and earnings prediction. This textbook is intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. It is sprinkled with practical examples using market data, and each chapter ends with exercises. Practical examples are solved in the R computing environment. They illustrate problems occurring in the commodity, energy and weather markets, as well as the fixed income, equity and credit markets. The examples, experiments and problem sets are based on the library Rsafd developed for the purpose of the text. The book should help quantitative analysts learn and implement advanced statistical concepts. Also, it will be valuable for researchers wishing to gain experience with financial data, implement and test mathematical theories, and address practical issues that are often ignored or underestimated in academic curricula. This is the new, fully-revised edition to the book Statistical Analysis of Financial Data in S-Plus. René Carmona is the Paul M. Wythes '55 Professor of Engineering and Finance at Princeton University in the department of Operations Research and Financial Engineering, and Director of Graduate Studies of the Bendheim Center for Finance. His publications include over one hundred articles and eight books in probability and statistics. He was elected Fellow of the Institute of Mathematical Statistics in 1984, and of the Society for Industrial and Applied Mathematics in 2010. He is on the editorial board of several peer-reviewed journals and book series. Professor Carmona has developed computer programs for teaching statistics and research in signal analysis and financial engineering. He has worked for many years on energy, the commodity markets and more recently in environmental economics, and he is recognized as a leading researcher and expert in these areas.

Optionsbewertung und Portfolio Optimierung

Author: Ralf Korn
Publisher: Springer-Verlag
ISBN: 3322832104
Format: PDF, ePub, Mobi
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Es werden die typischen Aufgabenstellungen der zeitstetigen Modellierung von Finanzmärkten wie Optionsbewertung (insbesondere auch die Black-Scholes-Formel und zugehörige Varianten) und Portfolio-Optimierung (Bestimmen optimaler Investmentstrategien) behandelt. Die benötigten mathematischen Werkzeuge (wie z. B. Brownsche Bewegung, Martingaltheorie, Ito-Kalkül, stochastische Steuerung) werden in selbständigen Exkursen bereitgestellt. Das Buch eignet sich als Grundlage einer Vorlesung, die sich an einen Grundkurs in Stochastik anschließt. Es richtet sich an Mathematiker, Finanz- und Wirtschaftsmathematiker in Studium und Beruf und ist aufgrund seiner modularen Struktur auch für Praktiker in den Bereichen Banken und Versicherungen geeignet.

77 Tools f r Design Thinker

Author: Ingrid Gerstbach
Publisher: GABAL Verlag GmbH
ISBN: 3956235371
Format: PDF, ePub, Docs
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Innovation ist heute der erfolgs- und wettbewerbsentscheidende Faktor für Unternehmen. Doch auf Knopfdruck kreativ zu sein ist gar nicht so einfach. Die gute Nachricht: Innovation ist kein Zufall. Die ideale und etablierte Methode, um sowohl kreativ als auch systematisch Innovationen zu generieren, ist Design Thinking. Für den Design-Thinking-Praktiker ist es dabei wichtig, die spezifischen Techniken und Fähigkeiten zu kennen, die an den verschiedenen Punkten während des Innovationsprozesses eingesetzt werden können. Er muss mit einer Vielzahl unterschiedlicher Prozedere vertraut sein, um das richtige Tool für ein Projekt und das entsprechende Team auszuwählen. In ihrem neuen Buch stellt Design-Thinking-Expertin Ingrid Gerstbach 77 praxiserprobte Tools für die tägliche Arbeit im Design-Thinking-Prozess zusammen. Übersichtlich und klar strukturiert erläutert sie die Schlüsselaktivitäten eines jeden Prozessschritts und zeigt detailliert, wie und wann das Verfahren im Projekt eingesetzt werden kann. Eine Anleitung für jede Methode unterstützt Sie bei der Umsetzung in Ihrer täglichen Arbeit.

Meta Heuristics Optimization Algorithms in Engineering Business Economics and Finance

Author: Vasant, Pandian M.
Publisher: IGI Global
ISBN: 1466620870
Format: PDF, Docs
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Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.