Statistics of Financial Markets : An Introduction. 5th ed. 2019

種類:

電子ブック

責任表示:

by Jürgen Franke, Wolfgang Karl Härdle, Christian Matthias Hafner

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2019

著者名:

• Franke, Jürgen.
• Härdle, Wolfgang Karl.
• Hafner, Christian Matthias.
• SpringerLink (Online service)

シリーズ名:

Universitext ;

ISBN:

9783030137519 [3030137511]    

注記:

Preface to the Fith Edition -- Part I Option Pricing -- Derivatives -- Introduction to Option Management -- Basic Concepts of Probability Theory -- Stochastic Processes in Discrete Time -- Stochastic Integrals and Differential Equations -- Black–Scholes Option Pricing Model -- Binomial Model for European Options -- American Options -- Exotic Options -- Interest Rates and Interest Rate Derivatives -- Part II Statistical Models of Financial Time Series -- Introduction: Definitions and Concepts -- ARIMA Time Series Models -- Time Series with Stochastic Volatility -- Long Memory Time Series -- Non-Parametric and Flexible Time Series Estimators -- Part III Selected Financial Applications -- Value at Risk and Backtesting -- Copulae and Value at Risk -- Statistics of Extreme Risks -- Neural Networks and Deep Learning -- Volatility Risk of Option Portfolios -- Nonparametric Estimators for the Probability of Default -- Credit Risk Management and Credit Derivatives -- Financial econometrics of Crypto-currencies -- A Te
Now in its fifth edition, this book offers a detailed yet concise introduction to the growing field of statistical applications in finance. The reader will learn the basic methods for evaluating option contracts, analyzing financial time series, selecting portfolios and managing risks based on realistic assumptions about market behavior. The focus is both on the fundamentals of mathematical finance and financial time series analysis, and on applications to specific problems concerning financial markets, thus making the book the ideal basis for lectures, seminars and crash courses on the topic. All numerical calculations are transparent and reproducible using quantlets. For this new edition the book has been updated and extensively revised and now includes several new aspects such as neural networks, deep learning, and crypto-currencies. Both R and Matlab code, together with the data, can be downloaded from the book’s product page and the Quantlet platform. The Quantlet platform quantlet.de, quantlet.com, quan

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