| Description |
1 online resource (ix, 248 pages) |
| Contents |
Intro; Half title Page; Title Page; Copyright; Table of Contents; Preface; 1 Introduction to R Programming; 1.1 Installation of R; 1.2 Operators; 1.3 Data structure; 1.3.1 Scalar; 1.3.2 Vector; 1.3.3 Matrix; 1.3.4 List; 1.3.5 Data frame; 1.3.6 Factor; 1.3.7 Investigation of types and structures of data; 1.4 Functions; 1.5 Control statements; 1.5.1 if-statement; 1.5.2 Iterative processing: for-statement, while-statement; 1.6 Graphics; 1.7 Reading and writing data; 1.8 Reading program; 1.9 Packages; SECTION I Statistics in Finance; 2 Statistical Analysis with R; 2.1 Basic statistics |
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2.2 Probability distribution and random numbers2.3 Hypothesis testing; 2.3.1 What is hypothesis testing?; 2.3.2 t-Test of population mean; 2.4 Regression Analysis; 2.5 Yield curve analysis using principal component analysis; 2.5.1 Yield curve; 2.5.2 What is principal component analysis?; 2.5.3 Example of principal component analysis using JGB; 2.5.4 How to calculate the principal component analysis?; 3 Time Series Analysis with R; 3.1 Preparation of time series data; 3.2 Before applying for models; 3.3 The application of the AR model; 3.3.1 Residual analysis; 3.3.2 Forecasting |
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3.4 Models extended from AR3.4.1 ARMA and ARIMA model; 3.4.2 Vector autoregressive; 3.4.3 GARCH model; 3.4.4 Cointegration; 3.5 Application of the time series analysis to finance: Pairs trading; SECTION II Basic Theory of Finance; 4 Modern Portfolio Theory and CAPM; 4.1 Meanvariance portfolio; 4.2 Market portfolio; 4.3 Derivation of CAPM; 4.4 The extension of CAPM : Multifactor model; 4.4.1 Arbitrage Pricing Theory; 4.4.2 FamaFrench's 3 factor model; 4.5 The form of the efficient frontier; 5 Interest Rate Swap and Discount Factor; 5.1 Interest rate swap |
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5.2 Pricing of interest rate swaps and the derivation of discount factors5.3 Valuation of interest rate swaps and their risk; 6 Discrete Time Model: Tree Model; 6.1 Single period binomial model; 6.1.1 Derivative pricing; 6.1.2 Pricing by risk neutral measure; 6.2 Multi period binomial model; 6.2.1 Generalization to the multi period model; 6.2.2 Pricing call options; 6.3 Trinomial model; 7 Continuous Time Model and the BlackScholes Formula; 7.1 Continuous rate of return; 7.2 Itô's lemma; 7.3 The BlackScholes formula; 7.4 Implied volatility; SECTION III Numerical Methods in Finance |
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8 Monte Carlo Simulation; 8.1 The basic concept of Monte Carlo simulation; 8.2 Variance reduction method; 8.2.1 Antithetic variates method; 8.2.2 Moment matching method; 8.3 Exotic options; 8.4 Multi asset options; 8.5 Control variates method; 9 Derivative Pricing with Partial Differential Equations; 9.1 The explicit method; 9.2 The implicit method; APPENDIX; Appendix A Optimization with R; A.1 Multi variate optimization problem; A.2 The efficient frontier by optimization problem; Appendix B Noise Reduction via Kalman Filter; B.1 Introduction to Kalman filter; B.2 Nonlinear Kalman filter |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force. WlAbNL |
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Vendor-supplied metadata |
| Subject |
Finance -- Mathematical models.
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Finance -- Mathematical models -- Data processing
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R (Computer program language)
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BUSINESS & ECONOMICS -- Finance.
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Finance -- Mathematical models
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Finance -- Mathematical models -- Data processing
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R (Computer program language)
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| Form |
Electronic book
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| Author |
Ruppert-Felsot, Jori, author.
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Yoshikawa, Daisuke, author.
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| ISBN |
9781315153810 |
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1315153815 |
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9781351649865 |
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1351649868 |
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9781498766104 |
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1498766102 |
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