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R Programming and Its Applications in Financial Mathematics

R Programming and Its Applications in Financial Mathematics (Hardcover)

Daisuke Yoshikawa, Shuichi Ohsaki (지은이)
CRC Press
308,750원

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R Programming and Its Applications in Financial Mathematics
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책 정보

· 제목 : R Programming and Its Applications in Financial Mathematics (Hardcover) 
· 분류 : 외국도서 > 경제경영 > 금융/재정 > 일반
· ISBN : 9781498766098
· 쪽수 : 248쪽
· 출판일 : 2018-02-12

목차

Preface

Introduction to R programming

Installation of R

Operators

Data structure

Functions

Control statements

Graphics

Reading and writing data

Reading program

Packages

SECTION I: STATISTICS IN FINANCE

Statistical Analysis with R

Basic Statistics

Probability distribution and random numbers

Hypothesis testing

Regression Analysis

Yield curve analysis using principal component analysis?

Time Series Analysis with R

Preparation of time series data

Before applying for models

The application for AR model

Models extended from AR

Application of the time series analysis to finance: Pair trading

Nonlinear statistics with R

ARCH and GARCH

Nonparametric

Functional Data Analysis

SECTION II: BASIC THEORY OF FINANCE

Modern Portfolio Theory and CAPM

Mean-variance portfolio

Market portfolio

Derivation of CAPM

The extension of CAPM: Multi-factor model

The form of efficient frontier

Interest Rate Swap and Discount Factor

Interest rate swap

Pricing of interest rate swap and derivation of discount factors

Valuation of interest rate swap and risk analysis

Discrete Time Model: Tree Model

Single period binomial model

Multi period binomial model

Trinomial model

Continuous time model and the Black-Scholes Formula

Continuous rate of return

It?o’s lemma

The Black-Scholes formula

Implied volatility

 

SECTION III: NUMERICAL METHODS IN FINANCE

Monte Carlo Simulation

The basic concept of Monte Carlo simulation

Variance reduction method

Exotic option

Multi asset options

Control variates method

Derivative Pricing with Partial Differential Equation

Explicit method

Implicit method

Noise reduction via Kalman Filter

Introduction to Kalman filter

Nonlinear Kalman filter

SECTION IV: APPENDIX 237

A Optimization with R

A.1 Multi variate optimization problem

A.2 Efficient frontier by optimization problem

B Noise reduction via Kalman Filter

B.1 Introduction to Kalman filter

B.2 Nonlinear Kalman filter

C The other references on R

C.1 Information sources on R

C.2 R package on finance

References

Index

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