R Programming and Its Applications in Financial Mathematics

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A01=Daisuke Yoshikawa
A01=Jori Ruppert-Felsot
A01=Shuichi Ohsaki
advanced R programming for financial modeling
AR Model
Arrow Debreu Securities
Author_Daisuke Yoshikawa
Author_Jori Ruppert-Felsot
Author_Shuichi Ohsaki
Average Option Price
Binomial Model
Black Scholes Formula
Black Scholes Partial Differential Equation
Black-Sholes formula
Call Option
Category=KCH
Category=KF
Category=PBT
Category=PBW
Control Variates Method
Cumulative Distribution Function
Daisuke Yoshikawa
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
financial data analysis
Finite Difference Method
GARCH Model
graduate level finance
Interest Rate Swap
Iv
Jori Ruppert-Felsot
Market Portfolio
Moment Matching Method
Monte Carlo simulation
Normal MC
numerical methods for finance
optimization in finance
Pair Trading
parameter estimation
portfolio optimization techniques
Pricing Derivatives
Principal Component Score
quantitative finance methods
R language
Rate Swap
Risk Neutral Measure
Risky Asset
Safe Asset
Short Selling Constraints
statistical analysis
statistics for finance
stochastic processes finance
Strike Price
time series analysis
time series modeling
tree model

Product details

  • ISBN 9781498766098
  • Weight: 572g
  • Dimensions: 156 x 234mm
  • Publication Date: 12 Feb 2018
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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This book provides an introduction to R programming and a summary of financial mathematics.

It is not always easy for graduate students to grasp an overview of the theory of finance in an abstract form. For newcomers to the finance industry, it is not always obvious how to apply the abstract theory to the real financial data they encounter. Introducing finance theory alongside numerical applications makes it easier to grasp the subject.

Popular programming languages like C++, which are used in many financial applications are meant for general-purpose requirements. They are good for implementing large-scale distributed systems for simultaneously valuing many financial contracts, but they are not as suitable for small-scale ad-hoc analysis or exploration of financial data. The R programming language overcomes this problem. R can be used for numerical applications including statistical analysis, time series analysis, numerical methods for pricing financial contracts, etc.

This book provides an overview of financial mathematics with numerous examples numerically illustrated using the R programming language.

After finishing a Ph.D course at Kyoto University, Dr. Daisuke Yoshikawa worked for Mizuho-DL financial technology and Bank of Japan. Meanwhile, Dr. Yoshikawa published a few refereed journal papers on finance. Currently, Dr. Yoshikawa is working for Hokkai-Gakuen University as a lecturer.

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