Mastering R for Quantitative Finance.pdf
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Mastering R for Quantitative Finance
Use R to optimize your trading strategy and build up your own risk management system
About This Book
- Learn to manipulate, visualize, and analyze a wide range of financial data with the help of built-in functions and programming in R
- Understand the concepts of financial engineering and create trading strategies for complex financial instruments
- Explore R for asset and liability management and capital adequacy modeling
What You Will Learn
- Analyze high frequency financial data
- Build, calibrate, test, and implement theoretical models such as cointegration, VAR, GARCH, APT, Black-Scholes, Margrabe, logoptimal portfolios, core-periphery, and contagion
- Solve practical, real-world financial problems in R related to big data, discrete hedging, transaction costs, and more.
- Discover simulation techniques and apply them to situations where analytical formulas are not available
- Create a winning arbitrage, speculation, or hedging strategy customized to your risk preferences
- Understand relationships between market factors and their impact on your portfolio
- Assess the trade-off between accuracy and the cost of your trading strategy
The book is organized as a step-by-step practical guide to using R. Starting with time series analysis, you will also learn how to forecast the volume for VWAP Trading. Among other topics, the book covers FX derivatives, interest rate derivatives, and optimal hedging. The last chapters provide an overview on liquidity risk management, risk measures, and more.
The book pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the book, you will be well versed with various financial techniques using R and will be able to place good bets while making financial decisions.


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