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  • Book Overview & Buying Mastering R for Quantitative Finance
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Mastering R for Quantitative Finance

Mastering R for Quantitative Finance

By : Gabler
4 (11)
Buy this Book
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Mastering R for Quantitative Finance

Mastering R for Quantitative Finance

4 (11)
By: Gabler
Buy this Book

Overview of this book

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.
Table of Contents (15 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Free Chapter
1
1. Time Series Analysis
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1. Time Series Analysis
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Multivariate time series analysis
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Volatility modeling
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Summary
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References and reading list
2
2. Factor Models
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2. Factor Models
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Arbitrage pricing theory
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Modeling in R
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Summary
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References
3
3. Forecasting Volume
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3. Forecasting Volume
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Motivation
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The intensity of trading
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The volume forecasting model
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Implementation in R
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Summary
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References
4
4. Big Data – Advanced Analytics
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4. Big Data – Advanced Analytics
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Getting data from open sources
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Introduction to big data analysis in R
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K-means clustering on big data
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Big data linear regression analysis
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Summary
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References
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5. FX Derivatives
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5. FX Derivatives
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Terminology and notations
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Currency options
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Exchange options
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Quanto options
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Summary
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References
6
6. Interest Rate Derivatives and Models
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6. Interest Rate Derivatives and Models
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The Black model
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The Vasicek model
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The Cox-Ingersoll-Ross model
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Parameter estimation of interest rate models
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Using the SMFI5 package
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Summary
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References
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7. Exotic Options
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7. Exotic Options
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A general pricing approach
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The role of dynamic hedging
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How R can help a lot
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A glance beyond vanillas
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Greeks – the link back to the vanilla world
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Pricing the Double-no-touch option
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Another way to price the Double-no-touch option
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The life of a Double-no-touch option – a simulation
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Exotic options embedded in structured products
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Summary
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References
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8. Optimal Hedging
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8. Optimal Hedging
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Hedging of derivatives
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Hedging in the presence of transaction costs
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Further extensions
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Summary
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References
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9. Fundamental Analysis
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9. Fundamental Analysis
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The basics of fundamental analysis
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Collecting data
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Revealing connections
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Including multiple variables
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Separating investment targets
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Setting classification rules
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Backtesting
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Industry-specific investment
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Summary
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References
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10. Technical Analysis, Neural Networks, and Logoptimal Portfolios
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10. Technical Analysis, Neural Networks, and Logoptimal Portfolios
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Market efficiency
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Technical analysis
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Neural networks
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Logoptimal portfolios
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Summary
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References
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11. Asset and Liability Management
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11. Asset and Liability Management
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Data preparation
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Interest rate risk measurement
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Liquidity risk measurement
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Modeling non-maturity deposits
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Summary
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References
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12. Capital Adequacy
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12. Capital Adequacy
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Principles of the Basel Accords
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Risk measures
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Risk categories
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Summary
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References
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13. Systemic Risks
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13. Systemic Risks
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Systemic risk in a nutshell
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The dataset used in our examples
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Core-periphery decomposition
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The simulation method
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Possible interpretations and suggestions
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Summary
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References
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Index
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Index

Summary

In this chapter, we demonstrated how R can support the process of asset and liability management in a commercial bank. There is a wide range of tasks from data preparation to reporting, where the R programming language can help or solve repeating problems. However, we only gave a brief introduction about how to solve problems of interest rate and liquidity measurement. We also provided some examples about the statistical estimation of the interest rate sensitivity of non-maturity deposits. You can find practical knowledge about the following:

  • Generating cash-flow from bank portfolios and market data

  • Measuring and reporting tools for basic interest rate risk management

  • Measuring and reporting tools for basic liquidity risk management

  • Modeling the behavior of non-maturity deposits

We think that this chapter is an organic part of the bank management topics in this book. Asset and liability management brings a particular problem set of the bank management, and R, as an open-source language...

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