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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
5
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
7
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
8
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
12
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

The simulation method

The best way to understand the role of a bank from a systemic point of view is to simulate the effects of its default. We can get this way the most precise results on a bank's systemic importance. Usually, the main problem with these methods is its data need. The main characteristics of individual institutions (for example, capital buffers or size) are not enough for this kind of exercise. We also have to precisely know its exposures to other banks through financial markets since the most important contagious channels are financial markets.

In this section, we will show a simple method to identify systemic importance of a financial institution. To make it as simple as possible, we have to make some assumptions:

  • We will investigate the effect of idiosyncratic defaults. After the default, all the contagious effects go through the network abruptly.
  • Since all the effects go through abruptly, there won't be any adjustment procedure by banks.
  • LGD is constant for all...

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