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Mastering R for Quantitative Finance

By : Gabler

4 (11)

Mastering R for Quantitative Finance

4 (11)

By: Gabler

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.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Time Series Analysis

1. Time Series Analysis

Multivariate time series analysis

Volatility modeling

Summary

References and reading list

2. Factor Models

2. Factor Models

Arbitrage pricing theory

Modeling in R

Summary

References

3. Forecasting Volume

3. Forecasting Volume

Motivation

The intensity of trading

The volume forecasting model

Implementation in R

Summary

References

4. Big Data – Advanced Analytics

4. Big Data – Advanced Analytics

Getting data from open sources

Introduction to big data analysis in R

K-means clustering on big data

Big data linear regression analysis

Summary

References

5. FX Derivatives

5. FX Derivatives

Terminology and notations

Currency options

Exchange options

Quanto options

Summary

References

6. Interest Rate Derivatives and Models

6. Interest Rate Derivatives and Models

The Black model

The Vasicek model

The Cox-Ingersoll-Ross model

Parameter estimation of interest rate models

Using the SMFI5 package

Summary

References

7. Exotic Options

7. Exotic Options

A general pricing approach

The role of dynamic hedging

How R can help a lot

A glance beyond vanillas

Greeks – the link back to the vanilla world

Pricing the Double-no-touch option

Another way to price the Double-no-touch option

The life of a Double-no-touch option – a simulation

Exotic options embedded in structured products

Summary

References

8. Optimal Hedging

8. Optimal Hedging

Hedging of derivatives

Hedging in the presence of transaction costs

Further extensions

Summary

References

9. Fundamental Analysis

9. Fundamental Analysis

The basics of fundamental analysis

Collecting data

Revealing connections

Including multiple variables

Separating investment targets

Setting classification rules

Backtesting

Industry-specific investment

Summary

References

10. Technical Analysis, Neural Networks, and Logoptimal Portfolios

10. Technical Analysis, Neural Networks, and Logoptimal Portfolios

Market efficiency

Technical analysis

Neural networks

Logoptimal portfolios

Summary

References

11. Asset and Liability Management

11. Asset and Liability Management

Data preparation

Interest rate risk measurement

Liquidity risk measurement

Modeling non-maturity deposits

Summary

References

12. Capital Adequacy

12. Capital Adequacy

Principles of the Basel Accords

Risk measures

Risk categories

Summary

References

13. Systemic Risks

13. Systemic Risks

Systemic risk in a nutshell

The dataset used in our examples

Core-periphery decomposition

The simulation method

Possible interpretations and suggestions

Summary

References

Index

Index

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Risk categories

Banks face various kinds of risks, for example, client default, changes in the market environment, troubles in refinancing, and fraud. These risks are categorized into credit risk, market risk, and operational risk.

Market risk

Losses realized from the movements of the market prices are covered by the market risk. It may include the losses on the trading book positions of a bank or financial institution, but the losses realized on interest rate or currency that may be in connection with the core business of a bank also belong to market risk. Market risk can include several subcategories such as equity risk, interest rate risk, currency risk, and commodity risk. Liquidity risk is also covered in this topic. Based on the advanced approach of the Basel II directive, the capital needed to cover these risks is mostly based on value at risk calculations.

Currency risk refers to the possible loss on the movements of the foreign exchange rates (for example, EUR/USD) or on its derivative...

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