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Mastering R for Quantitative Finance

You're reading from   Mastering R for Quantitative Finance Use R to optimize your trading strategy and build up your own risk management system

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Length 362 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (15) Chapters Close

Preface 1. Time Series Analysis FREE CHAPTER 2. Factor Models 3. Forecasting Volume 4. Big Data – Advanced Analytics 5. FX Derivatives 6. Interest Rate Derivatives and Models 7. Exotic Options 8. Optimal Hedging 9. Fundamental Analysis 10. Technical Analysis, Neural Networks, and Logoptimal Portfolios 11. Asset and Liability Management 12. Capital Adequacy 13. Systemic Risks Index

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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