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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
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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

Hedging of derivatives


Hedging means to create a portfolio that offsets the risk of the original exposure. As risk is measured by the fluctuation of the future cash flow, the goal of hedging is usually the reduction of the variance of the total portfolio's value. The first chapter of Daróczi et al. (2013) presents the optimal hedging decision in the presence of the basis risk, when the hedging instrument and the position to be hedged are different. This often happens at the hedging of commodity exposure, because commodities are traded on exchanges, where only standardized (maturity, quantity, and quality) contracts are available.

The optimal hedge ratio is the proportion of the hedging instrument as a percentage of the exposure that minimizes the volatility of the whole position. In this chapter, we will deal with the hedging of derivative positions, assuming that the underlying is also traded in the OTC market; therefore, there will be no mismatch between the exposure and the hedging derivative...

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