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Mastering R for Quantitative Finance

You're reading from  Mastering R for Quantitative Finance

Product type Book
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Pages 362 pages
Edition 1st Edition
Languages

Table of Contents (20) Chapters

Mastering R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Time Series Analysis 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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