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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

Summary


In this chapter, we have shown some practical problems that arise in the hedging of derivatives. Although the Black-Scholes-Merton model assumes continuous time trading, resulting in continuous rebalancing of the hedging portfolio without transaction costs, in reality, trading occurs in discrete time, and it does have costs. Consequently, the cost of hedging depends on the future path of the spot price of the underlying asset; thus, it is not a single value presented by the analytical formula any more, but it is a stochastic variable that can be described by its probability distribution. In this chapter, we simulated different paths, calculated the cost of hedging, and presented the probability distribution assuming different rebalancing frequencies. We received that in the absence of transaction costs the volatility reduces with the shortening of the rebalancing period. On the other hand, transaction costs can boost not only the expected value of the cost of the hedge but also its...

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