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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 measures

Financial risk is a tangible and quantifiable concept, a value that you can lose on a certain financial investment. Note that here, we strictly differentiate between uncertainty and risk, where the latter is measurable with mathematical-statistical methods with exact probabilities of the different outcomes. However, there are various kinds of measures for financial risks. The most common risk measure is the standard deviation of the returns of a certain financial instrument. Although it is very widespread and easy to use, it has some major disadvantages. One of the most important problems of the standard deviation as a risk measurement is that it treats upside potential the same way as downside risk. In other words, it also punishes a financial instrument that might bring huge positive returns and little negative ones than a less volatile asset.

Consider the following extreme example. Let's assume that we have two stocks on the stock market and we can exactly measure the...

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