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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

Motivation

The motivation behind gaining a better understanding of volume is not merely theoretical, but it equally has a great practical relevance. On order-driven markets, if a submitted buy (sell) market order is relatively large compared to the market, it will possibly swipe out several price levels; thus, the achieved average price on the entire trade will be higher (lower) than the best price level at the moment of order submission, and the submitter loses money. This phenomenon is often referred to as price impact, and it is well worth making an effort to avoid or at least minimize it.

One way to do this is to perform order splitting, that is, splitting a market order into smaller chunks and submitting them gradually. Among the numerous logics behind splitting, a popular one is the volume weighted average price (VWAP) strategy that aims to obtain the daily weighted average price where weights are determined by the volume transacted relative to the total daily volume. Long-term investors...

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