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Learning Quantitative Finance with R

You're reading from   Learning Quantitative Finance with R Implement machine learning, time-series analysis, algorithmic trading and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786462411
Length 284 pages
Edition 1st Edition
Languages
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Authors (2):
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PRASHANT VATS PRASHANT VATS
Author Profile Icon PRASHANT VATS
PRASHANT VATS
Dr. Param Jeet Dr. Param Jeet
Author Profile Icon Dr. Param Jeet
Dr. Param Jeet
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to R FREE CHAPTER 2. Statistical Modeling 3. Econometric and Wavelet Analysis 4. Time Series Modeling 5. Algorithmic Trading 6. Trading Using Machine Learning 7. Risk Management 8. Optimization 9. Derivative Pricing

Monte Carlo simulation


Monte Carlo simulation plays a very important role in risk management. Even if we have access to all the relevant information pertaining to risk associated with a firm, it is still not possible to predict the associated risk and quantify it. By the means of Monte Carlo simulation, we can generate all the possible scenarios of risk and using it, we can evaluate the impact of risk and build a better risk mitigation strategy.

Monte Carlo simulation is a computational mathematical approach which gives the user the option of creating a range of possible outcome scenarios, including extreme ones, with the probability associated with each outcome. The possible outcomes are also drawn on the expected line of distribution, which may be closer to real outcomes. The range of possible outcomes can be used in risk analysis for building the models and drawing the inferences. Analysis is repeated again and again using a different set of random values from the probability function...

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