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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 2. Statistical Modeling FREE CHAPTER 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

Questions


  1. How do you import stock data into the R workspace from Yahoo Finance?

  2. How do you generate a momentum strategy using moving average crossover?

  3. Which package helps to calculate the performance metrics of a strategy?

  4. How do you calculate the covariance matrix for a portfolio consisting of five stocks?

  5. Extract MSFT data from Yahoo and test that the closing price series is non-stationary.

  6. Use the distance method to generate trading signals which exit when the spread reverts to mean.

  7. How do you test a pair of stocks for co-integration and write code to test it?

  8. How do you calculate hedge ratio and how does it helps in trading?

  9. How do you calculate portfolio beta? Show it using an example.

  10. How do you use the fundamental factor to create quantiles and quantile spread?

  11. Write code to calculate portfolio expected _return and standard deviation.

  12. How do you calculate the efficient frontier and plot it using the R command?

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