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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. What is machine learning and how it being used in the capital market? Explain in brief.

  2. What is logistic regression and in which form does it generate its output?

  3. Write a small piece of code to use a neural network for any stock time series.

  4. How does a confusion matrix explain the accuracy of a model?

  5. How do you standardize data and why is it important in the model building process?

  6. How is support vector machine different from logistic regression?

  7. Explain supervised and unsupervised learning and how to use these techniques in algorithmic trading.

  8. Write a small piece of code for the k means algorithm using any one stock closing price.

  9. Apart from confusionMatrix(), what is the other function to calculate classification and misclassification matrices?

  10. What is the difference between decision tree and random forest and how are features selected from random forest?

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