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Mastering Python for Finance. - Second Edition

You're reading from  Mastering Python for Finance. - Second Edition

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Pages 426 pages
Edition 2nd Edition
Languages
Author (1):
James Ma Weiming James Ma Weiming
Profile icon James Ma Weiming

Table of Contents (16) Chapters

Preface Section 1: Getting Started with Python
Overview of Financial Analysis with Python Section 2: Financial Concepts
The Importance of Linearity in Finance Nonlinearity in Finance Numerical Methods for Pricing Options Modeling Interest Rates and Derivatives Statistical Analysis of Time Series Data Section 3: A Hands-On Approach
Interactive Financial Analytics with the VIX Building an Algorithmic Trading Platform Implementing a Backtesting System Machine Learning for Finance Deep Learning for Finance Other Books You May Enjoy

Conclusion on the use of machine learning algorithms

You may have observed that predicted values from our models are far off from actual values. This chapter aims to demonstrate the best of the machine learning features that scikit-learn offers, which may possibly be used to predict time series data. No studies to date have shown that machine learning algorithms can predict prices even close to 100% of the time. A lot more effort goes into building and running machine learning systems effectively.

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