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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

Stationary and non-stationary time series

It is important that time series data that's used for statistical analysis is stationary in order to perform statistical modeling correctly, as such usages may be for prediction and forecasting. This section introduces the concepts of stationarity and non-stationarity in time series data.

Stationarity and non-stationarity

In empirical time series studies, price movements are observed to drift toward some long-term mean, either upwards or downwards. A stationary time series is one whose statistical properties, such as mean, variance, and autocorrelation, are constant over time. Conversely, observations on non-stationary time series data have their statistical properties...

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