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Mastering Pandas for Finance

You're reading from   Mastering Pandas for Finance Master pandas, an open source Python Data Analysis Library, for financial data analysis

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Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783985104
Length 298 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with pandas Using Wakari.io FREE CHAPTER 2. Introducing the Series and DataFrame 3. Reshaping, Reorganizing, and Aggregating 4. Time-series 5. Time-series Stock Data 6. Trading Using Google Trends 7. Algorithmic Trading 8. Working with Options 9. Portfolios and Risk Index

The process of algorithmic trading


Algorithmic trading is the use of an automated system to execute trades in a market. These trades are executed in a predetermined manner using one or more algorithms and without human interaction. In this chapter, we will examine several common trading algorithms, along with tools that you can use in combination with pandas to determine the effectiveness of your trading algorithms.

Financial markets move in cycles. Proper identification of the movement of the market can lead to opportunities for profit by making appropriate and timely buys or sells of financial instruments. There are two broad categories for predicting movement in the market, which we will examine in this chapter: momentum strategies and mean-reversion strategies.

Momentum strategies

In momentum trading, trading focuses on stocks that are moving in a specific direction on high volume, measuring the rate of change in price changes. It is typically measured by continuously computing price differences...

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