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Python for Finance

You're reading from   Python for Finance If your interest is finance and trading, then using Python to build a financial calculator makes absolute sense. As does this book which is a hands-on guide covering everything from option theory to time series.

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Product type Paperback
Published in Apr 2014
Publisher
ISBN-13 9781783284375
Length 408 pages
Edition 1st Edition
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Tools
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (14) Chapters Close

Preface 1. Introduction and Installation of Python FREE CHAPTER 2. Using Python as an Ordinary Calculator 3. Using Python as a Financial Calculator 4. 13 Lines of Python to Price a Call Option 5. Introduction to Modules 6. Introduction to NumPy and SciPy 7. Visual Finance via Matplotlib 8. Statistical Analysis of Time Series 9. The Black-Scholes-Merton Option Model 10. Python Loops and Implied Volatility 11. Monte Carlo Simulation and Options 12. Volatility Measures and GARCH Index

What is a module?

A module is a package that is written by experts, users, or even a new beginner who is very good in a specific area to serve a specific objective. For example, a Python module is called quant, which is for quantitative financial analysis. The quant combines SciPy and DomainModel. The module contains a domain model that has exchanges, symbols, markets, and historical price, among other things. Modules are very important in Python. In this book, we will mention about a dozen modules implicitly or explicitly. In particular, we will discuss five modules in detail: NumPy and SciPy in Chapter 6, Introduction to NumPy and SciPy; Matplotlib in Chapter 7, Visual Finance via Matplotlib; and Pandas and Statsmodels in Chapter 8, Statistic Analysis of Time Series. As of November 6, 2013, there are 24,955 Python packages with different areas available according to the Python Package Index at https://pypi.python.org/pypi?%3Aaction=browse. For the financial and insurance industry, there...

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