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- Understand the fundamentals of Python data structures and work with time-series data
- Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib
- A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance

This book uses Python as its computational tool. Since Python is free, any school or
organization can download and use it.
This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.
The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory,
options and futures.
This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk,
running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.

[*]Become acquainted with Python in the first two chapters
[*] Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models
[*]Learn how to price a call, put, and several exotic options
[*]Understand Monte Carlo simulation, how to write a Python program to
replicate the Black-Scholes-Merton options model, and how to price a few
exotic options
[*]Understand the concept of volatility and how to test the hypothesis that
volatility changes over the years
[*]Understand the ARCH and GARCH processes and how to write related
Python programs

Download this book in **EPUB** and **PDF** formats

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Publication date :
Jun 30, 2017

Length
586 pages

Edition :
2nd Edition

Language :
English

ISBN-13 :
9781787125698

Category :

Languages :

Concepts :

Python for Finance Second Edition

Credits

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Preface

1. Python Basics

2. Introduction to Python Modules

3. Time Value of Money

4. Sources of Data

5. Bond and Stock Valuation

6. Capital Asset Pricing Model

7. Multifactor Models and Performance Measures

8. Time-Series Analysis

9. Portfolio Theory

10. Options and Futures

11. Value at Risk

12. Monte Carlo Simulation

13. Credit Risk Analysis

14. Exotic Options

15. Volatility, Implied Volatility, ARCH, and GARCH

Index

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Feb 7, 2024

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