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Python for Finance Cookbook

You're reading from   Python for Finance Cookbook Over 50 recipes for applying modern Python libraries to financial data analysis

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781789618518
Length 432 pages
Edition 1st Edition
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Author (1):
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Eryk Lewinson Eryk Lewinson
Author Profile Icon Eryk Lewinson
Eryk Lewinson
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Table of Contents (12) Chapters Close

Preface 1. Financial Data and Preprocessing 2. Technical Analysis in Python FREE CHAPTER 3. Time Series Modeling 4. Multi-Factor Models 5. Modeling Volatility with GARCH Class Models 6. Monte Carlo Simulations in Finance 7. Asset Allocation in Python 8. Identifying Credit Default with Machine Learning 9. Advanced Machine Learning Models in Finance 10. Deep Learning in Finance 11. Other Books You May Enjoy

Finding the Efficient Frontier using optimization with scipy

In the previous recipe, Finding the Efficient Frontier using Monte Carlo simulations, we used a brute-force approach based on Monte Carlo simulations to visualize the Efficient Frontier. In this recipe, we use a more refined method to determine the frontier.

From its definition, the Efficient Frontier is formed by a set of portfolios offering the highest expected portfolio return for a certain volatility, or offering the lowest risk (volatility) for a certain level of expected returns. We can leverage this fact, and use it in numerical optimization. The goal of optimization is to find the best (optimal) value of the objective function by adjusting the target variables and taking into account some boundaries and constraints (which have an impact on the target variables). In this case, the objective function is a function...

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