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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 Monte Carlo simulations

According to the Modern Portfolio Theory, the Efficient Frontier is a set of optimal portfolios in the risk-return spectrum. This means that the portfolios on the frontier:

  • Offer the highest expected return for a given level of risk
  • Offer the lowest level of risk for a given level of expected returns

All portfolios located under the Efficient Frontier curve are considered sub-optimal, so it is always better to choose the ones on the frontier instead.

In this recipe, we show how to find the Efficient Frontier using Monte Carlo simulations. We build thousands of portfolios, using randomly assigned weights, and visualize the results. To do so, we use the returns of four US tech companies from 2018.

How to do it...

...
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