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Jackal08 committed May 21, 2020
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# Chapter 10 Exercise Solutions

## Introduction
This folder contains the notebook that provides the worked solutions to the exercises found at the end of Chapter 10 of "Advances in Financial Machine Learning" by Marcos López de Prado (2018), as well as an implementation of the EF3M algorithm from "A mixture of Gaussians approach to mathematical portfolio oversight: The EF3M algorithm." _Quantitative Finance_, Vol. 14, No. 5, pp. 913-930, which is used in the exercise solutions.

## Contents
1. `Chapter10_Exercises.ipynb` - notebook with solutions using self contained code
2. `Chapter10_Exercises (mlfinlab).ipynb` - notebook with solutions using the `bet_sizing` functionality of the `mlfinlab` module
2. `ef3m_test.ipynb` - test cases for the EF3M algorithm
3. `EF3M` - small library containing the implementation of EF3M (used in `Chapter10_Exercises.ipynb`)
1. `ef3m.py` - Python file containing the class and methods
2. `__init__.py` - init file for `ef3m.py`

# Chapter 10 Exercise Solutions

## Introduction
This folder contains the notebook that provides the worked solutions to the exercises found at the end of Chapter 10 of "Advances in Financial Machine Learning" by Marcos López de Prado (2018), as well as an implementation of the EF3M algorithm from "A mixture of Gaussians approach to mathematical portfolio oversight: The EF3M algorithm." _Quantitative Finance_, Vol. 14, No. 5, pp. 913-930, which is used in the exercise solutions.

## Contents
1. `Chapter10_Exercises.ipynb` - notebook with solutions using self contained code
2. `Chapter10_Exercises (mlfinlab).ipynb` - notebook with solutions using the `bet_sizing` functionality of the `mlfinlab` module
2. `ef3m_test.ipynb` - test cases for the EF3M algorithm
3. `EF3M` - small library containing the implementation of EF3M (used in `Chapter10_Exercises.ipynb`)
1. `ef3m.py` - Python file containing the class and methods
2. `__init__.py` - init file for `ef3m.py`

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