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Mean-Variance Optimization for Cryptocurrencies

Applying Markowitz Mean Variance Optimization to obtain optimal allocation for specified cryptocurrencies using a two-week history of hourly prices

Installation

Runs on Python 3.7. Install all dependencies, as found in requirements.txt. python3 -m pip install -r requirements.txt

Running

From the cloned directory, run python3 main.py

Overview

Running main.py creates a vector of weights for the portfolio using mean-variance portfolio optimization, given a set of target weights. Cryptocurrencies for which to analyze are currently preset to BTC, LTC, and XRP.

The 'Markowitz Bullet' is generated by generating random portfolios; convex optimization is used to attain a set of optimal weights (maximizing return wrt. stddev) for each target stddev.

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