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An asset allocation app useful to study how to diversify a passive portfolio.
Through this app you select two sets of weights for two different buy & hold portfolios and the app runs a stationary bootstrap method for both portfolios; the algorithm locks the same random state generator of stochastic path for both sets of weights. In this way you can evaluate two passive portfolios ceteris paribus. Each time you select the two different sets of weights the algorith will refresh the random state generator, always by locking the same stochastic generator for both asset allocations.
You can choose weights among 3 assets:
- An ETF that tracks the S&P500 index
- An ETF that tracks the US 10-year T-bonds
- An ETF/ETC on Gold
The model takes into account costs (except taxes) and severe scenarios.
You can find more informations in the sections The explanation of the model and Hypothesis and results.
Requirements
Python 3.6 version or superior
How to run this demo
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cd to the directory where requirements.txt is located
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activate your virualenv
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run:
pip install -r requirements.txt
in your shell
git clone https://github.com/antonio-catalano/PassivePortfolioStrategy.git
cd into the project folder
'path'>cd PassivePortfolioStrategy
streamlit run app.py
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