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Find optimal portfolios (weights) - the one with minimal variance (MVP) and maximum Sharp ratio (MSP).

INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS

This project is on Portfolio optimisation and forecasting

1. Choose some assets (5-10) of your interest, possibly from different classes (shares, currencies, ETFs, metals). Either - download time series of these asset(s) prices in csv format, or use API to automatise the download directly in your Jupyter notebook (in the way we have experimented with stooq.com)

2. Present your data graphically, compare performance of these assets in different time horizons. (I.e. last year, last 2 years, last 5 years). Show histograms of rate of return on these assets and check if the distribution is normal or not, assuming some level of confidence of your choice.

3. Find optimal portfolios (weights) - the one with minimal variance (MVP) and maximum Sharp ratio (MSP). Experiment with different time horizons (as in the point above).

Comment on your results. [We assume short selling is not allowed]. The code you write may be based on the code we had used in the classroom when talking about Markowitz Theory.

4. Try to forecast prices of your selected assets for the next 3 months. Take the weights

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