Python fundamentals

A toolkit for market data

2025MIAX master's, Instituto BME

Figure 1. Simulated efficient frontier coloured by Sharpe ratio

Summary

The master's first block: it downloads prices from Yahoo Finance or Alpha Vantage, cleans them into data classes, runs Monte Carlo simulations and writes the reports, shown here on ten hypothetical portfolios.

Getting the data right

The master's first block: a toolkit for market data in five stages. It downloads prices from Yahoo Finance or Alpha Vantage into a standard format; validates and cleans them, checking for gaps, duplicates and impossible prices; and wraps them in data classes for a price series and a portfolio that compute their own statistics.

Simulation and reports

It runs Monte Carlo simulations with geometric Brownian motion, historical bootstrap or stochastic volatility, with VaR and CVaR; and writes Markdown reports with charts. End-to-end tests cover the whole flow, shown here on ten hypothetical portfolios.

Figures

**Figure 2.** Return against volatility for ten hypothetical portfolios

**Figure 3.** Sharpe ratio of the ten portfolios

**Figure 4.** How the weights are spread across the portfolios

Built with

PythonpandasyfinanceAlpha Vantage APImatplotlib · seabornMonte Carlo