monte-carlo-stock-sim

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monte-carlo-stock-sim

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Pull any stock's history from Yahoo Finance and simulate 10,000 possible versions of its next year

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A Jupyter notebook that pulls any stock's price history off Yahoo Finance and simulates 10,000 possible versions of its next year.

## Run it

```
pip install -r requirements.txt
jupyter notebook monte_carlo.ipynb
```

Change `TICKER` in the settings cell, then run all cells. Anything Yahoo Finance knows about works — `MSFT`, `^GSPC`, `BTC-USD`, `SAP.DE`.

## What it does

It measures two numbers from the last three years of daily log returns: annualised volatility, and expected return. Those feed a geometric Brownian motion model that gets run forward 252 trading days, 10,000 times over.

Out the other end you get a fan chart of every simulated path, the distribution of where they land, and the odds of finishing up, up 20%, or down 20%. The notebook explains each step as it goes, so it doubles as a walkthrough of why the final distribution is lognormal rather than a bell curve.

## Fair warning

GBM assumes volatility is constant and returns are normally distributed. Real markets are neither — volatility clusters, and the tails are much fatter than a bell curve allows. The drift estimate is noisy too: point this at a stock that happened to triple over the last three years and it will cheerfully project it tripling again.

Good for building intuition about how randomness compounds over a year. Bad for picking trades.

## Note on yfinance

Pinned to `>=1.2.0`. Older releases still install fine but get rejected by Yahoo's current API and return empty data — if you get "No price data", check your version first.

monte-carlo-stock-sim

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