---
name: generate_gbm_prices
kind: function
lang: py
domain: finance
version: "1.0.0"
purity: pure
signature: "generate_gbm_prices(initial_price: float, n_ticks: int, sigma: float, mu: float, jump_intensity: float, jump_size_std: float, seed: int) -> list[float]"
description: "Genera serie de precios fundamentales con Geometric Brownian Motion + jump-diffusion. S(t+1) = S(t) * exp((mu - sigma^2/2)*dt + sigma*sqrt(dt)*Z + J*N)."
tags: [simulation, gbm, price, montecarlo, finance, stochastic]
uses_functions: []
uses_types: []
returns: []
returns_optional: false
error_type: ""
imports: [numpy]
tested: false
tests: []
test_file_path: ""
file_path: "python/functions/finance/finance.py"
---

## Ejemplo

```python
prices = generate_gbm_prices(
    initial_price=100.0,
    n_ticks=1000,
    sigma=0.02,
    mu=0.0,
    jump_intensity=0.01,
    jump_size_std=0.05,
    seed=42,
)
# prices[0] == 100.0
# len(prices) == 1000
```

## Notas

Funcion pura — el seed fija el resultado deterministicamente.
`jump_intensity=0.0` desactiva los saltos (GBM puro).
`dt=1.0` por tick (tiempo discreto). Para tiempo continuo, ajustar sigma y mu en consecuencia.
Requiere numpy para la generacion de numeros aleatorios y el calculo de exp.