Probability of a Touch in Finance using Python Monte Carlo Methods

We use Monte Carlo methods with Python to calculate the probability of a stock reaching a given price in a specified amount of time. The code simulates a large number of potential stock prices using the implied volatility to get the width of the normal distribution used to sample random numbers. The code then counts the number of runs where the target price is reached and estimates the probability by taking the ratio of that number with the total number of simulated runs.

Github: https://github.com/kpmooney/numerical_methods_youtube

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