This repository contains the materials prepared for the short course/workshop "A Short Introduction to Monte Carlo Methods in Financial Mathematics", which I gave in the context of the 5th International Conference on Mathematical Modelling 5ICMM.
The course was aimed to undergraduate students and general audience interested on Financial Mathematics.
- Get students interested on financial mathematics and maybe even on pursuing a career as a Quant after graduating or after finishing postgraduate education.
- Show them the type of problems that Quants encounter in their jobs as well as the kind of mathematical tools that are required to solve them. In particular, we aim to price an European option under the Black-Scholes model by two methods: obtaining the analytical formula, and using Monte Carlo.
- Illustrate how mathematical concepts are translated into code in Python
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Recall basic concepts on Probaility and Stochastic Processes Theory:
- Random Variables, Stochastic Processes
- Brownian Motion
- Ito's formula
- Geometric Brownian Motion
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Lear how to download financial time series in Python
- Slides
- Notebook 1 - Random Variables
- Notebook 2 - Brownian Motion
- Notebook 3 - Geometric Brownian Motion
- Notebook 4 - How to download market data in Python
- Review the Black-Scholes Model for option pricing
- Review the definition of Monte Carlo
- See how these concepts are translated into code in Python
- Calculate the price of an Asian option using Monte Carlo
- Slides
- Notebook 1 - Black-Scholes model
- Notebook 2 - Monte Carlo to approximate integrals
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