aelkhair / ErAmine

Quantitative Finance, Financial Machine Learning and visualizations Notebooks

ErAmine

This repository, mainly built around Computational Finance in Python, is a collection of Jupyter Notebooks categorized into folders sharing the same concepts.

1. Assets Allocation and Portfolio Optimization

In this section, I have implemented two concepts about Assets Allocation:

Maximum Sharp Ratio Portfolio

To implement this portfolio's weights calculation, I have used the Monte Carlo Simulation to simulate multiple portfolio's possibilities and then select the one having the maximum sharpe ratio.

Markowitz Portfolio (Modern Portfolio Theory)

To explain

2. Financial Machine Learning

TBD

3. Monte Carlo Simulation

TBD

4. Volatility and Implied Volatility

TBD: SABR, Newton Raphson

5. Options & the Greek Letters

TBD: Jump Diffusion, Black Scholes, Binomial Method, Monte carlo method + Greeks and visualisation

6. Risk Metrics

TBD: Var (histo, para, monte carlo) , cVar, Expected Shortfall

7. Technical Analysis (Visualization)

TBD: MA7 + MA21, Bollinger Bands, MACD, ...