The repo contains my personal work/ projects related to quantitative finance in Python.
When we speak about some mathematics in Finance, we know that it has something to do with data. That is correct. Although a lot of people are very interested in quatitative finace, they seem to know a little about it. There are few miscenceptions as well. First, they think it's just some basic number crunching but it's not true. Second, they think it's a lot of deep mathematics but unfortunately, that is not a proper idea as well. Third, they think it's related to machine learning but trust me, ML is just 0.01% of quantitative finance.
I am starting to write this series of notebooks with pyhton codes and some dummy data to show example of most diffcult concepts of quantitative finance aiming to help best finance professionals. That is why my series is named as "When Finance meets Statistics".
Chapter 1: Fundamentals of Statistical Finance
Chapter 2: Martingales, Random Walks and Time Series models for Statistical Finance
Chapter 3: Capital Asset Pricing Models and Hedge Models
Chapter 4: Brownian Motion, Black Scholes Model and Some Advanced applications
Chapter 5: Machine Learning Applications (Case studies)