Introduction

Stochastic Finance comes under the more extensive umbrella of Quantitative Finance, which includes all numerical methods and their computational implementations from purely probabilistic perspectives targeted to solve problems in finance and economics. It shows how to model instruments of financial systems leveraging the randomness present there. The terms stochastic and probabilistic may sound intimidating to many readers. That is natural, especially for people from not-so-good mathematical/statistical backgrounds. However, do not worry; we will delve into these details stepwise. This book talks about different techniques used in Stochastic Finance from theoretical (mathematical details) and practical perspectives – programming and component design examples with Python should give you a 360-degree view of the subject. In addition, despite the availability of ready-made financial modeling systems (mostly, they are not free of cost), it always makes sense to have a transparent idea of their generic working principles. This could be useful when financial investors have limited access/resources to acquire such modeling systems or lack trust.