Get Free Shipping on orders over $79
Stochastic Finance with Python : Design Financial Models from Probabilistic Perspective - Avishek Nag

Stochastic Finance with Python

Design Financial Models from Probabilistic Perspective

By: Avishek Nag

eText | 13 December 2024

At a Glance

eText


$99.00

or 4 interest-free payments of $24.75 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

Journey through the world of stochastic finance from learning theory, underlying models, and derivations of financial models (stocks, options, portfolios) to the almost production-ready Python components under cover of stochastic finance. This book will show you the techniques to estimate potential financial outcomes using stochastic processes implemented with Python.

The book starts by reviewing financial concepts, such as analyzing different asset types like stocks, options, and portfolios. It then delves into the crux of stochastic finance, providing a glimpse into the probabilistic nature of financial markets. You'll look closely at probability theory, random variables, Monte Carlo simulation, and stochastic processes to cover the prerequisites from the applied perspective. Then explore random walks and Brownian motion, essential in understanding financial market dynamics. You'll get a glimpse of two vital modelling tools used throughout the book - stochastic calculus and stochastic differential equations (SDE).

Advanced topics like modeling jump processes and estimating their parameters by Fourier-transform-based density recovery methods can be intriguing to those interested in full-numerical solutions of probability models. Moving forward, the book covers options, including the famous Black-Scholes model, dissecting it from both risk-neutral probability and PDE perspectives. A chapter at the end also covers the discovery of portfolio theory, beginning with mean-variance analysis and advancing to portfolio simulation and the efficient frontier.

What You Will Learn

  • Understand applied probability and statistics with finance
  • Design forecasting models of the stock price with the stochastic process, Monte-Carlo simulation.
  • Option price estimation with both risk-neutral probabilistic and PDE-driven approach.
  • Use Object-oriented Python to design financial models with reusability.

Who This Book Is For

Data scientists, quantitative researchers and practitioners, software engineers and AI architects interested in quantitative finance

on
Desktop
Tablet
Mobile

More in Corporate Finance

Think Big : Make It Happen in Business and Life - Donald J. Trump

eBOOK

Amazon.com : Get Big Fast - Robert Spector

eBOOK