Probabilistic Machine Learning for Finance and Investing
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Machine learning AI artificial intelligence Python probabilistic programming finance investments Bayesian inference maximum likelihood statistics risk uncertainty probability PyMC3
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Product details
- ISBN 9781492097679
- Dimensions: 178 x 233mm
- Publication Date: 25 Aug 2023
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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Whether based on academic theories or machine learning strategies, all financial models are at the mercy of modeling errors that can be mitigated but not eliminated. Probabilistic ML technologies are based on a simple and intuitive definition of probability and the rigorous calculus of probability theory.
These systems treat uncertainties and errors of financial and investing systems as features, not bugs. And they quantify uncertainty generated from inexact inputs and outputs as probability distributions, not point estimates. This makes for realistic financial inferences and predictions that are useful for decision-making and risk management. These systems are capable of warning us when their inferences and predictions are no longer useful in the current market environment.
Probabilistic ML is the next generation ML framework and technology for AI-powered financial and investing systems for many reasons. By moving away from flawed statistical methodologies (and a restrictive conventional view of probability as a limiting frequency), you'll move toward an intuitive view of probability as a mathematically rigorous statistical framework that quantifies uncertainty holistically and successfully. This book shows you how.
Deepak Kanungo is an algorithmic derivatives trader, instructor, and CEO of Hedged Capital LLC, an AI-powered proprietary trading company. Since 2019, Deepak has taught tens of thousands of O'Reilly Media subscribers worldwide the concepts, processes, and machine learning technologies for algorithmic trading, investing and finance with Python.
In 2005, long before machine learning was an industry buzzword, Deepak invented a probabilistic machine learning method and software system for managing the risks and returns of project portfolios. It is a unique probabilistic framework that has been cited by IBM and Accenture, among others.
Previously, Deepak was a financial advisor at Morgan Stanley, a Silicon Valley fintech entrepreneur, a director in the Global Planning Department at Mastercard International and a senior analyst with Diamond Technology Partners.
