Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

Whether based on academic theories or discovered empirically by humans and machines, 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.

Unlike conventional AI systems, probabilistic machine learning (ML) systems treat errors and uncertainties as features, not bugs. They quantify uncertainty generated from inexact model inputs and outputs as probability distributions, not point estimates. Most importantly, these systems are capable of forewarning us when their inferences and predictions are no longer useful in the current market environment. These ML systems provide realistic support for financial decision-making and risk management in the face of uncertainty and incomplete information.

Probabilistic ML is the next generation ML framework and technology for AI-powered financial and investing systems for many reasons. They are generative ensembles that learn continually from small and noisy financial datasets while seamlessly enabling probabilistic inference, prediction and counterfactual reasoning. By moving away from flawed statistical methodologies (and a restrictive conventional view of probability as a limiting frequency), you can embrace an intuitive view of probability as logic within an axiomatic statistical framework that comprehensively and successfully quantifies uncertainty. This book shows you why and how to make that transition.

無論是基於學術理論還是由人類和機器實證發現的，所有金融模型都受到建模誤差的影響，這些誤差可以減輕但無法消除。概率機器學習技術基於對概率的簡單直觀定義和概率理論的嚴謹計算。與傳統的人工智能系統不同，概率機器學習系統將錯誤和不確定性視為特徵而非錯誤。它們將由不精確的模型輸入和輸出產生的不確定性量化為概率分布，而非點估計。最重要的是，這些系統能夠在當前市場環境中的推論和預測不再有用時提前警告我們。這些機器學習系統在面對不確定性和不完整信息時，為金融決策和風險管理提供現實支持。概率機器學習是下一代人工智能金融和投資系統的框架和技術，原因有很多。它們是生成式集成模型，能夠從小而嘈雜的金融數據集中持續學習，同時無縫地實現概率推斷、預測和反事實推理。通過擺脫有缺陷的統計方法（以及對概率的限制頻率觀點），您可以接受對概率的直觀觀點，將其視為在公理統計框架內的邏輯，全面且成功地量化不確定性。本書將向您展示為什麼以及如何進行這種轉變。