Parallel Fuzzified Fundamental Analysis for Value Investing

A Statistics Based Algorithmic Approach
Erscheinungsjahr 2027
ISBN: 978-3-032-45999-2
Verlag: Springer

Buch, Englisch, Format (B × H): 168 mm x 240 mm

Reihe: Synthesis Lectures on Technology Management & Entrepreneurship

This book presents a hybrid investment strategy that integrates fundamental and technical analysis through the use of fuzzy systems. Inspired by value-investing principles and F-Score–style multi-signal screening, the framework replaces Piotroski’s binary thresholds with a parallel set of fuzzy logic models embedded with Warren Buffet’s heuristics that evaluate firms across multi-year fundamental snapshots.

Statistical modelling-derived features of key accounting ratios serve as membership function inputs, enabling a graded assessment of financial strength that more closely reflects the reasoning processes of human analysts. Firms classified as fundamentally sound are then monitored under a mean-reversion hypothesis to identify favorable entry points using technical indicators, thereby separating the tasks of selection (fundamentals) and timing (technicals). Empirical results demonstrate consistent outperformance and support the use of fuzzy logic as a transparent and effective mechanism for systematic equity selection.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Huber, David

Neves, Rui

Inhaltsverzeichnis

Chapter 1- Introduction.- Chapter 2- Related Work.- Chapter 3- Architecture.- Chapter 4- Evaluation.- Chapter 5- Conclusion.

Über Autor(innen)

David Huber works in Quantitative Finance at BNP Paribas, where he develops infrastructure for financial analysis, builds analytical models, and supports internal and external clients in the areas of alpha generation and risk management. Prior to joining BNP Paribas, he worked at Nokia, contributing to the deployment, integration, and development of telecommunications systems across 3G, 4G, 5G, and next-generation network technologies.

Mr. Huber holds a master’s degree in computer science and engineering from Instituto Superior Técnico, specializing in artificial intelligence and cybersecurity. He completed two bachelor’s degrees simultaneously, in Computer Science and Engineering and in Logistics and Transportation Management. During his computer science studies, he was recognized as a top-performing student.

Rui Ferreira Neves has been a professor at the Instituto Superior Técnico since 2005. He received Eng -Diploma and PhD degree in electrical and computer engineering from the Instituto Superior Técnico, Technical University of Lisbon, Portugal, in 1993 and 2001, respectively. In 2006 he joined Instituto de Telecomunicações (IT) as a research associate focusing on evolutionary computation and pattern matching applied to the financial markets, sensor networks, embedded systems and mixed signal integrated circuits. He uses both fundamental, technical, and pattern matching indicators to study the evolution of the financial markets. He supervised 60 MSc theses and published more than 60 works including books, book chapters, journal papers and conference papers