Adrian Colehart

The Algorithmic Edge (eBook, ePUB)

Outsmarting the Market with AI and Data

• Format: ePub

Produktbeschreibung

Most retail investors still believe algorithmic trading is reserved for Wall Street elites with armies of coders and complex math degrees. In reality, the same tools that once gave hedge funds an unbeatable edge are now available to anyone-if you know how to use them without drowning in technical jargon. This book shows how to turn AI investing strategies and data-driven portfolio management into a simple, disciplined process you can actually follow.

It strips away the hype and replaces it with clear, rule-based investing systems you can test, measure, and refine-no coding required. You'll discover how to separate real signals from noise, when to trust machine-generated insights over your own instincts, and how to design a strategy that can protect you from the two biggest portfolio killers: bias and overconfidence.

Inside, you'll learn how to:

-Apply quantitative investing principles without becoming a statistician

-Use backtesting for stock trading to validate your ideas before risking capital

-Build risk management algorithms that keep losses small and gains steady

-Choose affordable, reputable AI trading tools and avoid predatory platforms

-Blend behavioral finance insights with automation for the best of both worlds

Whether you're a curious beginner or an experienced DIY investor, this is your blueprint for navigating markets with confidence. By the final chapter, you'll have a framework for making decisions that are faster, smarter, and less emotional-turning technology into your strategic partner instead of your blind gamble. The markets will always be unpredictable, but your process doesn't have to be.

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Produktdetails

• Verlag: Mindful Pages
• Seitenzahl: 292
• Erscheinungstermin: 21. November 2025
• Englisch
• ISBN-13: 9789371771825
• Artikelnr.: 75913615

Autorenporträt

Adrian Colehart writes at the intersection of markets, data, and everyday decision-making. A long-time observer of how retail investors actually behave, Adrian focuses on turning complex, quant-driven ideas into clear, usable rules that ordinary people can apply with confidence. His work emphasizes a practical creed-test small, measure honestly, iterate deliberately-while rejecting hype and guru theatrics. He has collaborated with fintech teams and independent traders, studied the psychology of risk-taking, and built simple rule-sets for personal portfolios that privilege discipline over prediction. Adrian believes the future of investing isn't about replacing judgment with machines, but about designing workflows where algorithms check our biases and accelerate the boring parts, so our attention is free for context and choices that truly matter.