Know When to Hodl, Know When to Fodl: How to Trade Bitcoin Like a Pro
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Survive and thrive amongst the professional traders using sophisticated cryptocurrency analysis and trading techniques
The purpose of this book is to provide a concise yet comprehensive background of some effective methods for analyzing markets and creating fully automated AI-optimized trading systems.
The book outlines some easy-to-replicate yet highly effective quant trading techniques that can be used for analyzing asset prices and then apply them to Bitcoin prices, showing how to generate actionable insights from data that can be used to create fully automated trading signals and systems.
Big data analytics can be enhanced with artificial intelligence techniques. Back testing and optimization methods are presented with a special emphasis placed on the use of distributed genetic algorithms for parameter optimization.
Finally, a case study of a fully automated trend-following trading strategy that leverages artificial intelligence is presented. Bitcoin AlphaBot(TM) combines human insight with AI-driven optimization to build profit table trend trading strategies.
EOGHAN LEAHY is the Founder and CEO of Quant Market Intelligence Limited, an AI-powered trading and research company. Previously working as the quant strategy and cryptocurrency product specialist at Bloomberg LP, he has helped hedge funds, sovereign wealth funds, and treasury departments back-test and automate trading strategies. Leahy helped Bloomberg become the top-rated platform for data visualization and technical analysis. He created and edited a popular Bloomberg publication, "The Quarterly - Global Cross Asset Overview" which won several industry awards. In 2016 he delivered the first series of cryptocurrency seminars in the EMEA region for Bloomberg clients. He also collaborated internally on the early phases of BloombergGPT. He holds a BASc in economics from University College Dublin, a master's degree in international business from the UCD Smurfit Business School, and an MSc in High Performance Computing from Trinity College Dublin.
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