About this item
Highlights
- 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.
- About the Author: EOGHAN LEAHY is the Founder and CEO of Quant Market Intelligence Limited, an AI-powered trading and research company.
- 176 Pages
- Business + Money Management, Personal Finance
Description
Book Synopsis
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.
From the Back Cover
USE THE POWER OF ARTIFICIAL INTELLIGENCE TO OPTIMIZE YOUR TRADING FOR PEAK PERFORMANCE
AI-Powered Bitcoin Trading: Developing an Investment Strategy with Artificial Intelligence by Eoghan Leahy offers a groundbreaking exploration into the use of AI for optimizing trading strategies. Leahy guides readers through the intricacies of Bitcoin, providing essential background on its creation and valuation, and delves into both traditional and advanced trading methods. With a focus on actionable insights, this book teaches you how to harness big data and AI to generate trading signals, back-test and optimize strategies. Distributed Genetic Algorithms are also introduced as a method to enhance investment returns. A comprehensive case study based on the Bitcoin AlphaBot(TM) trading system shows how a fully automated, AI-driven trend-following strategy can be developed and evaluated. This insightful guide is invaluable for anyone looking to improve their trading using artificial intelligence.
PRAISE FOR AI-POWERED BITCOIN TRADING
"An easy-to-understand, concise explanation of the workings behind Bitcoin and how to value it as a financial asset. Bitcoin AlphaBot's performance has been impressive too."
--Tom Pelc, Founder, Pelc Enterprises Ltd, Chief Investment Officer, Fortu Wealth
"Eoghan explains the foundational elements of trading strategies in clear terms. The application of artificial intelligence for parameter optimization is very insightful, and equally accessible."
--Tyler Wood, CMT, Managing Director, CMT Association, Co-Founder, GoNoGo Charts
About the Author
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.