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OverviewThe Agnostic Trader: Exploring the Financial Markets Using Python and Machine Learning introduces a revolutionary mindset for modern traders. In a world where financial markets are unpredictable and fast-moving, rigid strategies based on pre-defined rules are often doomed to fail. The agnostic trader, however, thrives on flexibility, using data-driven insights to constantly adapt and refine trading strategies without being bound by market dogma. This book presents a philosophy where no single model or method is universally effective. Instead, machine learning and Python are employed to create automated systems that respond dynamically to real-world market conditions. By embracing an agnostic approach, traders allow the data itself to guide their decision-making process, letting go of preconceived notions or biases. Whether you are a seasoned professional or new to trading, this guide provides you with the tools to build sophisticated, algorithmic trading systems. Through hands-on tutorials, you'll learn to gather and process financial data, build predictive models, and integrate these models into live trading environments like MetaTrader 5. The emphasis is always on adaptability-ensuring that your strategies evolve with changing markets to maximize success and manage risk effectively. Become an agnostic trader and unlock the power of data-driven flexibility, ensuring long-term success in the complex world of financial markets. Full Product DetailsAuthor: David López OñatePublisher: Independently Published Imprint: Independently Published Dimensions: Width: 21.60cm , Height: 1.50cm , Length: 27.90cm Weight: 0.653kg ISBN: 9798341061965Pages: 280 Publication Date: 03 October 2024 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: Available To Order ![]() We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |