Hi I have recently read 'Trading Systems and Methods' by Perry Kaufman and 'Systematic Trading' by Robert Carver. Those were valuable books. Can anyone suggest other valuable systematic and algorithmic trading books? Thanks
"Algorithmic Trading: Winning Strategies and Their Rationale" written by Ernie Chan, is a fantastic book by Ernie Chan, this one focuses on creating successful algorithmic trading techniques. Chan investigates a variety of quantitative trading techniques, including statistical arbitrage, momentum trading, and mean reversion strategies. He explains the rationale behind each plan and offers practical guidance on implementation and risk management.
Neural Network: Mastering the Art of Algorithmic Trading--Building Algorithmic Trading Strategies with Deep Learning in Python (2024) https://www.goodreads.com/book/show...arch=true&from_srp=true&qid=roCvkDUGRB&rank=2 Dive into the cutting-edge world of finance with our latest release, "Neural Mastering the Art of Algorithmic Trading." This groundbreaking book is your key to unlocking the full potential of neural networks in the fast-paced universe of algorithmic trading. Whether you’re a finance professional looking to sharpen your edge, a tech enthusiast eager to explore the intersection of AI and trading, or someone fascinated by the future of financial markets, this book is crafted especially for you. Why this book? "Neural Mastering the Art of Algorithmic Trading" stands out as a beacon for those seeking to navigate the complexities of using artificial intelligence in the financial sector. Written with the precision of an expert and the clarity of a seasoned educator, this book demystifies the science behind neural networks and offers a comprehensive guide to implementing them in your trading strategies. It's not just a book; it's a journey into the future of trading, where technology and market savvy meet. Grasp the essentials of neural networks, making even the most complex concepts accessible. Step-by-Step Follow detailed instructions on building your own neural network models tailored for algorithmic trading, ensuring you not only understand the theory but can also put it into practice.Real-World Learn through practical examples and real-world scenarios that illustrate how neural networks can be used to predict market movements, manage risks, and optimize trading strategies.Cutting-Edge Stay ahead of the curve with insights into the latest advancements and trends in AI and financial trading. Your Bridge to With its blend of theoretical depth and practical insights, "Neural Mastering the Art of Algorithmic Trading" is more than a book—it's your bridge to a successful future in algorithmic trading. It empowers you to blend the precision of AI with your market intuition, opening up new strategies that were once thought impossible.
In addition to the 2 books you pointed out, in these books there are complete codes in Easylanguage of various Trading Systems and they also teach how to create, optimize and test Trading Systems: - The Ultimate Trading Guide (John R. Hill, George Pruitt, Lundy Hill) - Trading Systems that Work (Thomas Stridsman) - Building Winning Trading Systems with TradeStation (1st and 2nd edition) - (George Pruitt, John R. Hill) - Cybernetic Analysis for Stocks and Futures (John Ehlers) - Trading Systems - A New Approach To System Development (Urban Jaekle and Emilio Tomasini) - Trend Following Systems (George Pruitt) - Trading Systems, Secrets of the Masters (Joe Krutsinger) - Rocket Science for Traders (John Ehlers) - Beating the Financial Futures Market (Art Collins) - Design, Testing, and Optimization of Trading Systems (Robert Pardo)
To me, it sounds like a book that is capitalizing on the fact everyone has heard about neural networks now. I am deep into Douglas Hofstadter's Surfaces and Essences: Analogy as the Fuel and Fire of Thinking and I think the issue is you can't think about trading systems and machine learning by analogy. It is its own thing. I looked into trying to build a macro model that would use hotel data APIs to extract the change in room pricing and then use that as a feature to a ML model. The problem for me as a single person is the data is too expensive and too time consuming to consume. Then imagine having 100 other of these type of non-market data, data sources plus all the actual market data sources. Now you are in the domain of comparing the effectiveness of a deep learning algorithm vs a random forest or whatever other ML algorithm you like. If you just have a few features derived from a single price series, it is complete nonsense to be talking about neural networks. It is a type of category error that is hard to explain since it can't be approached through analogy. The closest I can think of is a book title "The saw: mastering the art of building a house". As if to build a house you only cut wood. That is still a terrible analogy. This book is just standard LTSM time series models that don't really work in finance. It that regard, it is really hard to beat Facebook Prophet for time series. A non-ML model,written in the Stan programming language.