Truth Engine

Applying AI to Investing

Non-Fiction - Business/Finance
243 Pages
Reviewed on 12/01/2023
Buy on Amazon

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    Book Review

Reviewed by Asher Syed for Readers' Favorite

Dr. Leonidas Tam's book Truth Engine: Applying AI to Investing is a weighty text on how artificial intelligence could possibly be included in the world of finance. Tam takes a good hard look at mathematical and computational approaches, driving home artificial intelligence and machine learning's full, or nearly so, impact. Over the course of eleven distinct and interconnected sections and dozens of chapters, the book reviews core concepts like data-driven market analysis, risk management, and investing in strong companies. It considers portfolio optimization and the difficulties in this sector while considering AI, generative modeling, and how they're utilized in finance. It also takes into account value investing's future, raising ethical questions in the context of the changing AI-driven financial sector.

Dr. Leonidas Tam offers a thorough, forward-looking point of view on the potential benefits and moral dilemmas associated with combining AI with investing, which is most likely to shape the financial industry's future, whether we as individuals accept it or not. Change is coming, and Truth Engine shows us with crystal clarity what that change will probably look like. I'm a civil servant and economist who sees the benefit of AI, but even as a reader who does not know much about the investing side of finance, I thought that Tam's style of writing was comfortable. I see daily a staggering amount of mistakes that are basic human error so I liked that the book analyzes the relationship between AI algorithms and human decision-making. For instance, Tam points to disparity reversal, a phenomenon where omitting group information can lead to more equitable outcomes without sacrificing predictive accuracy in challenging conventional wisdom in predictive models. Insightful and educational in equal parts, and a job well done by Tam.

Jamie Michele

Dr. Leonidas Tam's Truth Engine: Applying AI to Investing is a comprehensive look at AI's integration into finance and, in many ways, at AI's impact on pretty much everything. Dr. Tam begins with a breakdown of Renaissance Technologies' strategies, comparing traditional and adaptive investing. Dr. Tam details difficulties in areas such as bias resistance and intellectual flexibility in investment approaches. Linking AI, investing, and Gödel's Incompleteness Theorem, he questions established models. His analysis moves to high-frequency trading and Bayesian reasoning, where he advocates for diverse information sources and balanced risk. Dr. Tam also marries neuroscience concepts and portfolio optimization, aligning with precision-focused philosophies. He homes in on ensemble strategies, hybrid human-machine decision-making, and the potential of generative AI in financial analysis, wrapping up all this and so much more by advocating for open-source platforms, aligning AI-driven stewardship with long-term value investing, and ethical considerations in AI development.

As someone who worked for years in international finance as a securities broker and, more importantly, as someone who worked before the explosion of technology relegated the beloved stock certificate to antiquity, I was drawn to Truth Engine by Dr. Leonidas Tam, and I learned a heck of a lot. Of course, investing goes far beyond securities trading, and so too does Dr. Tam, who writes his book with the authority and language of a true academic, but with plenty of stories and relatable examples to make the work accessible. In what just might be a fantastic first in a finance book, Dr. Tam uses the Steven Spielberg movie AI as a 'life imitating art' example, stating that “the emphasis of alignment to produce emergent phenomenon in RL has made fiction closer to fact.” He also includes graphs and figures that shore up his explanations effectively. I appreciate that Dr. Tam covers enough of the basics for a lay reader to understand without simplifying it so much that it is patronizing to those with a firm foundational grasp. Frankly, I think Truth Engine should be required reading in this new age of AI, particularly in its application to investing, and I have no doubt others who pick it up will agree. Very highly recommended.

K.C. Finn

Truth Engine: Applying AI to Investing is a work of non-fiction in the business and finance, technology, and guidance subgenres. Penned by author Dr. Leonidas Tam, the work is best suited to the general adult reading audience. The author offers readers the definitive guide to unlocking the future of finance by integrating machine learning into investing. Following the wisdom of Charlie Munger, the book provides multifaceted mental models to decode market complexities. It equips readers with machine learning principles, advanced tools like generative AI, and insights into data's nuanced role in models.

Author Leonidas Tam has crafted an interesting guidebook that successfully demystifies the application of AI in investing, making complex concepts accessible and engaging readers in a whole new world of possibilities. The integration of different perspectives, viewpoints, and mental models is handled well, emphasizing the importance of multifaceted thinking in navigating financial markets. The book is also organized, clearly labeled, and easy to refer back to whilst it adeptly covers systems design, portfolio optimization, and performance evaluation, providing a comprehensive understanding of AI's role in investing. What sets the work apart from others is the fact that Dr. Tam not only discusses crunching numbers but also emphasizes the significance of equipping oneself for the next evolution in the field and learning to adapt to constant progress and change. Overall, I would not hesitate to recommend Truth Engine as a valuable and well-penned resource for those seeking to redefine the boundaries of comprehensive investing in the era of AI.

Samantha Dewitt (Rivera)

AI is everywhere and it’s only going to continue to expand into different realms, including investing. But it doesn’t have to be as daunting as you might think. Leonidas Tam has created your guide to navigating the field for yourself, so you can take advantage of the steps that have already been put into place. Portfolio management, different fund structures, model ensembling, and more are all discussed here. You’ll also learn about the benefits and drawbacks of AI (like the truth about bias and the ‘human element’ when it comes to investing). Investing is complex, and this book isn’t going to be something you read through quickly. You’ll want to read through it and then check back often to review different parts and get even more advice because Truth Engine: Applying AI to Investing is the kind of book that you can’t possibly fully appreciate with just one read.

Graphs and charts throughout Truth Engine: Applying AI to Investing highlight some of the standard rules of investing and help you get a little more background on what’s going on in the technology realm in general and in AI more specifically. This is a high-level book that gives you a great deal of in-depth information to use in learning about AI and applying it to your own processes. It’s clear that Leonidas Tam did extensive research into the topic, including gathering insight and information from some of the most well-known investors of our time. You’ll also find interesting anecdotes and stories scattered throughout and firsthand information and experience from the author.

Courtnee Turner Hoyle

In Truth Engine: Applying AI to Investing, deep learning and artificial intelligence specialist Dr. Leonidas Tam presents the application of machine learning in the financial market, covering data gathering, financial risk assessment, decision-making, and portfolio management. With references to literature, history, and philosophy, the author conveys the importance of applying machine learning to investment opportunities. Tam covers biased judgments and the ways they may impact financial decisions, touches on environmental safety in business, and strengthens a reader's comprehension of financial markets. By clearly explaining the concepts of artificial intelligence, Tam illustrates the way machine learning and human thinking can work together to decode market complexities.

Dr. Leonidas Tam offers a guide for navigating the next phase of financial investing while paying careful attention to the role of artificial intelligence. Using the wisdom of Charlie Munger and examples involving Warren Buffett, Tam shows his readers how to leverage innovative technology for input in financial decisions. It's best to have some underlying knowledge of the subject matter as the book is written in a technical format, but the text provides insights that will aid the starting or seasoned investor's research. Readers can rely on Tam's assessments due to his years of successful experience and degrees from Brown and Yale. The clear and concise charts and graphs help clarify the data for better investment analysis. Truth Engine: Applying AI to Investing is a great resource for readers who hope to learn about the future of finance and investing as it is reshaped by advancements in artificial intelligence.