100 books like Chances Are . . .

Talking about money with people, the subject of rich and wealthy often comes up since people may think that’s what true retirement is.

Questions while developing my book came up like what is wealth and how is wealth created? Is there a difference between wealthy and being rich? How can everyday people use understanding wealth in their own personal financial affairs? Do you really need to be wealthy or rich to retire?

To answer these questions, a brief historical context discussed in this book helps us understand the evolution of wealth from how many sheep or other specialized skills you had, to trade from barter or objects, or to wealth derived from the markets such as today. The origin of wealth is knowledge Beinhocker states. 

In trade and today’s markets that knowledge leads to competition which sets prices in all markets that you find in your retirement plan savings.

We… show more.

Personal financial planning has to include investing. With investing comes risk. There are many books on investing. There are few on how to approach investing. Although a short book, it succinctly covers how to think about stock returns, modern financial theory, building a portfolio with risk also in mind, and applying Monte Carlo.

This book combines risk with returns so that you can better target risk to your financial plans. Having a long term, which means the rest of your life, view helps you understand everything has cycles. Using cycles of different investments in a portfolio construct, rather than viewing each investment separately, helps mute cyclical effects on your plans.

I always refer to the fundamentals discussed in this book when I begin to second guess my own plans when markets “misbehave” as they always do. It reaffirms how the application of modern financial theory has worked in the past… show more.

Everyone makes mental shortcuts and also have biases. How can we learn to recognize errors in thinking when it comes to our money? How can we make better choices when it comes to saving or spending? Are we normal or irrational?

Behavioral finance began in the 1970s and I found Statman’s discussion fascinating on almost every page. He sums up these biases when applied to our financial choices as well as to the markets.

Normal people have wants and emotions. This contrasts with many books about how people are irrational. Indeed, we are more normal than irrational once we understand that poor choices are actually normal. Statman describes how to make better choices by recognizing choice and biases we have.

These concepts are important if you want to grow your wealth without making someone else wealthy through your spending habits.

This is a wonderful book organized around four main concepts, each valuable in their own right: 1) The Theory of Investing; 2) The History of Investing; 3) The Psychology of Investing; and 3) The Business of Investing. 

The latter, the business section makes it clear the stockbroker is not your friend, even though they’re friendly (by design). Having started my career on the sales side of the business, I quickly learned the agenda is less about the customer and more about product sales, even though I was also a Certified Financial Planner ProfessionalTM. 

I dropped sales licenses and became a fee-only advisor and member of the National Association of Personal Financial Advisors (NAPFA) where the focus is on planning and helping clients achieve their wants and goals.

The principles in Bernstein’s book marry well with those of both Swedroe’s and Statman’s books (above) in the application of growing… show more.

Everyone knows what probability is, and we all understand how a coin flip works, but not everyone can explain the optimal betting strategies for a roulette table. We don’t study probability to understand the likelihood of events. We study probability to understand the expected outcomes of business processes that depend on those events.

In other words, this book won’t just teach you about probabilities, it will teach you about business strategies associated with those probabilities. It will help you answer a question like: How do I maximize the profit on this life insurance policy, given this set of survival probabilities? It isn’t just a likelihood question, it is a business question. I highly recommend that anyone studying probability does so through an actuarial lens.

I found a copy of this book in the sixties. That copy, much loved, was lost in moves and mayhem. Now, I only have a Dover reprint (water-logged during yet another move), but I have never been without and would search high and low if I were.

This is also a history of probability but with a very different focus. Ms. David was a statistician able to explain the calculations intuitively (good to assign to my students). But she was also thoroughly interested in the personalities involved. What was Galileo like? What happened to Pascal at Port-Royal?

I felt personally drawn into the historical narrative that often reads like a novel. 

This is a more comprehensive and mathematically rigorous book than Pierce’s book. For the novice, it should be read-only after first reading Pierce’s more informal text. Due to its vintage, the layout is fairly cramped, but the content is impeccable. At almost 500 pages, it covers a huge amount of material. This was my main reference book on information theory for many years, but it now sits alongside more recent texts, like MacKay’s book (see below). It is also published by Dover, so it is reasonably priced.

My knees tremble and my heart quakes when I think of how much work must have gone into these two companion volumes. Collectively, they are more than four times the length of my book, covering the whole of machine learning.

It is an essential encyclopedic resource that should be on the desk of anyone serious about machine learning.

Sadly, Games, Gods, and Gambling by FN David is out of print. This is the next best thing. Lorraine Daston has the supreme gift of making the complicated idea seem straightforward. This is an account of the frenzy for measuring that happened in the 18th century, and how it made the world we live in today, when the gambler’s eye for odds has become the algorithm of taming chance that guides all our decisions.

In the ongoing debates over artificial general intelligence (AGI), Judea Pearl is taking a firm stand: He argues that an intelligent robot should be able to reason about causality and that the currently fashionable approaches to AI miss this aspect.

A celebrated AI researcher and a Turing Prize laureate, Pearl has developed an amazingly original approach to this problem. This book is a high-end popular exposition of his approach.

But it’s so much more than that. It’s a history of statistics and its conflicted attitude to causality. It’s a story of heroes (or villains?) in this history. And it’s a scientific autobiography that describes Pearl’s journey. Pearl likes picking fights with the AI community, statisticians, or economists. He’s boastful, provocative, extremely intelligent, and knows how to tell a story.