My guest today is Bryan Krug, who manages the Artisan Partners Credit Team and overseas more than $3B in high yield credit investments for the firm. This was my first conversation on high yield, so I took it as an opportunity to get an overview on the investment universe and home in on the tools used for analysis and security selection. As an equity investor, I think one of the most fruitful areas of research is into ways that companies fail or go wrong, and credit investors focus almost entirely on this potential for impairment. My guess is that all equity investors will learn something useful from this conversation. Please enjoy.
My guest this week is Maureen Chiquet, the former longtime CEO of Chanel. Maureen also spent much of her career at the Gap, growing Old Navy from scratch, and serving as the president of Banana Republic. The topic of discussion is her experience running large businesses and of finding one’s way in a career and as a leader of others. I hope you enjoy this unique conversation and that it encourages you to, among other things, travel somewhere new and interesting in the coming year.
Modern Monopolies: What It Takes to Dominate the 21st Century Economy, which explores the platform business model (Uber, Airbnb, Github). Alex is also the founder and CEO of Applico, a company that he started in his dorm room that is since grown into a huge enterprise that helps startups and Fortune 500 innovate with platforms. Alex and I talk about history and future of businesses and different types of business models. There’s a lot in here for investors, entrepreneurs, and historians. Please enjoy!
My guest this week is Peter Attia, M.D., whose mission is to understand and improve human lifespan and healthspan (or quality of life). Reading Peter’s research, you find that there are many similarities between health and investing—ideas like compounding—which we explore in detail.
We spend a lot of time on mind, body, spirit and performance as it relates to living a better life. Of particular interest is the strategic problem that we face when studying longevity. As Peter puts it in our conversation: we are the species of interest, but we can’t conduct the kinds of experiments on humans—randomized trials, with control groups—that we apply to solve other big problems. So we have to back our way into a better understanding of longevity and quality of life.
To that end, we discuss what we can learn from studying centenarians, the problem of progress in science, a drug called Rapamycin (which Peter believes could be revolutionary), eating, the importance of muscle mass, and the idea of distressed tolerance. We emerge with a framework for thinking about health and well-being which can hopefully help us all live longer, better lives. Please enjoy!
My guest this week is Saifedean Ammous, author of the book the Bitcoin Standard. This was one of the more interesting conversations I’ve had in the world of cryptocurrency, primarily because we don’t talk about Bitcoin or Crypto until 25 minutes into the talk. Instead, we focus on history, economics, sound money, low time preference, and gold—all interesting topics.
Saif’s thinking on cryptocurrencies other than bitcoin—which is that they are worthless—is unique and thought provoking. His reasoning around why gold shouldn’t be compared to the returns generated by assets like equities was also compelling. If you’ve followed my Hash Power episodes, this is a new a differentiated interpretation of Bitcoin as a technology for the store of value use case. Please enjoy our conversation.
My guest this week is one of my best and oldest friends, Jeremiah Lowin. Jeremiah has had a fascinating career, starting with advanced work in statistics before moving into the risk management field in the hedge fund world. Through his career he has studied data, risk, statistics, and machine learning—the last of which is the topic of our conversation today.
He has now left the world of finance to found a company called Prefect, which is a framework for building data infrastructure. Prefect was inspired by observing frictions between data scientists and data engineers, and solves these problems with a functional API for defining and executing data workflows. These problems, while wonky, are ones I can relate to working in quantitative investing—and others that suffer from them out there will be nodding their heads. In full and fair disclosure, both me and my family are investors in Jeremiah’s business.
You won’t have to worry about that potential conflict of interest in today’s conversation, though, because our focus is on the deployment of machine learning technologies in the realm of investing. What I love about talking to Jeremiah is that he is an optimist and a skeptic. He loves working with new statistical learning technologies, but often thinks they are overhyped or entirely unsuited to the tasks they are being used for. We get into some deep detail on how tests are set up, the importance of data, and how the minimization of error is a guiding light in machine learning and perhaps all of human learning, too. Let’s dive in.