Reading List

I’m often asked what to read to understand topic X ∈ {'Quant', 'Wine'}. So often, in fact, that it inspired this section on my website. Odds are you're here because I pointed you here, and now that you are here, there are some disclaimers. These lists are far from exhaustive. Reading them won’t make you an expert or give you a complete view of the topic. They’re just a guide from someone who’s taken a unique path through these subjects. My recommendations are based purely on my own experiences and how much I personally got out of these readings. My background is in asset pricing. In industry, I worked in quantitative equities and asset allocation, focusing on alpha research. This is the 'new guard' of quants, very different from the 'old guard' in sell-side and derivatives pricing. So, my recommendations are specifically for those who want to dive into the 'new guard'.

1. The Fama Portfolio - Background reading; This is holy text, as far as I'm concerned. It provides the background on some of the most seminal work in empirical asset pricing. While no specific paper or review in this book will hand you tangible tools, the history of the subject is, in my opinion, essential reading. Sure, plenty of quants have gone on to be successful without reading this book, but well-read quants are more than just regression monkeys—they’re conscientious.
2. Active Portfolio Management - Tool book; I don't think I've met many quants who didn't read this at some point. This book is equivalent to what Investment Banking is to buy-side fundamental people.
3. Advances in Active Portfolio Management - Tool book; The keen reader might have noticed that the previous recommendation is a bit dated. Yes, there have been many advances in the field since 1994, but as I mentioned with The Fama Portfolio, having a solid background and starting from the basics is crucial to becoming a well-read quant. This book offers an update, using papers to help the reader grasp the innovations of the past 20 years.‍
4. Risk and Asset Allocation - Tool book; The previous two books in my opinion do not have enough material on optimization. As such, this book provides a good background on defining risk, estimating it, and using it in an optimization setting.

I love wine! Drinking, making, and learning about it consume a decent amount of my freetime. I have absolutely no formal education in wine production, tasting, or commerce. I am purely self taught through the following collection of materials. Once again, take these recommendations with a huge grain of salt.

1. Wine Folly - This is a beginners book about various wine varietals. Although it is very elementary, I still use it to this day to look-up and compare my tasting notes to what is thought of as canonical for a certain variety. The book is fun to have as a reference material.
2. Wine Gapes: A complete guide - Imagine Wine Folly but much much much more breadth and depth at the expense of readability and usefulness. For the extreme nerds out there, this book is worth it just for those occasions where you find {insert rare varietal here} at the store and wonder "Mhmm, does the book have this?". The answer is yes, yes it does. Buy the wine and find the page for a fun night.
3. Inside Bordeaux - If I was a professor teaching a class about Bordeaux, this would be the reference material. Unbelievable depth of information for my favourite region.
4. Bordeaux Legends - I might be beating a dead horse at this point, but I really like Bordeaux. Although most of the first growths are - ridiculously - expensive, they represent more than just wine. This book shows the history and exactly what you get for your - ridiculously - expensive bottle.
5. If you want non book based references, any video from WineKing, and Konstantin Baum is fantastic.

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Why We Choose to Study Economics

No person can fully grasp how far and how fast economic thought has traveled, but condense, if you will, the 50,000 years of human economic activity into a time span of but a half-century.

Stated in these terms, for the first 40 years, we know very little—except that at the end of them, man had learned to barter one thing for another. Then about 10 years ago, we invented money and discovered we could store value in metal coins. Only 5 years ago did we establish the first banks and learn that trust could be an asset.

The joint-stock company—less than 18 months ago. Adam Smith wrote The Wealth of Nations and gave us the invisible hand just last year. The Industrial Revolution—which transformed everything—came last summer.

Marx wrote Das Kapital last fall. The Federal Reserve was created last spring. Keynes published his General Theory and revolutionized our understanding just 8 months ago. Bretton Woods and the modern international monetary system—6 months ago.

Credit cards arrived 3 months ago. We floated our currencies off the gold standard 10 weeks ago. The first derivatives appeared 5 weeks ago. The internet enabled digital commerce just last month. The 2008 financial crisis happened two weeks ago last Tuesday.

Bitcoin was invented 10 days ago. And this morning, as we woke, artificial intelligence began trading securities faster than human thought.

This is a breathtaking pace, a pace that makes us dizzy. And now we stand at a crossroads, asking not whether our economy can grow, but whether our wisdom can match our innovation—whether we can understand these forces—whether we can master them.
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We choose to study economics, not because it is easy but because it is hard.

- Made by Claude Sonnet 4.5 when asked to roleplay JFK being asked why study economics during a speech at Rice.

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Videos I like

Rational Reminder #200 Prof. Eugene Fama

‍Quotes I Like

• “We have to forgo some mental tortures to deal with it, but I will accept it and see what happens.” - Gerolamo Cardano when he invented/discovered complex numbers in his “Ars Magna” “The great art of algebra”
  • I'm not entirely sure why, but this quote constantly resurfaces in my mind when I'm doing theoretical work. When I'm solving a problem and approaching a breakthrough, I often feel the most lost and confused. I've learned to embrace this feeling of being 'lost' and to keep progressing regardless, just to see what happens.
• "I’d compare stock pickers to astrologers, but I don’t want to bad-mouth the astrologers" - Eugene Fama
  • Although markets are likely not efficient, they are undeniably difficult to beat. Given this challenge, I find it puzzling why industry professionals often exude such confidence in their work. While comparing them to astrologers is amusing, there is a kernel of truth in the analogy. Astrologers, often seen as salespeople, use leading questions and a sharp eye to 'research' their clients, ultimately saying things that are otherwise meaningless. While the comparison may be extreme, and the industry does engage in meaningful work, asset managers also need to be astute researchers of their clients. In my view, a marginal unit of effort spent on sales yields far greater returns in the industry than in 'alpha' research.
• “There is no such thing as Alpha, only the Beta you don’t know about.” - John Cochrane
  • The citation here is not very precise. I have no idea when, where, or how he said this, or even if he did. I've heard many people attribute this quote to him. Regardless, this idea has always stood out and compelled me to think deeply about asset pricing. It has, without a doubt, influenced my own interest and research in asset pricing.
• "Buybacks are divisive. They divide people who understand finance from those that don't." - Ken French
  • I don't care for the topic as much as I care about the delivery. An eloquent shutdown. I can think of many topics which can replace the first word of the quote, can you? 
• "The past appears to be a predictably unpredictable predictor of the future" - Benjamin
• "Your Grandmother Is Wrong" - Jonathan Berk, Money Management in Equilibrium 2019
• "I saw the plot first, ..., and the first thing I thought was; programming error." - Richard Roll when making Figure 2 of Fama, Fisher, Jensen, and Roll (1969)
  
  • This is the first thought an empiricist should have when examining their results. Especially when they are as beautiful and clear as FFJR (1969).

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Technology

• Server: Apple Mac Studio, M3 Ultra, 500GB unified memory
  
  • Working with LLMs is hard. It is even harder when you want to work with larger models. This machine allows me to quickly (and cheaply) test new ideas. I would not reccomend it for many people but it has been a game changer for my research.
• Computer: Apple Macbook Pro, M2, 16-inch
  • My first Mac and it is my baby. I never thought of using/buying a mac, but with the recent chip and integration with the rest of the Apple Ecosystem: this thing is awesome.
• Tablet: Apple iPad Pro M2
  • I used to be pretty 'old school' when doing math: pen, paper, and a massive binder. It was only until I started doing research where this system irritated me into changing. Being able to search handwritten documents is a theorist's life hack.
• Source Control: Azure Devops (private repo)
  • Yes, Devops is complicated and has a high learning curve, but the ability to integrate into VMs and blob storage is unbeatable. The project management abilities of Devops also help with building big research infrastructure for big data, or complicated methods.
• Source Control: GitHub (public repo)
  
  • I do not like GitHub, but it is the easiest way to share code with others.
• IDE: Pycharm
  • It has a bunch of features which makes coding faster. I have encountered several circumstances where Pycharm becomes schizophrenic and requires re-setting but - so far - the functionality is worth more than this nuisance.

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