Raison D’Etre

In my prior life at Epic Systems, now a healthcare software goliath, I spent the majority of my time hyper-focused on how to keep customers happy on our outpatient pharmacy product. My core mandate was long-term customer support, but this meant different things on different days: walking customers through an upcoming upgrade, diving deep into the code to pinpoint the root cause of a patient safety issue, developing complex code for a future release, and critiquing developers’ upcoming designs could comprise a single day. In retrospect, what made the role so unique was that 95% of time and energy was spent on the customer; rarely did I think about sales, revenue, hitting KPIs, industry trends, or third-party relationships. The only focus was customer happiness, by whatever means necessary.

The past two years have reaffirmed my decision to leave Epic after 8 great years. Even though few days were boring and I really felt the patient-focused mission, I had a nagging feeling that growth at the company was an inward growth, that “new opportunities” at the company would build my internal expertise, doubling down on my Epic specialization. I’d felt that if I had stayed another five years, my work would be largely the same. Ten years later, would I regret not trying something new and challenging?

Seldom is the career risk not worth taking; I’ve enjoyed the opportunity to explore the endless number of careers paths. While still in Wisconsin, I finished up a Master’s of Computer Science just as ChatGPT was coming out, an exciting time to be studying machine learning. I’d never felt at home as a full-time software developer, though, so when I came to business school, I endeavored to continue to explore the standard paths (i.e. management consulting, investment banking, tech product management) to the less-trodden paths (e.g. general management, investment management, PE/VC, entrepreneurship through acquisition).

In hindsight, the way I gauged various career paths is: did the skills, expertise, and values of tenured employees match what I wanted? What future version of myself would I be willing to work hard for right now? What stuck out most was a career in investments, which at its best, seems like a mix of art and science, intellect and relationships, statistics and history. It’s an industry where every piece of news and history seems to be relevant.

I’ve spent the past couple years learning the foundations of investing; two years ago, I hadn’t heard of the “time value of money” or the concept of private equity. My goal for this blog is to take the leap from passive learning to actively synthesizing information about the wider investing universe. I’m certain that I’ll get some things wrong, but I’m hopeful that this will serve as (a) a form of accountability to myself and (b) a ledger-like record of my current thoughts. I hope it will help me straighten out the vast landscape of financial markets and, at some point, have a clear and interesting voice in the discussion.

A few things I’m hoping to dig into:

Technical (i.e. coding) analysis of markets. At Epic, I prided myself on being able to write code quickly to prove or disprove an idea; translating idea to code felt as easy as “breathing out” code. Unfortunately, Epic used a bespoke language (MUMPS) with a proprietary library, and so I’ve felt the pain of having to learn a new language (Python). The best solution: repetition, practice, and personal projects. In a past life, I built my reputation on understanding technical details better than anyone (and being able to translate into customer-consumable content). Being able to effortlessly produce quantitative evidence will be invaluable to my long-term edge as an investor.

Some projects here include:

• Collecting market data. At Epic, all of the data was centrally stored and easy to access – not the case in the real world! I’ve found I need to learn not only where to find financial data but which to trust, as well as how to access it via code.
• Testing market ideas. My hope is to be able to quickly and easily test market ideas, be it company vs. macroeconomic correlations, backtesting investment ideas, or screening public companies.
• Running cross-sectional regressions. After taking a course on quantitative investing, I’ve learned that the gold-standard in (academic) factor testing is cross-sectional regression. I’d love to be able to quickly test market factor ideas and recreate interesting paper ideas (such as Verdad Cap’s recent poor man’s pod shop replication idea).

Investment ideas, company valuations, and industry trends. I also hope to practice (a) thesis building and (b) fundamental valuations of public companies, especially for companies that I might want to invest in. My hope: have a paper trail of my own investment ideas and theses, so that I can see where I went right/wrong later.  

One thing I’ve been interested in lately is how/if investments in speculative industries can successfully be a part of an investment strategy. It’s not a novel strategy in the least; I’m reading Devil Takes the Hindmost and Bill Janeway’s Doing Capitalism in the Innovation Economy, which both touch on the historic hype/bust cycles of bubble markets (referred to as the “innovation economy” by Bill Janeway). But there have been a slew of public stocks that have “rocket-shipped” in the past couple months, including bitcoin and quantum. Are these performing well because of social media buzz (e.g. Reddit, Robinhood), market catalysts (e.g. Trump’s election), fundamental/structural changes in the internet economy, or something else? Could you construct a VC-like public equity portfolio (i.e. one or two big winners in 10 stocks) to capture these ultra-short-term momentum stocks? How would you hedge away risk (maybe hedge against an unexpected market dip with the VIX)?

Random finance news, history, and questions (especially from an asset allocator perspective). It’s fascinating how finance, like most industries, has been cobbled together into its current state through a series of scandals, accidents, and course corrections.

• One topic I’m particularly interested now is index investing. Modern wisdom for personal investors is to index everything (see: Buffett), but most large allocators have a large active portfolio. At what point (or under what conditions) does active management add value?
• If index investing is increasing, how does that impact price discovery? Does an increase in index investing buffer against price fluctuations or act as a catalyst for more volatility?
• There is a laundry list of other similar other finance and finance-adjacent topics, including: Ireland and its tax impact, quantitative understanding of risk, which types of companies go public (and what macro factors drives big IPO years).