The best investors bring an informed approach with a sprinkling of street savvy. No one entrusted with the world’s largest asset allocation decisions relies solely on quantitative analysis. Numbers matter, but so does human judgment. The key lies in finding a balance.

My path to Wall Street was accidental and unlikely. I grew up in rural West Virginia but missed school regularly for travel with my father’s work as a scientist. Asked in third grade to discuss Indian reservations, I drew a jetliner and wrote that reservations in India were difficult to get. I may have misunderstood the request but had already experienced a 24-hour taxi ride through a desert sandstorm when planes were unavailable.

Having caught the international bug early, I studied developing countries at West Virginia University, spending a year at Banaras Hindu University in India and another as a research assistant with Yale University in a Thai rainforest examining Asian honeybees. I had not the slightest thought of working in finance, although total immersion in social insect data collection best practices became unique preparation for a quantitative Wall Street career.

In the meantime, I acquired oral and written fluency in Japanese studying the language and working in Tokyo for two years after college, followed by a JD from the University of Washington. I sought to practice Asia-related trade and transactional law through my contacts and skills but timed it poorly, as Japan’s markets had fallen. Resolutely uninterested in practicing immigration law with my languages, I explored other fields and chose Wall Street.

The high-intensity sales atmosphere of Bear Stearns, my first employer, was more foreign in some respects than what I had experienced abroad. There was much to take in. What motivated someone earning $6 million per year to fling her pen in rage at an intern she had barely met? Or (different person) berate a customer for not appreciating that he had extended the courtesy of calling on an investment idea while standing atop his 40th floor desk overlooking the Golden Gate Bridge? What motivated any thinking in this environment? Were their investments more considered than their personal interactions?

My early career included a year at Hambrecht & Quist before settling into a longer stay with Smith Barney Citigroup (later merged into Morgan Stanley). This early exposure to three leading yet dissimilar firms was important because I could observe a consistently entrenched mindset that ‘we’ hired Wall Street’s best analysts, a logical impossibility. Curious to know more, I was surprised to find extensive data in the public domain. Fortunately, it went unnoticed until well after I had launched a career, but the data bore similarities to my experiences with honeybees: messy with outliers, but usable. It just required work, and a willingness to learn math and programming. I established a team which built processes for running 50,000 Monte Carlo simulations on each analyst, and we discovered that only 2% had a 75% chance or better of being ‘above average’ with only 1% having 90% odds. These elites worked across the industry, mostly migrated toward smaller firms over time, and tended to receive lower recognition and pay unless departing for hedge funds. Building this knowledge from scratch was my first exposure to the power of quantitative finance. Equally important since then has been a disciplined commitment to investigate constantly and push boundaries.

Continuing on the topic of Wall Street analysts, the ones I have met have unfailingly been talented credible individuals who know their crafts. As with professional athletes, however, they tend to cancel one another out. I would intuit that the same holds for hedge funds or any groupings of smart Wall Street professionals. A sense of invincibility takes root, fueled by high pay, with little thought for equally smart competitors focused on the same asset subclasses. A natural result of this dynamic has been the rise of index funds.

This early realization framed the singularly guiding question of my career: does anyone consistently outperform in ways that can be tracked for superior risk/reward outcomes? Folding this question into a broader strategy. and often feeling like Wall Street’s ultimate outsider before becoming established, I developed and ran the InsideTrack® portfolios for Citi Smith Barney, Morgan Stanley, and subsequently Global Key. The goal was simple: to profitably imitate observable ‘smart’ money. Insider transactional disclosures formed a component of the approach, as did limiting clients primarily to a pool of public company insiders across industries and geographies. These unique individuals became a brain trust inspiring further ideas, and many became friends.

Over time, InsideTrack® became increasingly quantitative to a point where our interns often hold masters or PhD’s from Berkeley, Stanford, or Columbia. We no longer ‘moneyball’ analysts, that idea having been arbitraged away, but will look at anything promising while maintaining a healthy awareness that appealing ideas often fail. One notable example is Congress and the Senate, a group we concluded performed no better than randomly even when trades bore a geographic or committee relationship to a legislator or were unusually large for the individual. In recent years, insider disclosures have become a primary area of our focus.

Much of our work remains confidential, although we have committed to publishing some of our findings academically, as we believe they represent important advances in behavioral finance. Our first paper has found, for example, that insiders worsen at acquiring shares while improving at selling, and that the frequency of an insider’s trading correlates negatively to performance. More than 200 academic papers have been published on officer/director insider trading, but ours was unique for taking a time series approach to make these discoveries.

This has been an introductory post describing the unlikely evolution of a career into ‘smart money.’ Future posts will explore ‘smart money’ from a variety of vantage points while introducing team members and sharing how they came to join this endeavor. Thank you for reading.