The InsideTrackSM Portfolios
Building on our work with insider clients, we offer fee-based investment management services for individuals, families and institutional investors. We seek superior long-term returns emphasizing risk management and broad diversification in passive strategies together with active approaches through Global Key's InsideTrackSM portfolios.
Most active investment strategies underperform because the talents and resources of even savvy money managers are relentlessly matched by competitors, and few information sources or approaches are unique. In instances where a successful manager maintains an edge over time, it can remain difficult to distinguish luck from skill. Notwithstanding these objective realities, strong vested interests and marketing agendas have long sustained an industry reliant on high fees, although a decades-long shift away from active management toward passive indexing underscores a growing recognition that efficient markets do not necessarily justify these expenditures.
Understanding this landscape early, the InsideTrackSM portfolios began in 1996 by asking a different question: is there such a thing as ‘smart money’ that can be mimicked for constructing diversified investment approaches with better risk/reward metrics over time? Building upon academic and practical research necessary for launching the undertaking, what happened next followed the logic of the resulting answer to the ‘smart money’ question. First, the InsideTrackSM portfolios were offered almost exclusively to officers and directors of public companies who came to serve as a collective brain trust for understanding unique industry drivers and trends. Second, the portfolios became increasingly quantitative over time. Significant efforts went into deep scrubbing and refining of publicly available datasets, especially those pertaining to insider (officer and director) share trading activity around the world.
Success in pursuing this unconventional approach has relied upon strong scientific curiosity combined with a nimble willingness to recognize that some datasets that ‘ought’ to produce viable investment signals may not do so in the end. As an example, we put considerable time into cleaning up and studying the buying and selling disclosures of US Senators and Congresspeople in an effort that included singling out trades that were unusually large for a given legislator or that bore possible connections to committee assignments or home district relationships. In the end, the legislators exhibited no information edge, their collective trades amounting to a so-called random walk down Wall Street. In other cases, the value of a dataset can diminish over time. The InsideTrackSM portfolios put substantial early work into evaluating the recommendation track records of Wall Street analysts, running 50,000 Monte Carlo simulations on each of several thousand analysts over multiple years at several hundred firms. We identified only 2% of analysts as having a 75% chance or better of being ‘above average,’ the rest amounting again to randomness. These insights served the InsideTrackSM portfolios well for several years until arbitraged away by firms hiring large teams of PhD’s to study and organize the data for sale to institutional investors; we believe this information currently no longer contains an information edge.
The InsideTrackSM portfolios currently rely primarily upon signals around publicly disclosed insider trading activity. The disclosure filings can be complex, and one unique aspect of our work is that our close involvement with insider clients made us aware early that none of the commercial services extracting and reporting insider trades from the SEC website were doing so in an inaccurate manner. We accordingly spent several thousand hours refining a better extraction process, following which we have consistently been able to attract top research talent as a result of having cleaner data. Working closely with insiders has also spurred us to consider novel behavioral questions around insider trading performance that have not been asked in any of the nearly 200 academic papers that have explored the topic. We have publications pending that we believe will be important contributions to the field - stay tuned!