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The Myth of “Money Always Finds Its Most Efficient Home”

This is a guest post by John Netto, a cross-asset class trader and author of The Global Macro Edge: Maximizing Return Per Unit-of-Risk. He is also the creator of the Netto Number, the Risk Factor Compensation System, and the Protean Strategy published on Collective2.

In March 2011, I began a literary journey that would last over 3000 hours, 200 weekends, 20 business trips, and would finally see its completion five and a half years later in October 2016. That journey was my 580-page book, The Global Macro Edge: Maximizing Return Per Unit-of-Risk. What set out to be a book on advanced strategies in the alternative investment space evolved into a comprehensive empowerment tool for investors, money managers, and advisers on how to enhance your own investment process, as well as manage and allocate to hedge funds and active money managers.

This journey was filled with numerous discoveries and why so much of the book is essentially “out-of-sample”. By that I mean much of the final content was not planned to be part of the original manuscript and experienced in real time as the book was being written. One of those key discoveries was the website Collective 2. It was such an important discovery because the book addresses what I believe are six huge myths on Wall Street and the problems they cause.

One of those myths is “money always finds its most efficient home”. In fact, I demonstrate anecdotally and empirically using websites such as Collective 2, that money often doesn’t find its most efficient home, or at least the time it takes to do so can be quite protracted.

During this journey, one of my most aspirational “aha” moments was when I discovered that the process of allocating capital is rife with inefficiencies.

I learned substantial allocations by large institutions were not necessarily based on what manager could generate the highest return per unit-of-risk. There were two reasons for this. The first was CYA (cover your backside) investing proto­col and the second was a lack of technology.

Allocators were not necessarily seeking the absolute best investment but, instead, the investment they could best justify to their bosses and investors. If an investment in a hedge fund with a storied history of success blows up, at least it’s defensible. However, if an investment with a manager from a nontraditional background, a start-up, or in a relatively obscure strategy suffers, it is easy for those in power to question the decision to invest in the first place. Collectively, there are allocators with control over trillions of dollars in assets who figure it is better for their careers to jump off a cliff with the crowd than invest in some newfangled, odd-looking flying device.

The second reason is one of technology. Most allocators can’t justify committing the due diligence resources that come from allocating to smaller, emerging managers. Whereas a large, established manager may have $500 million in capacity, a smaller manager may only be able to run his strategy up to $25 million before seeing noticeable degradation in performance. However, technology can go a long way towards solving this problem. If instead of doing extensive due diligence on a manager, it may be more cost effective to make a number of small allocations to prospective managers. Then, by using technology, seamlessly aggregate these small allocations into one account where you can monitor and enforce individual risk budgets.

I would much rather have 10 emerging managers each with a $1 million allocation running non-correlated strategies across a range of asset classes working within a predetermined risk budget than one manager working a $10 million allocation. Given the non-correlation benefits, it may be possible to allocate 2 million to each of those emerging managers and get a larger return in my portfolio with the same volatility as the allocation to the one large manager. However, cost, lack of know-how, and technology can be barriers for many in accomplishing this.

The good news is that Collective 2 can be a huge resource in finding those emerging managers, as they offer an array of tools and performance attribution on each strategy. Those who educate themselves in what metrics to look for and how to incorporate it into their investing process stand to benefit the most as the landscape of asset allocation changes in the years to come.

About the Author: 

Mr. Netto has conducted numerous live trading webinars where viewers watch his P&L, positions, and orders in real time for total transparency of his methods. He has appeared on CNBC’s Fast Money, Closing Bell, and Squawk on the Street, as well as Bloomberg, CNN, Fox Business Channel, and PBS. 

Mr. Netto is also the author of One Shot – One Kill Trading. Mr. Netto speaks, reads, and writes Japanese, Chinese, Portuguese, and Spanish to help him articulate his vision of the markets to an international audience. John Netto’s ability to convey esoteric concepts was put on display when he was featured in two documentary movies, Life on the Line and Ghost Exchange, where he simplified to viewers some of complex aspects of creating a point spread model on The Super Bowl and executing high frequency trading strategies. Netto served in the United States Marine Corps for over eight years and is passionate about Veterans’ causes.

Follow him on Twitter @JohnNetto

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