Q&A with Troy Buckner, Managing Principal, NuWave Investment Management

Nov 18 2010 | 11:08am ET

New Jersey-based, multi-strategy hedge fund manager NuWave Investment Management applies its quantitative pattern recognition-based trading strategies to both financial and commodities markets, overseeing assets in excess of $900 million. The goal of the firm, established in early 2000, is to “capitalize on directional trading opportunities missed or ignored by long-biased investors and most hedge funds.”

A career spent analyzing such opportunities has taught NuWave Managing Principal Troy Buckner the importance of one factor in particular – the human factor. FINalternatives' Mary Campbell spoke to Buckner recently about the role of behavioral finance in NuWave’s approach to investment.

FINalternatives: Can we begin with a little background on NuWave?

Buckner: NuWave is a systematic trading firm. We have a broad macro style that may be implemented through both futures and cash equity markets. The Combined Futures Portfolio is a managed futures strategy that trades 44 futures markets internationally. With holding periods that range from a few weeks to as long as six months (averaging 55 days), the strategy provides broad participation in directional price movements across commodities, grains, softs, energies, and financial markets (including currencies, fixed income and stock index contracts) around the world. We also have an equity market-neutral strategy that trades only blue-chip U.S. equities. In either case, we are purely systematic in our implementation and entirely model driven.

How do you define behavioral finance and how does it factor into your investment decisions?

Well, I don’t know that I can offer you a definition of behavioral finance that would be particularly insightful given that we don’t prepare our presentations with the idea of educating individuals on the science of behavioral finance, but aspects of behavioral patterns do find their way into our work …What we model is significantly a function of the human component that affects prices. And so we would argue that it really isn’t necessary for us to understand fundamental events themselves, as the headlines will change, the catalysts will change. But, in our case, we’re focusing on the behavioral patterns of human beings in response to those events. And so, recognizing that it is always going to be the case that there will be some new explanation, some fundamental factor, some change in perhaps world economic perspective that may affect the markets—those are categories of information, and human beings tend to respond in a fairly repetitive manner to information fitting into those categories. Certainly not repetitive each and every day [or] so repetitive that it would be easy to identify all the repetitive responses, but that’s our specialty. We consider that there is a great deal of random noise, but the repetitive responses are significant enough that we can identify them and profit from them on a fairly consistent basis.

How do you go about identifying and measuring these repetitive responses?

Well, a great deal of our research effort is focused on identifying intuitively appealing information that does show up in price. What we don’t attempt to do is highlight and describe a particular pattern and give it a name (a head-and-shoulders pattern, for instance). Nor do we catalog a handful or a list of patterns and then assign trading rules to those patterns—rather, we examine the characteristics of price action in any given market and the features that have defined, or dominated, a particular market’s price movements over the recent and intermediate-term past.

So, in our case, we study everything from tick data to daily data that may go back as much as 18 months. And we’re looking for the routine and the repetitive aspects of price behavior that we argue are indicative of emotional response—fear, greed, hope, despair being examples of emotions that tend to dominate human behavior. And this is not new…Dow Theory is based on a similar concept, Elliott Wave Theory—[but] our implementation is very different, we don’t subscribe to the “A Wave, B Wave, C Wave” philosophy, you know, counting waves one through five…we approach the problem differently, but we share the view that, by and large, there is a consistent factor in markets . . . and that’s the human factor.

And so, whether we’re studying the 1970s, the 1980s or the present, there is a relatively stationary effect that is associated with the human factor. Consider that supply and demand imbalances will always occur and that there will always be some catalyst or fundamental explanation (which may be identified after the fact, not necessarily ahead of time). What we feel is reasonably consistent is the human being behind the price movement. It’s in our DNA. If we can identify that portion of the price action that is repetitive, and if we can see through the randomness . . . discard the randomness and identify those repetitive footsteps—that’s our goal.

And has this been something you’ve been incorporating into your business for some time or is this a relatively new approach for NuWave?

Since our inception … in February 2000. The idea really came to me—at least, the early form of the theory—back in my days at Salomon Brothers, where I quickly came to the conclusion that all traders are pattern recognizers, whether they perceive themselves to be pattern recognizers or not. The proprietary trader on the desk who said he traded on ‘gut feel,’ well, after watching him, I came to the conclusion that it wasn’t really ‘gut feel’ at all; rather, it was actually an analysis of patterns and information…and each piece of information itself is changing over time. So there’s a…pattern to the information itself and then, collectively, multiple pieces of information, or patterns if you will, which form a profile for that trader.

There’s only so much information a trader can follow, but in each person’s case they’re relating this complex picture in their mind of the five, six, seven categories of information that they typically follow and relate it to their past experience—when have they seen a combination of information look similar? And among those historical situations that looked similar, what were the outcomes? And from my perspective, I could see capital being committed when they could conclude that they’d seen this general pattern of events before and that there was a reasonably consistent outcome.

I read one definition of behavioral finance that said it was a collection of facts, not a complete theory, does that ring true for you?

[Laughs] I wish I could say that I have a complete knowledge of behavioral finance in terms of concept and theory or what it is or isn’t—the truth is that our specialty is pattern recognition. As it relates to behavioral finance, I can at least suggest that behavioral patterns portend directional price movements across all markets, and it is this information that guides NuWave’s investment decisions. 

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