Founded by Troy Buckner, NuWave Investment Management LLC pursues a unique multi-strategy approach to investing in many of the world’s most liquid markets. Buckner serves as Managing Principal, joined by a staff of 10 professionals, including Yury Orlov, NuWave’s Head of Research, and Craig Weynand, the firm’s Chief Operating Officer.
NuWave has long considered itself a pioneer in the application of machine learning and artificial intelligence techniques to the financial and commodity markets, having first deployed such concepts as far back as 2001. In the last decade significant advances in computing power and the development of increasingly sophisticated AI modelling concepts have continued to shape NuWave’s systematic approach to trading.
“By way of analogy, consider the incredible advances made in terms of machine-based speech recognition,” says Weynand. “Ten years ago, machines were capable of only a rudimentary understanding of speech – the only acceptable responses being ‘Yes’, ‘No’ or ‘Representative.’ Five years ago, the range of responses was somewhat broader, consisting of certain phrases or specific sentences. Today, the machine is capable of ‘understanding’ virtually any response. Similarly, personal assistants, such as Siri or Google, understand queries, perform tasks, follow instructions – all from conversational speech.”
Building on the example of speech recognition, Weynand goes on to explain that NuWave applies machine learning and AI to better understand the language of financial and commodity markets. “It is undeniable that the markets speak a distinct language … a language that we – along with many others – are trying to decipher. Different investment managers may utilise different methods or focus on different input data, but we all share the same goal – to better understand what the market is saying and, in doing so, to identify potential trading opportunities. Each piece of data, whether technical or fundamental, is analogous to an individual syllable … and multiple data points, like multiple syllables, combine to form words and sentences which, in turn, form paragraphs – all of which help to describe price behaviour.”
He further notes that, much like speech, there are infinite ways to parse and aggregate feature-rich information. “Consider such features as directionality, volatility, seasonality, sequence, technical data, fundamental data – there are countless ways to define or categorise such data sets and determine which combinations of relevant data sets are meaningful. Essentially, advanced machine learning and AI concepts can sift through history and compare combinations of data sets to determine which combinations are likely to yield high probability directional outcomes. Simply put, machine learning and AI help us better understand what the market is telling us.”
NuWave’s systematic approach to directional trading can be applied across multiple asset classes. Along with four unique futures portfolios and two cash equity funds, the firm now serves as sub-adviser to a liquid alt mutual fund that blends NuWave’s cash equity trading capabilities with its diversified managed futures trading, all within a single portfolio, offering the potential for non-correlated returns during both bull and bear market scenarios.
Weynand confirms that, while 2018 has been a rather challenging year for many commodities markets, many of NuWave’s systematic trading methodologies have identified significant opportunities for directional commodity trading, “particularly during August, when much of NuWave’s outperformance was derived from trading in commodities.” n