Part of Pack Creek’s compensation is linked to our ability to beat a benchmark. This value-added trading is at the core of what we offer our commodity hedge clients – when our clients achieve their hedge objectives, Pack Creek earns a performance fee. The better they do, the better we do.  It sounds straight forward but in reality this is a skill based activity that draws from decades of experience and knowledge.  Can this knowledge be systematically coded into a trading algorithm? Perhaps a better question is, should it be coded into an algorithm?

When speaking with clients, this topic of systematic trading comes up often. There is a natural tendency to compare systematic methods to discretionary methods. Driving the conversation is a single theme, “which method produces better performance?”

In the following piece, Cliff Asness and his team at AQR Capital Management tackle the issue.

Here are some highlights:

  • The terms ‘quantitative’, ‘systematic’ and ‘rules-based’ are often used interchangeably; they represent an investment approach that is often perceived to be in direct opposition to what a ‘fundamental’, ‘discretionary’ or ‘stock-picking’ approach may be.
  • While it is fair to contrast systematic and discretionary approaches, we stress that they are not opposites. Indeed, both systematic and discretionary managers pursue the same objective and both can be fundamentally-oriented. That is, they can use very similar inputs, but in different ways, to try and achieve the singular goal of improving investment performance.
  • Neither systematic nor discretionary managers are inherently superior. Each has the ability to deliver good investment outcomes and, as we show in the data, there is little evidence that one approach is better than the other.
  • The historical correlations between excess returns from systematic and discretionary managers are low, which suggests that many investors may benefit from incorporating both types into their allocations.
  • Importantly, historical correlations among systematic investors are also low, as low as they are among discretionary investors, suggesting that the notion that ‘all quants trade on the same signals’ is misplaced.