Part 2: The rise of the machines: Building the talent to support quantitative trading in commodities

While the prospect of computers automating trading strategies and taking out the need for the physical intervention of a trader may sound like all-round bad news for commodities traders, the rise of the machines in commodities creates many opportunities for those with the right skills.

As quantitative and algorithmic trading strategies advance in the commodities markets, traders who do not want to become dinosaurs will need to learn new computerized principles, and commodities firms will have to invest in, and compete for, the best human capital to develop their platforms.

We anticipate a huge battle for talented individuals able to deliver market-leading platforms for firms willing to invest. Trading professionals with strong academic profiles, and especially PhDs, in computer sciences, physics, maths and engineering will be in high demand, as will those with strong exotic derivatives trading experience in markets such as equities and interest rates, which can be transferred to commodities.

The ability to combine the application of complex technological data analytics with fundamental macroeconomic research underpinned by advanced maths, engineering or other scientific credentials will be extremely attractive to trading firms. Professionals who have worked at global macro hedge funds, quantitative research firms or top tier investment banks, and then progressed to work for commodity-specific hedge funds or commodity merchants, will be particularly sought after.

But it may not be easy to hire in such talent. The challenge for those looking to bring in these professionals is that the concept of automated trading and algorithmic trading strategies is still relatively new to the commodities world. As a result, there may not be many trading professionals with a proven track record in building robust and successful automated trading models in commodities, and so firms will need to hire people from equity and related markets and adapt their skillsets to commodities.

Another issue is competition. Professionals with the necessary specialist and niche quantitative skills to develop automated trading models, and then trial and test those platforms, will be highly sought after, and salaries will inevitably sky-rocket. Bringing such talent aboard could be transformative for a business: introducing a fresh approach, and a chance to revisit trading strategies and innovate in a way that could generate a significant competitive advantage.

Another opportunity with these hires is the potential for a commodity trading merchant to centralise an automated trading model that can then be adapted for a variety of commodity products.

Successful human capital strategies in response to advances in quantitative and algorithmic trading will mean commodity trading firms having a combination of fundamentally-driven trading strategies and technical systematic automated trading strategies. Being able to deliver such a two-pronged approach will potentially put those firms willing to invest early at a huge competitive advantage when it comes to formulating superior trades.