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Bridging the gap between quant and discretionary

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As the rate of data proliferation intensifies, hedge fund managers are increasingly leavening their discretionary approaches with quantitative methods in order to better utilise the available data. 

“Traditionally, the idea was that asset managers were either discretionary, making investment decisions in a less systematic way, or they were quants – susceptible to criticism for following a too strict rules-based approach. The truth is somewhere in the middle, where both sides apply some measure of the other in their approach but in different parts of their investment processes,” says Daniel Leveau, VP Investor Solutions at SigTech, “However, the explosion in technology and analytical methods seen in the last couple of years means managers can start to quantify things that were not really quantifiable five or 10 years ago.” 

The easy access to powerful technology allows discretionary investment managers to become more technology-driven investors. These funds are showing a growing propensity to systematise parts of their investment process, be it in the widening of their product range to include quant funds or the integration of systematic analytics into their investment processes. 

In Leveau’s view, this is necessary in order for managers to compete in today’s market and to generate the alpha they need: “Many managers that historically wouldn’t consider themselves to be quantitative in their approach need to start applying more of these systematic analyses to their investment processes to stay competitive.” 

The findings in a research report published by SigTech further supports this view. Three out of four respondents (77%) agree hedge funds need to ensure both access to high quality and operationally ready data and cutting-edge technological infrastructure in order to achieve strong absolute returns in the future. 

Leveau describes this shift as the “quantification of the industry”. This doesn’t mean the end of discretionary investment management, however the trend towards investment decisions being based on systematic analysis is gathering momentum. 

This need is felt more acutely in times of turmoil within financial markets. “Hedge funds are in a prime position to show their true value for investors in today’s market; having the ability to deliver absolute returns in any market environment. However, to stay competitive and to profit from the general quantification of the industry, hedge funds need to continue investing in new technology and data,” Leveau says. 

Barriers to quantification 

However, this shift does not come without challenges. A common hurdle managers face is accessing the skill set necessary to implement quantitative techniques within their firm. “It is not just the hedge fund industry being quantified but other industries as well. This means competition for skilled professionals in the field is fierce,” observes Leveau, “Those who have the required knowledge are highly sought after, not just by the financial industry but by other sectors as well. It’s very easy to underestimate how much time and effort goes into building the code infrastructure needed to run these analytical systems and to deploy these strategies successfully.” 

The next challenge in implementing these changes is dealing with the data needed to run quant models. Simply buying the data is not enough; it needs to be cleaned, validated and pre-mapped to be operationally ready. These are tasks managers often find tedious. 

“This is one of the major pain points. When we talk to investors, an aversion to cleaning and validating data is a common theme,” notes Leveau, “therefore, firms are breaking up their value chains: focusing on their strengths and outsourcing tasks better suited to external professionals.” 

Therefore, managers gain economies of scale by focusing on their core competency, allowing service providers to become experts at delivering operationally-ready data and to build and deploy quantitative infrastructure in a scalable and flexible manner. 

Tough to compete 

Managers who do not transition into using more quantitative techniques could be in for a bleak future. Leveau says: “The main risk of inaction is that managers face tougher and tougher competition and subsequently fall further and further behind. Data and new information is being processed faster and faster and through collaboration, the computing mind can elevate what the human mind can do. Managers who fail to innovate can struggle performance wise. Further, as systematic investment strategies are gaining market share from discretionary managers, the potential pie they can take a piece of shrinks from a structural point of view.” 

Leveau highlights the benefits of applying quantitative techniques to investing: “One of the main advantages of a systematic approach is that it is non-emotional and thus ensures greater consistency. This doesn’t mean it is always a better approach but from experience, people don’t tend to make the wisest decisions when there is havoc in the markets.” 

“And now, with the ever-expanding computing power available, together with more extensive datasets, managers can also react faster to changes in the market. It’s not that systematic investing is always going to outperform discretionary but there will be these small advantages that will add up in the long-term.” 

Consolidation up ahead 

So according to Leveau, the discretionary and systematic approaches are going to connect more as time goes by: “There will be more flow between these areas and systematic analysis is going to play some part in all investment processes, even within a traditional discretionary approach. 

“I also believe that there’s going to be increased specialisation in the industry, with a move away from hedge funds doing everything internally. Instead, the trend for outsourcing with third party specialist providers ensuring managers gain access to the right technology and data will accelerate.” 

On the data side, Leveau expects to witness consolidation: “There are so many data providers out there, but there is a big gap between getting the data from a provider to hedge funds actually making use of that data. The industry needs to see the expansion of an intermediary space where specialist providers take the data from the vendors, clean it, validate it and make it operationally ready. These groups must have the expertise to fully understand what impact the data can have on the hedge funds’ investment strategies and present the data accordingly. 

Daniel Leveau, VP Investor Solutions, SigTech

Daniel, VP of Investor Solutions at SigTech, has a 20+ year career in investment management. He has held senior positions including Chairman, CEO, head of portfolio management and senior fund manager at hedge funds, asset managers and banks. At SigTech, Daniel acts as a subject matter expert and frequently publishes articles and papers.

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