Do quant processes add value to portfolio management?
The question was the subject of a panel session I was on at the most recent annual HedgeNews Africa Symposium. The topic goes to the heart of the debate within the hedge fund (and indeed wider investment management) industry—how can firms identify alpha and generate returns, and are humans or machines the best way to do it?
The reality, as the panel made up largely of quant fund managers argued, is there are benefits from employing a mix of quantitative and qualitative approaches. Since humans are ill-equipped to manage today’s inexorable rise in data volumes, speed and complexity, fund managers of all descriptions are increasingly turning to quantitative processes in their portfolio management to help filter information and spot useful signals. However, applying a layer of human subjective thinking is necessary to ensure the machines respond appropriately to those signals and market movements.
Events this past year underscore the point. Many pure quant funds suffered in 2020 when their models struggled to cope with the pandemic-induced dislocations and volatility. Actively-managed hedge funds proved more adept at navigating and profiting from the extraordinary circumstances, demonstrating the value human judgement can still bring to trading decisions.
The session discussion highlighted a number of lessons from a technology and operations perspective.
One factor contributing to quant funds’ recent underperformance is their algorithms struggle with black swan events such as Covid-19, geopolitical shocks or extraordinary financial policy measures they aren’t programmed to predict.
Employing a robust, comprehensive risk management solution can help. A dedicated third-party provider has the resources, expertise and insights to continually add to the extensive range of scenarios and what-if capabilities built into their risk modelling platform. As well as saving investment firms the work of developing a system in-house, buying a solution is considerably faster and less expensive.
Another lesson to emerge from the discussion is the importance of process automation. Quant-oriented trading can create a lot of transactions and associated charges. Automating the trade compliance and workflow steps from order entry to settlement allows firms to manage high transaction volumes with less effort, fewer errors and at lower cost.
The right portfolio management, accounting and reporting infrastructure can automate trade capture and reconciliations, and provide accurate, up-to-date P&L, performance, and exposure reporting to improve front office investment decisions. Platforms offering full support for all instruments, transaction types and currencies also provide firms with the flexibility to pursue investment opportunities wherever they arise.
Focus on core competencies, outsource the rest
Such systems are vital, as is having the right people. Whether it is programmers and investment strategists designing the algorithms, or portfolio managers and traders directing trading decisions, investment firms should direct resources to those areas of differentiation where they can add the most value.
Managing operational tasks in-house offers hedge funds little competitive advantage. Outsourcing daily administrative functions efficiently alleviates the load, freeing firms to focus on generating alpha, and meeting and exceeding their investors’ expectations — regardless of their portfolio management strategy.