We consider three different investment managers that vary by dependence on the level of quantitative analysis and implementation.
Each methodology has their own advantages and drawbacks, which we will aim to highlight. We consider the discretionary manager, the quantitative manager and the hybrid manager.
The discretionary manager relies on a multitude of quantitative and qualitative factors to guide their investment decisions. There is significant weight given to the manager’s experience and feel for the market environment.
The discretionary manager is able to harness the incredible processing power of the human brain, making decisions based on variables that are unable to, or uneasily, be modelled. For example, during 2007, investment managers in the US visited areas with high subprime lending to help identify whether loans could be repaid. Based on this experience, more informed investment decisions could be made to trade securities that were correlated to such an event.
There is significant pressure on the manager being right. When wrong, this can often lead to emotionally based trading decisions and extreme risk taking. Only the discretionary managers that have strong control over their emotions, and hence, risk, outperform over the long term. Additional emotional biases may occur if a manager likes an executive team or has some history with the company.
A Quantitative Fund selects securities using advanced quantitative analysis. Quantitative managers build models based on an investment hypothesis and test their theory with historical data, ultimately guiding an investment decision. These funds use strategies that are rules-based and implemented by a computer, with little or no human intervention.
Quantitative managers are able to back-test a large universe of securities over multiple economic cycles in an attempt to find the best-performing strategies and asset classes. Entry and exit rules are developed to maximise return while maintaining some defined level of risk. Investment strategies that have previously been successful and have qualities that indicate likelihood to succeed in the current market environment give the quantitative fund the potential to outperform the market.
Quantitative investing often uses multiple screening criteria to identify companies with various risk characteristics. For example, one momentum model might identify stocks that are currently performing well, with share prices at all-time highs, while another may find stocks that have recently under-performed, but are poised for a rebound. Combining these screened stocks in a portfolio may enhance its overall diversification.
The success of a quantitative investment strategy depends on how well it represents the current market environment. Although there are many similarities, no one market environment completely mirrors itself. This may lead to false signals being generated and loss of capital.
Hybrid – discretionary manager & quantitative signals
The hybrid manager attempts to mitigate the negatives of the purely discretionary and quantitative managers, while capturing the main advantages of each manager. The hybrid manager is able to use quantitative screens as a tool and apply their experience and understanding of the current market environment in attempt to generate alpha (out-performance).
The hybrid manager receives signals from quantitative screens and applies their discretion for trade entry and exit. This allows the manager to add further layers of analysis that are hard to model while receiving multiple trading signals that would be time consuming to discover manually. For example, a quantitative screen may reveal that a company has a particular technical setup with positive expectancy, but the manager identifies a new executive who has failed previously to deliver on their strategy at another company.
Given the repeatable and consistent nature of a quantitative approach, the manager can achieve discipline when following a historically proven strategy. Sticking to the approach will help eliminate emotion and excessive risk taking in the investment process.