Active Portfolio Management of diverse fund types by an individual Portfolio Manager (“PM”) or an Investment Management team without effective oversight can lead to potentially unfair allocation of investment decisions between funds, a type of conflict of interest called side-by-side risk that needs to be managed and mitigated. In material cases, the asset management firm may have to compensate the disadvantaged client.
Controls for Side-by-Side risk
The higher the dispersion of individual funds with different investment objectives managed by the same PMs, the higher is the side-by-side risk.
Disproportionate or unfair allocation of individual orders to some funds may be identified periodically by comparing funds with each other and assess if they have performed as expected with regards to their risk and return profile. Investment Risk reviews are however rarely able to identify individual assets or investment decisions that create a dispersion of the risk and return profile between broadly comparable funds.
Most often the fairness or proportionality of allocations is assessed manually by applying a sampling approach when analysing and comparing the allocations by a PM. This occurs with a considerable time lag and is time and resource consuming considering the large volume of orders in any given period and is entirely based on the judgement and experience of the controller.
Statistical Model Approach
A better approach to this problem is to use an automated algorithmic analysis to support the monitoring of side-by-side risk, in order to
- mitigate side-by-side risk in a timely fashion and at the source - the release of orders by the PM to the dealer
- reduce the time spent on manual reviewing samples of orders and
- increase the coverage of an analysis to 100% of all orders and of all PMs.
Such an algorithm can analyse order data and apply risk scores to orders reflecting the risk of potential disproportionate size of an allocation at the time of the investment decision.
This analysis informs a controller of the orders with the highest side-by-side risk within a comparable group of funds, allowing to focus the effort and analysis on confirmed outliers which are the trades most requiring analysis and potential follow-up activity.
Key steps that this analysis needs to take are:
Following the deployment of this approach at an active asset management client, we accurately identified and scored the highest risk orders for funds managed by the same PM. Through back-testing we were able to confirm that the highest risk orders identified by the solution matched the current controller’s output after manual analysis.
- Control reviews of side-by-side risk can expand from the existing manual sampling approaches to review the full set of data across all orders.
- The time required for manual filtering and reviewing allocations is reduced by over 90%.
- The statistical and automated approach to monitoring side-by-side risk provides better consistency in the control quality and eliminates the judgement aspect of the manual sampling control.
- Focus on investigating confirmed outliers and clearing any allocations deemed to potentially constitute a side-by-side risk.
For more information on any of the contents of this article please contact Daniela Strebel or Jorge Prado De Castro.