According to the FMSB, sophisticated modelling techniques used for calculating trading risk and required capital came under significant global regulatory scrutiny following the financial crisis as a result of their acutely revealed shortcomings in containing risk. As a result, regulatory guidance seeking to address the possible adverse consequences of decisions based on incorrect or misused models was issued. Yet while this guidance applies to all model types, including the use of models in algorithmic trading, the degree of model risk and the potential magnitude of any adverse consequences varies significantly across model types.
In response, FMSB has published a final SoGP intended to support all firms in wholesale financial markets that operate electronic trading algorithms involving the use of models, taking into account the nature, scale and complexity of such models as well as existing systems and risk controls intended to mitigate associated market, conduct, credit and operational risks. The detailed guidance considers a range of factors, such as determining if a method used in an algo constitutes a model and tailoring model risk management activities for models deployed in algos to the context and purpose for which models are deployed.
“It is important that the industry comes together to make sure that good practice in a complex area such as this is set out in a way that can be well understood and easily applied, including practical examples,” says Myles McGuinness, CEO of FMSB.
Algorithmic trading risk summary (‘Key Risk Summary’)
The table above summarises material risks associated with the deployment of Algos either to fair and effective markets or to Algo operators. The table encapsulates conduct, market, credit, operational and Model Risks. A firm’s risk management frameworks, of which a model risk management framework is one component, will typically be designed to reduce or mitigate such risks, though appropriate calibration and effective application of such frameworks will be key to their effectiveness.
The guidance sets out nine statements of good practice which are relevant to the application of a model risk management framework to algos. The industry-developed good practice statements supplement existing broader supervisory guidance which FMSB says firms should continue to apply.
The statements include additional commentary and are followed by examples of applying a model risk management framework to algos indicating whether the examples are consistent or inconsistent with each SoGP.
Statement of Good Practice (SoGP)
SoGPs are issued by FMSB from time to time. SoGPs do not form part of FMSB Standards, and they are not subject to FMSB’s adherence framework. Rather, they reflect FMSB’s view of what constitutes good or best practice in the areas covered by the SoGPs in question. Member Firms are expected, and other firms are invited, to consider their own practices in light of the relevant SoGP and make any changes to such practices that they deem to be appropriate. Failing to do so will not, however, create any presumption or implication that a firm has failed to meet its regulatory or other obligations.
