Liquidity risk – Algorithmics advocates different metrics for different components of liquidity risk

Toronto - 7 May 2009

In its recent submission to the Basel Committee on Banking Supervision’s consultative paper ‘Proposed enhancements to the Basel II Framework’, Algorithmics has focused on liquidity risk and the techniques necessary to effectively understand and manage the three specific risk components which are embedded within the broader category of liquidity risk.

Whilst strongly endorsing the Committee’s overall view that the strengthening of supervision is necessary, Algorithmics takes a step further in suggesting that:

• liquidity risk needs to be considered at a more granular level and should be split into its component parts – funding, market and contingency risk -and then calculated using the risk measures which are most appropriate for each component
• a more extensive analysis of model risk is required to enable allocation of risk capital according to the complexity of the pricing models
• leverage caps should not be set uniformly for all banks. They should be dependent on the size of the institution.

Dr Mario Onorato, Senior Director of Balance Sheet Risk Management Solutions at Algorithmics and Honorary Senior Lecturer, Cass Business School in London, said: “In our view, the majority of liquidity risk is funding liquidity risk and it should be measured in cash flow not value terms. Therefore, it should be addressed by supervisors accordingly.

“It is only by splitting liquidity risk into its components and then by calculating each using the appropriate risk measure, that firms will have a complete understanding of their liquidity risk, and regulators will be able to supervise it. Funding liquidity risk should be addressed in terms of the minimum liquidity sources defined by stress scenarios. Other components of liquidity risk that depend on market or credit risk factors can still be addressed with value-based capital measures. It is important for regulators to converge to a common approach so as to avoid regulatory arbitrage.

“In addition, model risk is an area that requires more analysis. Complexity of products and embedded optionality have made banks’ risk assessment and representation increasingly dependent on assumptions. Where pricing models and parameter calibrations are not supported by empirical evidence or long-established acceptance in the market, the capital charge should reflect a conservative regulatory ethos.

“Ultimately, enterprise risk management models should not have economic capital as the only cornerstone of oversight. The task of ensuring sustainable growth and long-term value creation should be supported by more appropriate and comprehensive metrics that consider assets and liabilities in an integrated manner. In this environment, liquidity risk becomes an integral part in the setting and monitoring of explicit risk appetite and reward targets.”

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