Algo Risk Service Insight is a publication that covers topics of interest to Algo Risk Service clients including current regulatory and risk reporting news, data partnerships, service features, and common support questions and answers. Produced by members of the Algo Risk Service team, articles are developed to assist clients in optimizing their return on investment in Algo Risk Service.
Current Issue: Issue 3: Spring 2012
The prevalence of quantitative techniques in equity risk management continues to grow. Even firms that invest based on fundamental principles are finding that objective, robust quantitative models help to pinpoint specific market factors that can be sought out or avoided. By subscribing to a new extension, Algo Risk Service users can gain access to a new breed of advanced equity factor models created by Axioma. They can then further analyze the key contributors to their risk, all within a flexible, consistent, multi-asset class simulation framework.
Risk analytics continue to find a larger audience outside of the traditional buy side middle office. Executives, front office managers, investors and regulators all have specific requirements for understanding firm risk exposure and portfolio outcomes. The Algo Risk Service Advanced Reporting module can provide clear, well-presented results for all stakeholders both within and outside client organizations.
Various attribution and decomposition techniques exist to provide a summary view of the key sources of portfolio risk. At some point however, analysts need to dig deeper into the results and observe scenario level results. With the new Scenario Viewer functionality, the Algo Risk Service offers the capability for users to go further in analyzing results at a portfolio, instrument or risk factor level.
Following the credit crisis of 2008, interdependence between counterparties has become a standard concern amongst buy-side market participants. Simple measures such as current exposure can give an approximation of the aggregate exposure to counterparty risk, but the dynamics of risk factor sensitivity over longer investment horizons begs an approach working in a more advanced simulation framework.
Liabilities are a key ingredient in strategic risk management. The 2007/2008 financial crisis and following sovereign debt crisis has shifted attention to pension fund risk management and pension plan asset allocation strategies. The sudden turnaround from surplus to deficit served as the catalyst for more regulatory pressures and calls for better risk management. This growing demand for pension funds to focus on scheme-wide market risks, means that moving actuarial models into a broader asset liability structure is a crucial requirement. This in turn challenges technology systems to support a wider range of asset classes with more sophisticated methodologies and risk management capabilities.
Delays in the closing of accounts, delays in fund reporting and the final confirmation of positions can play havoc with the consistency of risk simulation. Approaching the challenge in a data and time independent manner, Algo Risk Service (ARS) can now handle backdated ‘As Of‘ processing through a flexible workflow.