Buy-side Awards 2016
Regulators are trying their best to get a grip on liquidity risk, in several instances proposing asset liquidity measurements the buy side must report. But in the absence of an established standard for measuring liquidity – especially in the fixed-income arena – their efforts have lacked a common theoretical basis.
Buy-side firms have also taken jumbled approaches to the issue. Sometimes initiatives have been different between a single company’s own portfolio management, trading and risk management departments.
Bloomberg took a step back from this confusion to see if it could identify the fundamentals of liquidity risk and use them to address both regulatory requirements and the need for a standard approach.
“First, we studied the most basic components of liquidity, to construct a quantitative framework that could be applied across asset classes. Second, we created a measurement model that uses a wider array of traditional and non-traditional factors that can influence liquidity, such as trade size and liquidity of comparable assets on the target security,” says Naz Quadri, head of quant research and development for enterprise solutions at Bloomberg in New York.
In its research and development of a liquidity risk model, Bloomberg made use of machine learning, applying clustering techniques to infer the liquidity metrics of an illiquid bond by finding and analysing comparable bonds. Also, it used machine learning to help apply its vast database of fixed-income market data to the calibration process.
The result is the Bloomberg Liquidity Assessment Tool (LQA), which provides a standard definition of liquidity and a consistent approach to measuring the expected cost of liquidation for a specific volume of securities, and a desired time horizon. It also provides a score designed to indicate security-level liquidity with respect to liquidation cost and its distributions across different volumes.
The LQA model provides firms with a consistent and reliable calculation of liquidity, so firms can not only understand risk exposures, but also meet regulatory mandates to report total time to liquidation and cost for given volumes
Naz Quadri, Bloomberg
Bloomberg LQA can be used by various groups across a buy-side firm. “Portfolio managers gain consistent information about the dependencies of position size, cost and time to liquidation for a specific security, or across multiple asset classes in a portfolio. Risk managers can consistently measure liquidity and related systemic risk. LQA enables these stakeholders to assess and price redemption risks, run scenario analysis and incorporate liquidity considerations into the investment process, such as balance returns against redemption profiles, and use the liquidity score as a key risk indicator,” says Quadri.
Bloomberg began delivering LQA as an enterprise data feed to individual clients in mid-2015. Clients register their portfolios, which can contain 200,000 or more securities in some cases, with Bloomberg and submit these daily or at another frequency. They then receive machine-readable reports that can plug directly into internal risk management systems. In March this year, the company made LQA available on its Bloomberg Professional terminal for ad hoc analysis of individual securities.
“Regulation is compelling investment firms to standardise their approach to risk management, so they can reliably produce standard metrics and outputs needed for regulatory reporting,” says Quadri. Global asset managers are affected by the Alternative Investment Fund Managers Directive and the Undertakings for Collective Investment in Transferable Securities framework in Europe, the Securities and Exchange Commission's 22e-4 rule and Form PF in the US, and the Securities and Futures Commission of Hong Kong's guidance and set of principles published in July, all of which call for more detailed and consistent reporting.
“The LQA model provides firms with a consistent and reliable calculation of liquidity, so firms can not only understand risk exposures, but also meet regulatory mandates to report total time to liquidation and cost for given volumes,” says Quadri.
Clients include a major US asset management firm, which says it chose Bloomberg LQA because it offered the most advanced approach to estimating and measuring real-time liquidity for fixed income, and uses actual market data to ensure the measures are objective and react to changes in market liquidity conditions.
Another major US asset manager says Bloomberg's depth of data and track record in producing high-quality analytics that draw on its data were key factors in choosing LQA. “Particularly for fixed income, LQA brings transparency in a consistent manner to complement the liquidity assessments traders and risk managers make on a daily basis,” says the firm’s head of risk.