The Evolution of Liquidity Risk Management – Risk.net | Region & Cash

After the global financial crisis that began in 2007/08, policymakers have multiplied their efforts and implemented reforms to strengthen the resilience of the financial sector. But – while established frameworks and models for market, credit and operational risk were implemented and understood by the industry – liquidity risk was the most difficult to model and manage due to its systemic component.

By Thierry Ciszewski, Senior Risk Manager, HSBC asset management

Thierry Ciszewski, HSBC Wealth Management

Thierry Ciszewski, HSBC asset management

To address this difficulty, industry-wide regulations have been put in place to mitigate liquidity risk. These include Rule 22e-4 of the Securities and Exchange Commission, which prompted industry participants to evolve their framework and focus on the impact on the market; the 2018 Principles of the International Organization of Securities Commissions, under which many regulators updated their approaches to liquidity risk; and the European Securities and Markets Authority’s Guidelines on Liquidity Stress Testing, which proposed an end-to-end framework to mitigate systemic risk, reduce contagion risk and strengthen the global financial system.

While these policies made strides toward better liquidity risk management, the Covid-19 pandemic put pressure on wealth managers that elude regulatory scrutiny and shifted global risk perceptions. As significant volatility set in, bid-ask spreads widened and transaction costs rose dramatically, dealers’ ability to provide liquidity became noticeably constrained and the cost of accessing liquidity skyrocketed despite decent exchange volumes. Against this background, liquidity risk also poses a reputational risk for wealth managers – especially if it is not managed proactively. Sound management of fund liquidity risk is a prerequisite for managers and the demand from stakeholders to demonstrate that this risk is managed appropriately has never been greater.

Addressing liquidity risk is paramount in today’s market of rising interest rates, inflation concerns and rising geopolitical tensions. These dynamics bring liquidity risk assessments into the spotlight as they provide a critical basis for funds to better anticipate and manage fund liability claims.

A framework for liquidity risk management

Liquidity Trend Analysis, Bloomberg 0522

Bloomberg LQA Data as of April 2022

The main objectives of any liquidity risk management approach should be based on the following principles:

  • Products should be understandable and meet the needs of investors
  • Commitments should be fulfilled and reflected in investment strategies
  • Potential liquidity mismatches should be prevented and managed to protect investors’ interests.

Disclosure is another key piece of the puzzle — and not just disclosure to regulators. Investors may choose to invest in less liquid assets, but these decisions must be made on a fully informed basis. The disclosures should be comprehensive enough to cover a fund’s key characteristics, the potential for illiquidity associated with different types of asset classes, the potential impact of significant redemptions of open-ended funds, and the dilutive effect of excess cash during periods of significant inflows. Fund managers have reporting obligations to their investors and failure to provide appropriate disclosures can damage reputation and relationships.

The Funds’ ability to raise liquidity is dependent on their ability to liquidate the underlying investments within a specified time frame at an acceptable cost and market impact in dynamic market conditions. The changing and often binary nature of market liquidity complicates this process. While analysis of market liquidity has evolved significantly, analysis of funds’ liabilities is often limited due to data unavailability and limitations, e.g. This lack of efficient data management can ultimately hamper companies’ ability to accurately forecast investor inflows and outflows.

Ensuring correct liquidity data for fund managers

By leveraging state-of-the-art data and extending frameworks originally designed for regulatory compliance, many organizations are able to holistically and proactively manage liquidity risk across their entire organization.

An example of an effective solution is Bloomberg’s liquidity rating (LQA) tool that uses advanced financial models to consider a broader universe of securities, including those for which there is no data or little to no recent trading activity. By training models on a large database of executed trades from a variety of sources worldwide, it is calibrated daily to capture changing market conditions.

Bloomberg’s model has three parameters: spread sensitivity, price impact sensitivity and price impact exponent. It also has three explanatory variables: bid-ask spread, volatility risk, and participation rates. The utility and purpose is to identify early warning signals and get a more informed picture of the multi-dimensional concept of liquidity, which first requires an assessment of the liquidity ratio before the cost of liquidity can be estimated. Since the liquidation ratio depends on three factors – the liquidity of the portfolio to be sold, the amount to be sold and the liquidation policy – it is important to consider that the liquidity ratio is relative to the trading restrictions and the liquidation plan (or trading structure).

In general, liquidity costs are measured by transaction costs. However, in a liquidity stress testing program, this measure is only theoretical as it is based on the transaction cost model. Therefore, it can be complemented by the ex-post cost of liquidity, also known as the effective cost.

When an asset manager does not have enough data, regression and advanced modeling techniques must be used to establish the value of these parameters. That LQA The model is used across the industry for regulatory compliance. Because this model is data-driven, it eliminates subjectivity and provides a more robust and defensible liquidity assessment.

In finding the optimal approach to liquidity risk, managers must consider the big picture of having the right access to the right data in the right context. Liquidity risk assessment is an increasingly integral part of an asset manager’s regulatory compliance framework and the proactive management of liquidity risk – particularly in more turbulent markets.

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