This is particularly so for institutional investment managers who have to meet margin calls, perform regular fund rebalancing, execute redemptions, among other potentially liquidity-threatening activities. Failure to afford liquidity risk management the focus and priority jeopardizes the health of an institution, perhaps fatally so.
Pension funds and other institutional asset managers tend to look at their liquidity risk in two different ways: through the prism of market liquidity and through the prism of funding liquidity. From a perspective of market liquidity, asset managers need to monitor their available liquidity in the future, particularly in the near-term.
Funding liquidity, in contrast, involves the capacity to project all possible cash flows and cash balances, as well as identifying potential funding gaps. Both these functions are highly germane to the effective functioning of any financial institutions.
Rules and Regulations
In the wake of the great financial crisis, and as part of the 2010 Basel III banking reforms, the Basel Committee on Banking Supervision (BCBS) introduced both the Liquidity Coverage Ratio (LCR) and the Net Stable Funding Ratio (NSFR). These were designed to improve the resilience of banks to short-term liquidity crunches of the kind which had been so damaging in 2008 and 2009.
The LCR was structured to ensure that banks possess enough high quality liquid assets (HQLA) to survive a period of market dislocation and illiquidity lasting 30 calendar days. A 30-day period is deemed to be the minimum necessary to allow the bank’s management enough time to take remedial action.
The NSFR, however, is designed to fortify a bank’s liquidity over a longer time period and seeks to do so by incentivising banks to rely on more stable sources of funding rather than often illiquid assets. In May 2016, the Federal Deposit Insurance Committee (FDIC) also introduced a proposal to create a net stable funding ratio that would “implement a liquidity requirement consistent with the NSFR…”
From September 30th 2020, under new rules introduced by the European Securities and Markets Authority (ESMA), EU fund managers must employ liquidity stress-testing tools to better insulate themselves in times of market dislocation. The regulator puts particular emphasis upon the ability of investment funds to meet redemptions.
The Margin Call Minefield
In these periods, margin calls are increasing as asset values depreciate, but market liquidity is also drying up. Assets which might have taken a day or two to liquidate can now take 10 or 15 days and then only with a much increased haircut. Asset managers are caught in the rip tide.
There are two types of margin call: variation margin and initial margin. Both forms of margin increase, and sometimes dramatically, during periods of market dislocation and volatility.
For example, in the worst days of the recent COVID-19 sell-off, some instruments witnessed their biggest price movements in three decades, and initial and variation margin spiralled higher. Recent data released by the Bank of England shows that in March, the daily variation margin calls by UK central counterparties were up to five times higher than seen in January and February.
The amount of initial margin required by central counterparties also increased dramatically, hitting a peak which was 31% higher than the average margin seen earlier in the year.
Margin calls appear to have done their job: central counterparties were protected and derivatives markets continued to function during the recent crisis. But, funding those margin calls created considerable stress as banks and asset managers scrambled to find sources of liquidity. Rather worryingly, the Bank of England noted, “This contributed to a ‘dash for cash’ in March 2020, as some market participants appeared to have insufficient buffers of cash-like assets to meet actual or anticipated margin calls.”
Static Versus Dynamic
It is not that market participants are indifferent to the urgency of liquidity risk management and its relevance during market stress – it is that effective risk management is acutely difficult to perform comprehensively.
The asset management industry has realised that static stressed-scenario liquidity testing is not sufficient to meet demands in a period of market dislocation. Consequently, it has, with the larger players leading the pack, moved to a dynamic, multi-period stress testing methodology.
For example, in the real world, asset managers are bound by their mandate and documentation to rebalance portfolios according to pre-determined models or risk parameters.
Consequently, a multi-event stress scenario is required to more adequately reflect the reality of husbanding liquidity during periods of dislocation. The institution must possess sufficient liquidity to be able to withstand several cycles of the same crisis but in different forms.
Alternatively, funds modelling their capacity to withstand multiple redemptions might incorporate a series of shocks, such as, the collapse of a major market-maker. Historically, this has caused extreme redemption levels of 15% or 20% of total assets and adverse external market shocks such as an unexpected hike to interest rates.
A multiple scenario and rebalancing strategy, according to designated rules, can also incorporate opportunities for tilting – that is to say evaluation of possible market openings for trading gain. Comprehensive and efficient liquidity stress-testing is a win/win.
But, while the theory might be acknowledged, the practice, at the majority of investment funds, is still intermittent, idiosyncratic and largely manual. Those in the industry speak of a couple of staffers getting together in an office every two or three months with only an Excel spreadsheet for company – and this is even at larger funds. The process is wasteful and costly, and often prone to human error.
What is required is an automated, integrated and single view of liquidity risk across multiple asset classes in all markets. This single platform, operated in a central location, would have the capacity to run forward-looking liquidity analysis, calculate and report liquidity risk exposure, which takes into account all potential future obligations.
Such a platform would produce much more effective, continuous and consistent liquidity risk data. It would also free up the staff currently employed in such work to more valued-added deployment.
Data, Data & More Data
As is nearly always the case in the development of state-of-the-art solutions, the development of robust analytics presents a big headache but the accumulation of data of sufficient granularity and depth presents an even bigger one. This is particularly true in the case of, say, a sovereign wealth fund which possesses a plurality of different asset types but might not face any liabilities or dispersals for the next 20 or 30 years.
Only the most sophisticated and powerful engines can handle the requirement to accumulate and assess enough and the right type of data, to underpin a single view, automated, dynamic liquidity risk platform. Such an engine needs to be able to gather data from a variety of different sources. It is this that makes automation possible, and can produce a solution that can then be calibrated and indexed according to the internal priorities of the institution in question.
Proper evaluation and provision of liquidity risk is not a quick fix; it requires diligent contemplation of needs, and a reliable partnership with the right technology and data provider. COVID-19 has reshaped many of our previously firmly held beliefs about life and the workplace; it might also be the case that it has justly refocused attention upon the pressing need to tackle liquidity risk management.