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Liquidity

ESMA Liquidity
Stress TestingContents
01 Guideline Overview
04 Workflow

ESMA Liquidity
Stress Testing
ESMA’s new Liquidity Stress Testing (LST) guidelines take effect on 30 September
2020, and will apply to all Alternative Investment Funds (AIFs) and Undertakings for theCollective Investment in Transferable Securities (UCITS) along with Money Market Funds.
The guidelines enhance existing standards, promote consistency and increase frequency
of current LST practices. Whilst not prescriptive, the guidelines specify fund managers
need a “strong understanding of their fund’s liquidity profile” in both hypothetical andhistorical stress scenarios.
Bloomberg’s award-winning Liquidity Assessment (LQA) solution enables quantitativeevaluation of execution measures for in-scope firms. Examples include liquidation cost orliquidation horizon for a fund’s holdings under custom stress scenarios. This provides thefoundation for a comprehensive Liquidity Risk Management (LRM) framework supporting
ESMA LST guidelines.

Guideline Overview
The 16 principal-based guidelines promote awareness of liquidity risk incorporatingstress testing to enhance liquidity risk management.
From an implementation perspective, the guidelines fall into three categories:
Governance Framework, Scenario Definition, and Stress Test Results.
ESMA Liquidity Stress Testing Guidelines
1. Governance Framework

2. Client Input/Customization*

3. Stress Test Output**#1. LST Model Design#5. Frequency#6. Use of LST Outcomes#2. Understanding Liquidity Risk

#7. Fund Specific LST#9. Data Availability#3. Governance Principles#8. Stress Scenarios#10. Product Development#4. L ST Policy#12. Liability Based LST#11. Asset Based LST#13. LST on Other Liabilities#14. Investments in Less Liquid Assets#15. Combined Asset & Liability LST#16. Aggregating LST Across Funds*Client customizable input to Bloomberg’s Liquidity Solution
Component of Bloomberg’s Liquidity Solution**Figure 1 — Overview of ESMA guidelines with summary classification information.

ESMA Liquidity Stress Testing

Governance Framework
As liquidity risk measurement and management evolves, legacy frameworks often do nothave sufficient flexibility to build an appropriate governance framework. Bloomberg’s fully
customizable LQA solution enables a fund-specific framework providing the analytics tosupport custom liquidity stress scenarios, metrics, and reporting.
LQA can assess the impact of multiple fund-specific scenarios based on the key liquidity risk
factors applicable to fund holdings, and seamlessly incorporate the results into Enterpriserisk-management workflows.Front office workflow is supported through a ProgrammaticAPI, Excel Add-In, and/or the Bloomberg Terminal.
Scenario Definition
Defining appropriate stress scenarios can present a major challenge due to a lack ofobservable data-points to calibrate such events. LQA provides a straightforward approachto scenario definition based on four market parameters:• R edemption Amount• Daily Available Volume• Price Volatility• Bid-Ask Spread
Firms can calibrate multiple scenarios using data from historical events, and/or hypothetical(forward looking) events to simulate a variety of stresses, including those with low probability
but high impact. Stress factors can be defined either as a multiplier of current market conditions
or as absolute values. Applied at the portfolio-level, asset class-level or even security-level
this provides customisation options to complement fund investment style. A parameter-based
approach enhances explainability to senior management.
Whilst LQA does not have oversight of a fund’s liabilities or investor profile, firms can evaluate
the liquidity sensitivity of a fund under any foreseeable redemption scenario.

Portfolio
Fixed
IncomeEquity

NormalMild
Scenario

Moderate
Scenario

SevereScenario

ExtremeScenario

Redemption %

1%

3%

5%

7%

10%

Confidence Level

50%

50%

50%

50%

50%

Daily Available
Volume Multiplier10.90.75

0.50.25

Price Volatility
Multiplier

11.25

1.51.75

3

Bid Ask
Spread Multiplier

11.1

1.25

1.5

2

Daily Available
Volume Multiplier

110.9

0.90.75

Price Volatility
Multiplier

11.5

233.5

Bid Ask
Spread Multiplier

11.25

1.50

22.5

Figure 2 — Sample redemption scenario definitions with asset class-specific stresses.

2ESMA Liquidity Stress Testing

Stress Test Results
Generation of fund specific actionable liquidity metrics is possible following the applicationof discrete scenarios. LQA leverages a vast amount of global transactions data to model
the time it takes to liquidate each position conditional upon liquidation cost preferences(i.e. market impact). Aggregating liquidity metrics facilitates measurement of the cumulativeliquidation horizon for each scenario.

Figure 3 — Cumulative liquidation horizon under various stress scenarios.

Guideline 15 requires evaluation of stress scenarios applied to both the Asset and Liability
sides of the Balance Sheet. The example below illustrates portfolio level liquidation horizons
for a variety of stress scenarios under different redemption (liability) shocks.
LQA provides flexibility to incorporate fund-dealing frequency. This allows an early warning system
to alert which scenarios have adverse outcomes in meeting fund redemptions. Firms can alsomeasure the cost of liquidating each position within customisable time-periods to determine
the total liquidation cost of each scenario.

The values showed on this table reflect expected liquidation horizon (days).
Figure 4 — Basic dashboard combining asset and liability shocks overlaid with limit monitoring framework.

3

ESMA Liquidity Stress Testing

Workflow
LQA offers seamless integration into your current workflow whether based in a third party
application, internal systems, Excel, and/or the Bloomberg Terminal. LQA liquidity analytics
are available through:• BLP API for programmatic connectivity via Python, R, C++, Java, etc.
• E xcel API• Enterprise Data-Feed• Bloomberg Terminal:• LQA<GO> for single security and sector comparison• LQAP<GO> for portfolio liquidity profiling

User Input

Bloomberg Liquidity Solution

Enterprise Delivery
OutputInput

Terminal:
LQA<GO>
LQAP<GO>
Market &Trading Data
Enterprise
Data via
Excel API

FundHoldings
Reference
Data
Scenario
Definitions
Pricing
Data

Liquidity
Analytics

Enterprise
Data via API(Python, R,C++, etc.)

Custom Excel
Reports

Third Party/InternalApplications

CustomReporting &Dashboards

Enterprise
Data Feed

Comprehensive documentation is available including implementation guidance, stress-testing
calibration examples, model methodology papers, and detailed model validation documents.

4

ESMA Liquidity Stress Testing

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