Real-world applications
The opportunity to measure, monitor and manage market liquidity provides opportunities to add value in both the pre- and post-trade environments.
From a pre-trade perspective, minimizing execution cost is the main focus, with modelling scenarios around ease of execution for portfolio re-balancing adding the ability to optimize execution workflow.
Following trade execution, use cases center around governance where the emphasis is on evaluating liquidation profiles, typically concentrating on liquidation horizon.
Pre-trade portfolio optimization
Traditionally, portfolio selection has primarily been based upon market risk factors or price based measures. Whilst this is a time served approach, the cost of achieving expected returns may have an adverse effect upon net portfolio performance.
Including liquidity measures such as liquidation cost into the asset selection process allows this variable to be minimized whilst maintaining a specific risk profile.
By using Liquidation Cost as one of the optimization variables within the Bloomberg PORT application, we are able to reduce the expected turnover of securities within a portfolio, with an associated reduction in trading costs across the strategy. The net result is a reduced drag on portfolio alpha.
Analyzing the effect of market events
Following a market risk event, historically it has been difficult to gauge changes in the ability to execute transactions. Mid-2018 witnessed tension between China and the USA around tariff levels, which had a knock on effect upon transaction costs for equities within the region.
Provision of liquidity measures allow these to be incorporated into either the investment process or to supplement pro-active portfolio management.
Examples of these include:
Scenario analysis
Stress testing both the asset and liability side of the Balance Sheet is becoming increasingly important from both a regulatory and internal governance perspective. Most global regulators either currently have or are developing detailed guidance to incorporate this within firms' Liquidity Risk Management (LRM) frameworks.
Examining the effect on both liquidation cost and liquidation horizon profiles following redemption requests under both normal and stressed market conditions facilitates more efficient portfolio management. This also allows compliance with regulatory reporting mandates globally. For prospective investors demonstration of enhanced governance processes via analysis of additional subscriptions provides further confidence in the fund.
Comparing liquidity profiles between risk portfolios and benchmark portfolios
Changes in price are not always mirrored in the ability to execute trades. Whilst minimizing beta as a measure of tracking error, the ability to decompose areas of the portfolio which may cause issues in the future is a valuable input into any decision making process.
Assessing how liquidity measures change through time and how these are distributed over a portfolio allows portfolio managers to re-balance portfolios ahead of a deterioration in market conditions.
The reaction to the September 2018 Italian EU budget deficit target demonstrates how changes in ease of execution were not uniformly distributed across the entire benchmark BTP curve.
