Liquidity Risk and Other Non-Market Risks › Key Parameters

Michael BrenndoerferDecember 24, 20252 min read
Quantitative FinanceAll chapters
Part 10 of 15Risk Management and Financial Risk Controls
Chapter 57Liquidity Risk and Other Non-Market Risks › Key Parameters
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The key parameters for Liquidity-Adjusted VaR (LVaR) are:

  • Standard VaR: The baseline market risk measure assuming instantaneous liquidation. This captures the risk from adverse price movements over the VaR horizon and is the foundation upon which liquidity adjustments are built.
  • Position Value: The total market value of the position to be liquidated. Larger positions face greater liquidity challenges because they require more market capacity to absorb.
  • Spread: The bid-ask spread expressed as a percentage. This represents the immediate cost of crossing the spread. In LVaR calculations, typically half the spread is used since you only pay one side when exiting.
  • Days to Liquidate: The estimated time required to exit the position without excessive price impact. This is determined by position size, average daily volume, and the maximum acceptable participation rate. Longer liquidation periods increase both the time component of risk and the accumulated impact cost.
  • Daily Volatility: The volatility of the asset, used to estimate price impact and risk over the extended liquidation horizon. Higher volatility increases both the expected impact (since impact scales with volatility in the square-root law) and the risk of adverse price movements during the liquidation period.

These parameters interact in important ways. Higher volatility increases both the standard VaR component and the liquidity adjustment. Longer liquidation periods compound the effect of volatility through the square-root scaling of both impact and extended holding risk. Wider spreads are often correlated with longer liquidation times, since illiquid assets typically have both wider spreads and lower trading volumes. Understanding these interactions is essential for properly calibrating LVaR models.