Demetrio Lacava, Paolo Santucci de Magistris
arXiv 1 Sep 2026 · Finance — Risk Management
arXiv:2609.00943 · PDF · Extracted main text
Market efficiency relies fundamentally on stable liquidity. Consequently, forecasting liquidity dynamics is a priority for both investors and regulators. We introduce a new tail-risk metric, Illiquidity-at-Risk (IlliQaR), designed to quantify the magnitude of extreme liquidity dry-ups. Relying upon the realized Amihud (a precise illiquidity measurement derived from high-frequency data as the ratio of realized volatility to trading volume) we assess the predictive power of various linear and non-linear econometric models, with a specific focus on the impact of discontinuous jump components. Accounting for these jumps is essential for achieving accurate probability coverage and better IlliQaR predictions during periods of systemic stress, where standard continuous models systematically underestimate the severity of liquidity evaporation. Our empirical analysis, encompassing the S&P 500 index and a cross-section of 25 large U.S. equities, demonstrates that incorporating jumps significantly improves forecasts of illiquidity. Our results suggest that individual stock IlliQaR violations often cluster during periods of S&P 500 liquidity stress. This indicates that Illiquidity at Risk is not just a localized concern but a systemic one, where the main index acts as a leading indicator for extreme dry-ups in individual stock liquidity.
appendix boundary found by appendix_titled_section at “Supplementary Document” · 72% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Lacava, Demetrio and Ranaldo, Angelo and Santucci de Magistris, Paolo (2026) Realized Illiquidity self | 1.000 | 9 | 4 | 100% |
| 2 | Ranaldo, Angelo and Santucci de Magistris, Paolo (2022) Liquidity in the global currency market | 1.000 | 5 | 4 | 100% |
| 3 | Yakov Amihud (2002) Illiquidity and stock returns: Cross-section and time-series effects | 0.928 | 4 | 3 | 100% |
| 4 | Hafner, Christian M and Linton, Oliver B and Wang, Linqi (2023) Dynamic autoregressive liquidity (DArliQ) | 0.843 | 3 | 3 | 100% |
| 5 | Hafner, Christian M and Linton, Oliver B and Wang, Linqi (2025) The permanent and temporary effects of stock splits on liquidity in a dynamic semiparametric model | 0.843 | 3 | 3 | 100% |
| 6 | Caporin, Massimiliano and Rossi, Eduardo and Santucci de Magistris,… (2017) Chasing volatility: A persistent multiplicative error model with jumps | 0.811 | 4 | 2 | 100% |
| 7 | Engle, Robert (2002) New frontiers for ARCH models | 0.811 | 4 | 2 | 100% |
| 8 | Fulvio Corsi (2009) A Simple Approximate Long-Memory Model of Realized Volatility | 0.644 | 2 | 2 | 100% |
| 9 | Pástor, L'ubo s and Stambaugh, Robert F (2003) Liquidity risk and expected stock returns | 0.644 | 2 | 2 | 100% |
| 10 | Chan, Wing H and Maheu, John M (2002) Conditional jump dynamics in stock market returns | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 39 scored citations.