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Machine Learning and Liquidity Dynamics in European Stock Markets

Author

Listed:
  • Veni Arakelia
  • Guglielmo Maria Caporale
  • Mirto M. Gasparinatou
  • Menelaos Karanasos

Abstract

This paper examines the forecasting of liquidity dynamics in European stock markets by means of traditional econometric models and machine learning techniques. It uses daily data for the DAX, CAC 40, FTSE 100, FTSE MIB, and IBEX 35 over 2010–2026, liquidity being measured by the logarithmic Amihud illiquidity indicator. The empirical framework compares ARIMA models and a dynamic panel specification with Random Forest, Extreme Gradient Boosting (XGBoost), and Support Vector Regression (SVR) within a common rolling one-step-ahead forecasting framework. The results show that liquidity is highly persistent and that the dynamic panel model achieves the lowest forecast errors, although Diebold–Mariano tests indicate no significant predictive advantage over the leading machine learning models. SHAP analysis reveals that trading activity, lagged liquidity, and market uncertainty are the main determinants of liquidity forecasts. The findings highlight the complementary role of explainable machine learning in empirical finance.

Suggested Citation

  • Veni Arakelia & Guglielmo Maria Caporale & Mirto M. Gasparinatou & Menelaos Karanasos, 2026. "Machine Learning and Liquidity Dynamics in European Stock Markets," CESifo Working Paper Series 12829, CESifo.
    • Handle: RePEc:ces:ceswps:_12829
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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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