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<p>In line with market trade signals, we develop a micro-founded structural price formation model featuring partially informed and noise traders. Imposing zero expected net profit per trade under market efficiency, we derive the model’s likelihood to reliably estimate daily market and funding liquidity from intra-day transaction prices. We examine the dynamic interplay among stock volatilities, market liquidity, and funding liquidity via an MGARCH-VAR process. Fitting the model using standard realized volatility econometrics on intra-day data estimates, our analysis of NYSE stocks uncovers four stylized facts: (i) stock volatilities, market liquidity, and funding liquidity co-move; (ii) these co-movements intensify during funding liquidity shortages; (iii) lower volatility stocks tend to have higher market liquidity; and (iv) funding liquidity constraints more adversely affect the market liquidity of high-volatility stocks.</p>

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Funding liquidity and stocks’ market liquidity: structural estimation from high-frequency data

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  • 发表日期：

    2025年5月13日

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  • Gian Piero Aielli,
  • Davide Pirino

摘要

In line with market trade signals, we develop a micro-founded structural price formation model featuring partially informed and noise traders. Imposing zero expected net profit per trade under market efficiency, we derive the model’s likelihood to reliably estimate daily market and funding liquidity from intra-day transaction prices. We examine the dynamic interplay among stock volatilities, market liquidity, and funding liquidity via an MGARCH-VAR process. Fitting the model using standard realized volatility econometrics on intra-day data estimates, our analysis of NYSE stocks uncovers four stylized facts: (i) stock volatilities, market liquidity, and funding liquidity co-move; (ii) these co-movements intensify during funding liquidity shortages; (iii) lower volatility stocks tend to have higher market liquidity; and (iv) funding liquidity constraints more adversely affect the market liquidity of high-volatility stocks.