market microstructure

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Replication Data: Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices

Replication Data: Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices

Lisa
Open Dataset
Creators: David Ardia, Emanuele Guidotti, and Tim A. Kroencke
Publication Date: 2024
Creators: David Ardia, Emanuele Guidotti, and Tim A. Kroencke

This dataset, hosted on Harvard Dataverse, contains the replication data for the study “Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices” (Ardia, Guidotti & Kroencke, 2024, Journal of Financial Economics). It includes OHLC (open, high, low, close) price data and estimated bid-ask spreads used to validate a new efficient estimator of bid-ask spreads that can be applied to daily price data without requiring intraday transaction data.

bidask – R and Python Package for Bid-Ask Spread Estimation

bidask – R and Python Package for Bid-Ask Spread Estimation

Lisa
Open Dataset
Creators: Emanuele Guidotti
Publication Date: 2025
Creators: Emanuele Guidotti

The bidask package, hosted on GitHub, provides R and Python implementations of the efficient bid-ask spread estimator developed in Ardia, Guidotti & Kroencke (2024, Journal of Financial Economics). It enables researchers and practitioners to estimate bid-ask spreads from daily OHLC price data without requiring tick-level transaction data, making liquidity estimation accessible for a wide range of financial datasets.

Replication Data: Heterogeneous Liquidity Providers and Night-Minus-Day Return Predictability

Replication Data: Heterogeneous Liquidity Providers and Night-Minus-Day Return Predictability

Lisa
Open Dataset
Creators: Zhongjin Lu, Steven Malliaris, and Zhongling Qin
Publication Date: 2023-03-02
Creators: Zhongjin Lu, Steven Malliaris, and Zhongling Qin

This dataset, hosted on Mendeley Data, contains the replication data for the study “Heterogeneous Liquidity Providers and Night-Minus-Day Return Predictability” (Lu, Malliaris & Qin, 2023, Journal of Financial Economics). It includes high-frequency trading and order flow data used to examine how differences among liquidity providers, such as market makers and other traders, during overnight versus intraday periods generate predictable patterns in stock returns, with implications for market microstructure and asset pricing.

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