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

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

This repository implements an efficient estimator of the effective bid-ask spread from open, high, low, and close prices as described in:

Ardia, D., Guidotti, E., Kroencke, T.A. (2024). Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices. Journal of Financial Economics, 161, 103916. doi: 10.1016/j.jfineco.2024.103916

The estimator is available in:

C++ | Julia | MATLAB | Python | R | SAS

You can also check the pseudocode to implement the estimator in any programming language.

Contribute

If you implement the estimator in a new programming language and want your implementation to be included in this repository, please open a pull request.

Open data

The following datasets are available to download:

Download Dataset Description
download Bid-Ask Spread Estimates for U.S. Stocks in CRSP Contains monthly estimates of the effective bid-ask spread for each stock in the CRSP U.S. Stock database
download Bid-Ask Spread Estimates for Crypto Pairs in Binance Contains monthly estimates of the effective bid-ask spread for crypto pairs listed in Binance

Replication code

All code to replicate the paper is available here. The code meets the requirements of the cascad reproducibility policy for a rating of RRR.

Related works

You can browse publications related to the paper here.

Terms of use

All code is released under the GPL-3.0 license. All data are released under the CC BY 4.0 license. When using any data or code from this repository, you agree to:

Cite as

Ardia, D., Guidotti, E., Kroencke, T.A. (2024). Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices. Journal of Financial Economics, 161, 103916. doi: 10.1016/j.jfineco.2024.103916

A BibTex entry for LaTeX users is:

@article{edge,
  title = {Efficient estimation of bid–ask spreads from open, high, low, and close prices},
  journal = {Journal of Financial Economics},
  volume = {161},
  pages = {103916},
  year = {2024},
  doi = {https://doi.org/10.1016/j.jfineco.2024.103916},
  author = {David Ardia and Emanuele Guidotti and Tim A. Kroencke},
}