Lightning Network Economics: Channels

21 Pages Posted: 6 May 2021 Last revised: 13 Sep 2021

See all articles by Paolo Guasoni

Paolo Guasoni

Boston University - Department of Mathematics and Statistics; Dublin City University - School of Mathematical Sciences; University of Bologna - Department of Statistics

Gur Huberman

Columbia University - Columbia Business School, Finance

Clara Shikhelman

Chaincode Labs

Date Written: May 5, 2021

Abstract

Compared with existing payment systems, Bitcoin’s throughput is low. Designed to address Bitcoin’s scalability challenge, the Lightning Network (LN) is a protocol allowing two parties to secure bitcoin payments and escrow holdings between them. In a lightning channel, each party commits collateral towards future payments to the counterparty and payments are cryptographically secured updates of collaterals. The network of channels increases transaction speed and reduces blockchain congestion. This paper (i) identifies conditions for two parties to optimally establish a channel, (ii) finds explicit formulas for channel costs, (iii) obtains the optimal collaterals and savings entailed, and (iv) derives the implied reduction in congestion of the blockchain. Unidirectional channels costs grow with the square-root of payment rates, while symmetric bidirectional channels with their cubic root. Asymmetric bidirectional channels are akin to unidirectional when payment rates are significantly different, otherwise to symmetric bidirectional.

Keywords: lightning network, bitcoin, cryptocurrencies, payment systems

JEL Classification: E42

Suggested Citation

Guasoni, Paolo and Guasoni, Paolo and Huberman, Gur and Shikhelman, Clara, Lightning Network Economics: Channels (May 5, 2021). Michael J. Brennan Irish Finance Working Paper Series Research Paper No. 21-7, Columbia Business School Research Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=3840374 or http://dx.doi.org/10.2139/ssrn.3840374

Paolo Guasoni (Contact Author)

Dublin City University - School of Mathematical Sciences ( email )

Dublin
Ireland

HOME PAGE: http://www.guasoni.com

Boston University - Department of Mathematics and Statistics ( email )

Boston, MA 02215
United States

University of Bologna - Department of Statistics ( email )

Bologna, 40126
Italy

Gur Huberman

Columbia University - Columbia Business School, Finance ( email )

3022 Broadway
New York, NY 10027
United States
(212) 854-5553 (Phone)

Clara Shikhelman

Chaincode Labs ( email )

450 Lexington Avenue
New York, NY 10017
United States

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