Professor Coin: How do you pay for cryptocurrencies like Bitcoin and Ethereum?

Professor Andrew Urquhart is Professor of Finance and Financial Technology and Head of Finance at Birmingham Business School (BBS).

This is the third part of Professor Coin's column, in which I bring valuable insights from published academic literature about cryptocurrency to the reader. This week we examine how cryptocurrencies fare.

In any market, one of the most important questions is ‘What is the expected return on the investment? This age-old question has been studied thousands of times by academics, investment bankers, traders and funds in the equity markets.

In the year One of the most famous discoveries that helped Eugene Fama win the Nobel Prize in Economics in 2013 is the Fama-French factor, which helps explain market returns, the performance of small and large firms, and the stock returns of high book-to-market and low book-to-market firms.

They extend this with Fama-France's five-level model, which includes profitability and investment climate, and has been shown to be very successful in explaining equity returns.

But how do we deal with cryptocurrencies in the absence of balance sheets and therefore no access to book-to-market ratio or investment performance data of the firm?

This is a popular area to study in the cryptocurrency literature, as cryptocurrency prices are incredibly volatile and difficult to predict.

One of the most important works, a 2022 paper by Yukun Liu, Aleh Tsyvinsky and Xie Wu, studies various pricing conditions known in equity markets, which can be applied to cryptocurrencies (such as volume, momentum, volume and volatility), excess market returns, Size and speed are worth over 1,800 cryptocurrencies, and help explain the returns. This result indicates that the pricing of cryptocurrencies is not the same as that of equity shares.

By Siddharth Bambhwani, George M. A follow-up paper by Korniotis and Stefanos Delikoras takes advantage of the information investors can glean from blockchain. The paper explores whether two blockchain-base factors, computing power and network size, help explain a portion of cryptocurrency returns. The authors suggest that these two factors help explain returns and that blockchains provide information beyond market data (such as price, volume, and volatility) that can value cryptocurrencies.

Finally, a very recent paper by Athanasios Sakas and myself went beyond the previously mentioned work and created 13 scenarios based on chain-based data from more than 35 different blockchains.

These factors are based on whale holdings, coin activity, network value and decentralization of crypto holdings. Using a sophisticated technique to capture the performance of these factors together, the paper shows that a very simple model, including market capitalization returns and network distribution, explains cryptocurrency returns better than anything else found in previous literature. In particular, investors demand a “whale premium” to hold cryptocurrencies with a low level of decentralization, or as the authors call them.

So, cryptocurrencies may not be that different with transactions when trying to price them—but given the vast amount of data on the blockchain, using this data to predict the future value of cryptocurrencies is of some value.

Edited by Stephen Graves

For more information, see:

Bhambhwani, S., Delikouras, S., Korniotis, GM (2023). A cross section of blockchain features and cryptographic returns. Journal of International Financial Markets, Institutions and Money, 86, 101788.

Liu, Y. Tsyvinski A. (2021). Risks and returns of cryptocurrency. Review of Financial Studies, 34, 2689-2727.

Liu, Y., Tsyvinksi, A., Wu, X. (2022). Common risk factors in cryptocurrency. Journal of Finance, 77, 1133-1177.

Sakas, A., Urquhart, A. (2024) Blockchain Factors. Journal of International Financial Markets, Institutions and Money, 94, 103012.