Bitcoin Return Prediction: Is It Possible via Stock-to-Flow, Metcalfe’s Law, Technical Analysis, or Market Sentiment?

Austin Shelton ()
Additional contact information
Austin Shelton: Department of Finance, Sykes College of Business, The University of Tampa, Tampa, FL 33606-1490, USA

JRFM, 2024, vol. 17, issue 10, 1-24

Abstract: Popular methods to value Bitcoin include the stock-to-flow model, Metcalfe’s Law, technical analysis, and sentiment-related measures. Within this paper, I test whether such models and variables are predictive of Bitcoin’s returns. I find that the stock-to-flow model predictions and Metcalfe’s Law help to explain Bitcoin’s returns in-sample but have limited to no ability to predict Bitcoin’s returns out-of-sample. In contrast, Bitcoin market sentiment and technical analysis measures are generally unrelated to Bitcoin’s returns in-sample and are poor predictors of Bitcoin’s returns out-of-sample. Despite the poor performance of Bitcoin return predictors within out-of-sample regressions, I demonstrate that a very successful out-of-sample Bitcoin tactical allocation or “market timing” strategy is formed via blending out-of-sample univariate model predictions. This OOS-blended model trading strategy, which algorithmically allocates between Bitcoin and cash (USD), significantly outperforms buying-and-holding or “HODL”ing Bitcoin, boosting CAPM alpha by almost 1300 basis points while also increasing portfolio Sharpe Ratio and Sortino Ratio and dramatically reducing portfolio maximum drawdown relative to buying-and-holding Bitcoin.

Keywords: Bitcoin; cryptocurrency; asset pricing; Metcalfe’s Law; stock-to-flow; technical analysis; sentiment; blockchain (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1911-8074/17/10/443/pdf (application/pdf)
https://www.mdpi.com/1911-8074/17/10/443/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jjrfmx:v:17:y:2024:i:10:p:443-:d:1490211

Access Statistics for this article

JRFM is currently edited by Ms. Chelthy Cheng

More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().