Publication Type

PhD Dissertation

Version

publishedVersion

Publication Date

5-2026

Abstract

This dissertation examines whether Bitcoin options risk-reversal (RR) spreads predict future Bitcoin returns, using daily Deribit data from April 2021 to December 2025 (1,723 observations).

In the primary 25-delta, 90-day specification, the RR coefficient is significant at the 1% level in a thirteen-variable baseline regression with Newey–West standard errors. Robustness tests across all available delta–tenor specifications show statistically significant RR coefficients in the majority of configurations, concentrating in the 30–180-day maturity band.

The butterfly spread (BF) also predicts returns. Both remain significant after controls are added: the RR t-statistic increases from 1.91 (univariate) to 3.73 (full baseline), and the BF t-statistic increases from 2.13 (univariate) to 2.34 (full baseline).

Forward return block regressions show that the predictive effect is concentrated in the first day, with the cumulative regressor coefficient remaining positive and generally increasing through day one to six without reversal. This persistence pattern is more consistent with information content than with transient liquidity or hedging effects.

The predictive signal attenuates after January 2024. In the pre-2024 period, both RR and BF coefficients were highly significant at the 1% level. Post-2024, the RR signal weakens to the 5% level and the BF signal becomes insignificant. A Chow test provides evidence of a structural break (F = 1.76, p = 0.040) of the regression parameters. Around the start of 2024, several significant developments coincided with changes in the structure of the crypto market: the approval of spot Bitcoin ETFs by US regulators, a sustained Bitcoin bull market, and regulatory changes associated with broader institutional acceptance of Bitcoin as an investible asset class. These structural developments coincided with a deterioration of the BTC volatility smile predictive signals, a pattern consistent with the adaptive markets hypothesis.

The findings extend options-implied return predictability to cryptocurrency markets and provide empirical evidence consistent with the adaptive markets hypothesis as Bitcoin markets institutionalise.

Degree Awarded

PhD in Business (General Management)

Discipline

Finance | Finance and Financial Management

Supervisor(s)

HU, Jianfeng

First Page

1

Last Page

71

Publisher

Singapore Management University

City or Country

Singapore

Copyright Owner and License

Author

Download

Share

COinS