# Net Buying Pressure and the Information in Bitcoin Option Trades

**Authors:** Carol Alexander, Jun Deng, Jianfen Feng, Huning Wan  
**arXiv:** [2109.02776](https://arxiv.org/abs/2109.02776)  
**Date:** 2021-09-06  
**Summary page:** https://www.summarizepaper.com/en/paper/2109.02776v1/

## Key points

- Study by Carol Alexander, Jun Deng, Jianfen Feng, and Huning Wan on Bitcoin option trades
- At-the-money option prices driven by volatility traders; out-of-the-money options influenced by both volatility traders and individuals with proprietary information
- Deribit evolving into an efficient platform for aggregating information from informed traders
- Dynamics of directional-learning versus volatility-learning among traders in different options contracts over time periods
- In 2019 and 2020, both volatility-driven demands and directional-motivated demands impact implied volatility changes
- Preference of informed traders for trading cheaper out-of-the-money options over at-the-money options due to knowledge about volatility and directionality
- Contrast with findings from established markets where directional-learning typically outweighs volatility-learning
- In 2021, only directional-learning evident in at-the-money put options due to bitcoin price bubble phenomenon

## Summary

In their study "Net Buying Pressure and the Information in Bitcoin Option Trades," researchers Carol Alexander, Jun Deng, Jianfen Feng, and Huning Wan examine how supply and demand from informed traders influence market prices of bitcoin options. The study utilizes tick-level data from Deribit options and supports the limits-to-arbitrage hypothesis regarding market maker supply. The findings reveal that at-the-money option prices are primarily driven by volatility traders while out-of-the-money options are influenced by both volatility traders and individuals with proprietary information about future bitcoin price movements. This highlights a shift in demand-side effects within the bitcoin options market compared to previous studies on established options markets in the US and Asia. Specifically, Deribit is rapidly evolving into a more efficient platform for aggregating information from informed traders. The study also delves into the dynamics of directional-learning versus volatility-learning among traders in different types of options contracts over various time periods. The analysis indicates that in 2019 and 2020, both volatility-driven demands and directional-motivated demands impact out-of-the-money and deep-out-of-the-money implied volatility changes. However, only volatility information drives at-the-money option trades during this period. This suggests that informed traders with privileged knowledge about volatility and directionality tend to prefer trading cheaper out-of-the-money options rather than more expensive at-the-money options. Furthermore, the study contrasts findings from well-developed markets where directional-learning typically outweighs volatility-learning. However, in 2021, only directional-learning is evident in at-the-money put options due to the bitcoin price bubble phenomenon. Overall, these insights shed light on how informed traders' behaviors shape market prices of bitcoin options on Deribit and provide valuable implications for understanding market dynamics in cryptocurrency derivatives trading.