A Quantitative Analysis of BTC Implied Volatility: Seasonality Alpha

Not too long ago, there were numerous memes vilifying traders who found themselves as net sellers of crypto during Asia hours, leaving their Western counterparts to hold up the market. While the intraday seasonality of crypto spot prices has already received ample attention, a significant gap in public research exists regarding the seasonality of implied volatility dynamics in the crypto space. Given the round-the-clock nature of the crypto options market, we stand in a unique position to dissect intraday volatility regimes across different times of the day and pinpoint patterns that can be systematically leveraged for profit. Throughout our exploration of this subject, we’ve unearthed a compelling signal that offers a distinct perspective on BTC implied volatility dynamics.


1. Overview of Key Findings: 


Similar to the behavior of spot returns during different times of the day, a corresponding pattern has emerged for BTC IV. A simple yet powerful study involves analyzing the cumulative change in 30-day BTC ATM IV over the past six months and assessing its performance during different times of the day. As illustrated below, a striking disparity emerges when comparing IV changes between 6am to 12pm EST and 6pm to 12am EST.

Based on these results, it becomes evident that traders would be inclined to assume a net long vega position during US trading hours (6am to 6pm EST) and a short vega position during Asian trading hours (6pm to 6am EST). In theory, maintaining a constant ATM vega exposure using options over the past six months could have yielded roughly 75 vols during daytime, while netting 100 vols overnight.

In practice, of course, transaction costs come into play, and this portfolio requires active management with options to sustain constant vega exposure. Nonetheless, as we will see, these findings lay a robust foundation for comprehending how to navigate seasonal implied volatility trading.


2. Potential Reasons For BTC IV Seasonality 


At this stage, we understand that BTC IV changes tend to be positive during US trading hours compared to negative overnight IV returns. A look at several months of Paradigm RFQ block trade data on Deribit reveals that the majority of cumulative buy and sell volume tends to concentrate during US trading hours between 6am to 6pm EST. The surge in aggregated trading activity during US hours implies that traders within this time zone are the primary movers of the crypto volatility market, given the heightened liquidity during this period.

We can further investigate intraday high and low ranges using hourly data for each respective time segment. Below, a box and whisker plot displays hourly BTC high and low spot percentage movements across various time buckets. Similar to our earlier analysis, notice how the buckets between 6am to 6pm EST consistently exhibit the highest overall volatility, coinciding with our initial findings of IV being higher during US hours.

Lastly, we can compute the realized volatility (RV) of BTC using different hourly close times such as 12am, 6am, 12pm, and 6pm EST. While this data provides less of a clear signal, it’s worth noting that RV calculated at 12pm EST consistently tends to be higher than at other times of the day. This aligns with expectations, as this time falls squarely within the heart of the US trading day when volatility is naturally expected to be elevated.

Furthermore, in lieu of solely relying on daily close-close volatility, an alternative method to illustrate this phenomenon involves analyzing the high/low price ratio within each time segment. In accordance with our earlier findings, this ratio consistently demonstrates increased volatility during the 6am to 6pm EST time window. This correlation aligns logically, as periods characterized by higher realized volatility tend to coincide with heightened implied volatility during the same timeframe.

While understanding the root cause of intraday seasonality in IV remains a complex challenge, the figures presented above represent an attempt to quantify option trading data to bolster our thesis. In the following section, we will delve into the limitations of trading IV seasonality and outline practical strategies for implementation.


  • Limitations and Practical Implementation of Strategy:


The core premise of this signal is rudimentary: buy volatility during US market hours and sell it during Asian hours. However, translating this into practice can be challenging due to several factors:

  • Transaction Costs: Executing this strategy flawlessly would require daily rebalancing (shifting between net long and net short vega positions). This approach isn’t practical and will result in substantial transaction costs from crossing the bid-ask spread.
  • Assuming Constant Maturity ATM + Vega Exposure: Maintaining consistent exposure to ATM 30-day strikes alongside constant vega is difficult with options. As mentioned earlier, this would necessitate significant turnover of options, especially during volatile markets when the underlying ATM option frequently changes.


Both of these limitations are heavily influenced by the bid-ask spread. Consequently, we examine the distribution of the bid-ask spread during different times of the day to identify optimal trading windows. This analysis involves studying top-of-the-book bid-ask spreads for options closest to ATM and with a 30-day maturity, tracked on an hourly basis. Interestingly, liquidity appears to be optimal between 6am to 6pm EST, as indicated by the shape of the distribution and the median vertical lines (notably, the median spread for US hours is lower than during Asian hours).

Another approach to visualizing these results is by focusing solely on the median of the bid-ask spread across each time cluster. This reveals that the spread is at its narrowest during US hours, underscoring the higher liquidity during this period.

As demonstrated, the median cost of crossing the bid-ask spread is slightly over 1 vol point. In contrast, the theoretical P&L of the volatility strategy, which yielded around 175 vol points over six months (100 vols short overnight + 75 vols long daytime), amounts to just under 1 vol point profit per day. Based on these back-of-the-envelope calculations, implementing this strategy in isolation would likely erode profits mainly due to turnover and transaction costs. Nevertheless, there are alternative ways to harness this signal within a trading strategy:


  • Market-Making Overlay: If a market-maker possesses a trading signal or hedging requirement demanding the purchase or sale of volatility over extended timeframes, it’s prudent to synchronize these trading activities with the observed seasonality. In simpler terms, if a trader finds the need to buy volatility, it would be advisable to wait until the end of the Asia session, capitalizing on the volatility upswing typically witnessed during US hours.
  • Optimized Trading Strategy: Traders can refine the vanilla strategy of buying vol in the day and selling overnight by incorporating filters to reduce the number of trades taken. For instance, introducing trend-following on the underlying IV time-series can help filter out lower-quality trades, thereby reducing trading costs and enhancing the strategy’s likelihood of success.


Our investigation into BTC implied volatility seasonality lays the groundwork for the formulation and implementation of more nuanced and effective trading strategies in the crypto options market. While these seasonality results have proven reliable over the past six months, echoing the famous Anchorman quote, “60% of the time, it works every time,” we maintain a sense of humility in the face of the crypto market’s constant evolution. We acknowledge that market dynamics can change rapidly, emphasizing the uncertainties inherent in this realm. With this newfound understanding of when to embrace volatility and when to exercise caution, traders can approach the crypto market with confidence, equipped with a dependable foundation to navigate its ever-shifting landscape and identify opportunities with clarity.