Grayscale Trends are your friends – Managing Bitcoin’s volatility with momentum signals
Grayscale Trends - Managing Bitcoin's volatility with momentum signals
Some investors may hold an optimistic view on the long-term potential of Bitcoin, but are unsure how to evaluate this novel asset and wish to mitigate volatility. In these cases, traditional “momentum” signals can be used in a risk management framework to provide guidance on when to increase or decrease Bitcoin allocations.
The price of Bitcoin has historically shown clear “momentum” evidence – meaning that gains tend to follow gains, and losses tend to follow losses.
The Grayscale research team uses various simple trading rules to demonstrate how trend-following strategies have been applied in the past as a tool to help portfolios capture Bitcoin price appreciation while reducing the risk of steep declines.
Evidence of price “momentum” can be seen in almost all asset classes, where returns tend to trend upwards and losses tend to trend downwards, both at the individual security level and at the overall index level (1). In fact, a subset of the alternative industry, commodity trading advisors (CTAs) or managed futures funds, aim to generate uncorrelated returns primarily using trend-following strategies. The reasons for these price patterns are subject to debate, but researchers often associate these patterns with behavioral factors, including investors’ insufficient reaction to changes in asset fundamentals, and the “herding effect” of investors that leads to price declines (i.e. the tendency to chase previous winners) ultimately deviating from fair value.
The momentum effect is particularly pronounced in the digital asset market (2). As shown in Chart 1, buying into Bitcoin when it has risen in the previous month brings high returns, while buying when Bitcoin has declined in the previous month does not bring high returns. Other assets with significant momentum patterns at the index level include commodities and baskets of the US dollar against multiple currencies.
- Glassnode Crypto market trading volume reaches historic low, BTC is...
- Is this year’s rise in BTC due to the pump of $3.5 billion by...
- Peter, the Market Director of New Fire Technology, stated that New ...
While we believe the best strategy is for investors to hold Bitcoin for the long term – and generally avoid adopting technical analysis strategies – we explore momentum signals as a tool for investors to manage volatility. For those who are inclined to trade more actively for risk management purposes, this approach can provide guidance on when to increase or decrease cryptocurrency allocations. Using various simple trading rules, we demonstrate how trend-following strategies have historically helped portfolios capture Bitcoin price appreciation while reducing volatility and/or mitigating the risk of steep drawdowns.
Chart 1: Bitcoin’s price shows clear momentum
Trend-following strategies use past price changes to indicate appropriate points to enter or exit investment positions, rather than valuation indicators or other fundamentals. (3) The purpose of trend-following is not to predict specific price levels; instead, these methods jump on the trend once it is established and stay with the trend until price patterns indicate a reversal. The goal is to participate in market upswings while preserving capital during long drawdown periods.
The simplest trend or momentum indicator is the moving average line: the simple average of asset prices over a previous period (e.g. 50 days). The logic behind the moving average line (“MAVG”) is simply to create a smooth line that makes long-term trends easier to identify. Given that assets often exhibit “noise” in the form of short-term fluctuations, it can be challenging to discern whether short-term price movements are part of a larger, meaningful trend or simply random fluctuations. By averaging prices over a longer period, the moving average line strategy helps reduce this noise and produces a smooth line that can identify long-term trends.
A basic moving average strategy for Bitcoin would involve monitoring the price of Bitcoin relative to the average price over the past 50 days (Chart 2). When the price of Bitcoin crosses above the 50-day (50d) moving average line, this is interpreted as a bullish signal and a moment to initiate long positions. Conversely, when the price of Bitcoin falls below the 50-day moving average line, this is seen as a bearish signal and a point to return to cash. (4) While trend-following funds typically hold both long and short positions, here we are only considering a strategy of returning to cash when a bearish signal is present, rather than shorting.
Chart 2: The 50-day moving average line is a common momentum indicator
This 50-day moving average strategy, although simple, has proven to be effective. From 2012 to the present, compared to the traditional buy-and-hold strategy, this momentum-based strategy not only brings higher annualized returns, but also reduces volatility (see appendix for details). The improvement in performance is largely attributed to the strategy’s ability to mitigate losses during significant price declines, such as in the fourth quarter of 2021 and the second quarter of 2022 (Chart 3). The 50-day moving average strategy also performs well in terms of the Sharpe ratio, with a score of 1.9 for the entire period from January 2012 to July 2023, compared to a score of 1.3 for buy-and-hold. It is worth noting that the simple moving average strategy is not particularly sensitive to the choice of “lookback window,” which is the period over which the moving average is calculated.
Chart 3: Turning to cash when the price falls below the 50-day moving average line may reduce drawdowns
The moving average crossover strategy based on the simple moving average strategy uses two moving average lines – typically a short-term moving average and a long-term moving average. “Crossover” refers to the point at which the short-term moving average crosses above or below the long-term moving average. For example, consider a strategy that tracks two moving average lines: a short-term 20-day moving average and a long-term 100-day moving average (Chart 4). When the short-term (20-day) moving average crosses above the long-term (100-day) moving average, we define this event as a “bullish crossover.” This is interpreted as a favorable signal for long positions. Conversely, when the short-term moving average falls below the long-term average, we have a “bearish crossover.” This is usually seen as an unfavorable signal, indicating that it may be time to return to cash.
Figure 4: Tracking Two Moving Averages with Cross Strategy
From 2012 to present, the performance of the 20-day/100-day moving average cross strategy has been better than buying and holding Bitcoin. The annualized return of this strategy is 116%, with a Sharpe ratio of 1.7, while the annualized return of the buy and hold strategy is 110% with a Sharpe ratio of 1.3. The results of backtesting the cross strategy vary slightly in different periods. For example, during the period from 2020 to 2023, these strategies generated better risk-adjusted returns compared to holding Bitcoin, but the total return was lower (Figure 5). In some periods, the reduction in risk came at the cost of lower returns.
Figure 5: The cross strategy had lower total return but higher risk-adjusted return in the previous cryptocurrency market cycle
Compared to the basic moving average strategy, the results of the moving average crossover strategy are more sensitive to the choice of the backtesting window. To illustrate this, we conducted backtesting on the moving average crossover strategy using different combinations of backtesting windows (Figure 6). The results varied significantly depending on the selected backtesting period; some combinations produced excellent Sharpe ratios, indicating better risk-adjusted performance, while others produced less satisfactory results. The highest Sharpe ratio was achieved when the short-term moving average was set to around 10-30 days. It should be emphasized that the results are based on historical data and the price patterns of Bitcoin may change over time. In addition, strategies with relatively shorter moving averages will generate more trading signals, resulting in higher transaction costs for investors.
Figure 6: The risk-adjusted return of the cross strategy is maximized when the short-term moving average is around 10-30 days
Source: Grayscale Investments Finally, we tested a strategy based on exponential moving averages (6). This approach is similar to the basic moving average strategy mentioned above, but assigns higher weights to recent price points in the tracking average. In this analysis, we used an exponential moving average based on the past 150 days of price data (Figure 7).
Figure 7: Exponential moving averages focus more on recent values
Like the basic moving average strategy and the crossover strategy, the exponential moving average method generated good returns in backtesting. Over the entire sample period from 2012 to 2023, this strategy (alternating between Bitcoin and cash) produced an annualized total return of 126% with a Sharpe ratio of 1.9.
Figure 8: The hypothetical exponential moving average (MAVG) strategy captures the upside potential of Bitcoin while reducing drawdowns.
There are some considerations to keep in mind with our analysis. Most importantly, backtesting performance depends on historical price patterns, which may change in the future. Additionally, all hypothetical returns reported here do not account for transaction costs, meaning that returns for strategies involving more trades may be overstated.
It’s worth repeating: this analysis is purely based on price movements and ignores fundamental factors that can significantly impact asset prices. Ultimately, fundamentals are crucial in determining long-term value. Following mechanical trading rules based solely on historical price data may expose investors to other risks.
Risk Management Tools
Bitcoin has provided exceptional total returns in its brief history, despite experiencing several significant drawdowns along the way. We believe that Bitcoin and the entire cryptocurrency asset class will continue to offer attractive returns in the coming years, and the best way to capture its upside potential is to buy and hold Bitcoin. However, some investors may be uncertain about how to evaluate the asset and cautious about its volatility. Investors seeking to capture Bitcoin price appreciation while managing volatility and/or drawdown risk may consider applying momentum signals and trend following. We have demonstrated how these tools and strategies can provide guidance on when to increase or decrease Bitcoin allocation. Historically, when applied correctly, they have improved risk-adjusted returns for both long and short investment portfolios. Therefore, incorporating momentum signals as part of a cryptocurrency allocation risk management framework may enhance portfolio performance over time.
Appendix: Strategy Returns
For example, see Asness, Moskowitz, and Pedersen’s “Value and Momentum Everywhere”. The Journal of Finance, 2013; and Moskowitz, Ooi, and Pedersen’s “Time Series Momentum”. The Journal of Financial Economics, 2012.
For example, see Liu and Tsyvinski’s “Risks and Returns of Cryptocurrencies”. Financial Research Review, 2021; and Harvey et al.’s “Cryptocurrency Investor’s Guide”. Journal of Portfolio Management, 2022.
All strategy results are for the period from January 1, 2012, to July 31, 2023.
For the cash return proxy, we use the Bloomberg 1-3 Month Treasury Bill Index. This index represents the returns investors would have received from holding short-term government securities.
The Sharpe ratio is a commonly used measure of risk-adjusted performance, calculated as the annualized excess return (relative to cash) divided by its annualized volatility.
An exponential moving average places more emphasis on recent price observations; the weights for earlier observations decay exponentially within the lookback window.