Grayscale Trends are Your Friends – Managing Bitcoin Volatility with Momentum Signals

Grayscale Trends - Managing Bitcoin Volatility with Momentum Signals

Original Title: The Trend is Your Friend: Managing Bitcoin’s Volatility with Momentum Signals

Original Authors: Zach LianGuaindl, Michael Zhao

Original Source: GRAYSCALE

Translation: Lynn, MarsBit

• Will MicroStrategy stop buying Bitcoin?
• Crypto is building a rule-based order and gradually allowing Old Money and retail investors to enter the market.
• Crypto+AI The Cryptocurrency Narrative of the Next Bull Market

• Some investors may hold an optimistic attitude towards the long-term potential of Bitcoin, but are uncertain about how to evaluate this novel asset and hope to mitigate its 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.

• Bitcoin’s price has historically shown clear “momentum” evidence, meaning gains tend to follow gains, and losses tend to follow losses.

• The Grayscale research team demonstrates how trend-following strategies can be applied as a tool to help portfolios capture Bitcoin price appreciation while reducing the risk of significant declines.

Evidence of price “momentum” can be seen in almost all asset classes, where gains tend to trend upward and losses tend to trend downward, both at the individual security level and at the overall index level (1). In fact, part of the alternative industry, such as commodity trading advisors (CTAs) or managed futures funds, aims to generate uncorrelated returns primarily using trend-following strategies. The reasons for these price patterns are controversial, but researchers often associate these patterns with behavioral factors, including investors’ inadequate response to changes in asset fundamentals and the “herd effect” of investors chasing previous winners, ultimately leading to prices exceeding fair value.

The momentum effect is especially pronounced in the digital asset market (2). As shown in Chart 1, buying Bitcoin when it rose last month resulted in high returns, while buying when Bitcoin fell last month did not bring high returns. Other assets with significant momentum patterns at the index level include commodities and a basket of currencies against the US dollar.

While we believe the best strategy for investors is to hold Bitcoin for the long term – and typically avoid technical analysis strategies – we explore momentum signals as a tool for investors to manage volatility. For those who tend 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 the application of trend-following strategies in history has helped portfolios capture Bitcoin price appreciation while reducing volatility and/or mitigating the risk of significant drawdowns.

Chart 1: Bitcoin’s price shows a clear trend

Trend-following Strategy

Trend-following strategies use past price changes to indicate appropriate entry or exit points for investment allocation, 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 trends once they are established and stay on the trend until price patterns indicate a trend reversal. The goal is to participate in market upswings while preserving capital during long-term pullbacks.

The simplest trend or momentum indicator is the moving average: the simple average of asset prices over a previous period (e.g., 50 days). The logic behind the moving average (“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, distinguishing whether short-term price movements are part of larger, significant trends or just random fluctuations can be challenging. By averaging prices over a longer period, moving average strategies help reduce this noise, generating a smooth line that is expected to identify long-term trends.

The 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 breaks above the 50-day (50d) moving average, this is interpreted as a bullish signal and a time to initiate long positions. Conversely, when the Bitcoin price falls below the 50-day moving average, this is seen as a bearish signal and a point to revert to cash. (4) Although trend-following funds typically hold both long and short positions, here we only consider a strategy that returns to cash instead of going short when a bearish signal is present.

Chart 2: 50-day moving average is a common momentum indicator

While this 50-day moving average strategy is simple, its effectiveness is significant. Since 2012, 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 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 selection of the moving average strategy’s calculation period.

Chart 3: Turning to cash when the price falls below the 50-day moving average may reduce drawdowns

The Moving Average Crossover strategy based on the Simple Moving Average (SMA) strategy uses two moving averages – usually a short-term moving average and a long-term moving average. “Crossover” refers to the point where the short-term moving average crosses the long-term moving average. For example, consider a strategy that tracks two moving averages: 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 typically seen as an unfavorable signal, indicating that it may be time to move back to cash.

Chart 4: Strategy tracking two moving averages

From 2012 to the present, the performance of the 20-day/100-day moving average crossover strategy has outperformed buying and holding a Bitcoin allocation. The strategy has an annualized return of 116% and a Sharpe ratio of 1.7, while the annualized return for the buy and hold strategy is 110% with a Sharpe ratio of 1.3. The results of backtesting the crossover 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 a Bitcoin position, but with lower total returns (Chart 5). In some periods, the reduction in risk comes at the cost of lower returns.

Chart 5: In the previous cryptocurrency market cycle, the crossover strategy resulted in lower total returns but higher risk-adjusted returns

Compared to the basic moving average strategy, the results of the moving average crossover strategy are more sensitive to the choice of the backtest window. To illustrate this point, we conducted a backtest of the moving average crossover strategy using different combinations of backtest periods (Chart 6). There are significant differences in the results depending on the selected backtest period; some combinations produce excellent Sharpe ratios, indicating better risk-adjusted performance, while others produce less satisfactory results. The highest Sharpe ratio is achieved when the short-term moving average is set at 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. Additionally, strategies with relatively shorter moving averages will generate more trading signals, resulting in higher transaction costs for investors.

Chart 6: The risk-adjusted return of the crossover strategy is maximized when the short-term moving average is around 10-30 days

Source: Grayscale Investments. Finally, we tested a strategy based on the exponential moving average (EMA) (6). This approach is similar to the simple moving average (SMA) strategy described above, but gives more weight to the most recent price points in tracking the average line. In this analysis, we used an EMA based on the past 150 days of price data (Chart 7).

Chart 7: Exponential moving averages prioritize recent values.

Like the SMA and crossover strategies, the EMA method generates favorable returns in backtesting. Over the entire sample period from 2012 to 2023, this strategy (alternating between Bitcoin and cash) yielded an annualized total return of 126% and a Sharpe ratio of 1.9.

Chart 8: The hypothetical EMA strategy captures Bitcoin’s upside potential while reducing drawdowns.

There are important caveats to our analysis. Most importantly, backtesting performance relies on historical price patterns, which may change in the future. Additionally, all hypothetical returns reported here do not account for transaction costs, meaning the returns of strategies involving more frequent trading may be overstated.

It bears repeating: this analysis is purely based on price movements and ignores fundamental factors that can significantly impact the value of assets. Ultimately, fundamentals are crucial for determining long-term value. Following mechanically 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 multiple significant drawdowns. We believe Bitcoin and the entire cryptocurrency asset class will continue to offer attractive returns in the years to come, and the best way to capture its upside potential is to buy and hold Bitcoin. However, certain investors may be unsure how to assess the asset and approach its volatility with caution. Investors looking 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 allocations. When applied correctly, historically, they enhance risk-adjusted returns for both long and short investment portfolios. Therefore, incorporating momentum signals as part of a cryptocurrency allocation risk management framework may improve the overall performance of the portfolio over time.

Appendix: Strategy Returns

1. For example, please refer to “Value and Momentum Everywhere” by Asness, Moskowitz, and Pedersen. The Journal of Finance, 2013; and Moskowitz, Ooi, and Pedersen, “Time Series Momentum”. Journal of Financial Economics, 2012.

2. For example, please see Liu and Tsyvinski, “Risk and Return of Cryptocurrencies”. Review of Financial Studies, 2021; and Harvey et al., “Cryptocurrency Investor Guide”. Journal of Portfolio Management, 2022.

3. All strategy results are for the period from January 1, 2012 to July 31, 2023.

4. For the cash return proxy, we use the Bloomberg 1-3 Month Treasury Bill Index. This index represents the return investors receive from holding short-term government securities.

5. The Sharpe ratio is the annualized excess return (relative to cash) divided by its annualized volatility and is a commonly used measure of risk-adjusted performance.

6. The moving average of an index places more emphasis on recent price observations; the weights of earlier observations decay exponentially within the lookback window.

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