- Building a diversified portfolio has gotten harder, due to lower bond returns, narrowly concentrated gains in equities, higher correlations across assets, and macro risks.
- At Grayscale, we believe that the crypto asset class can be a useful ingredient for building an effective portfolio. Bitcoin and other digital assets have historically offered high returns (for high risk) and a low correlation to public equities. This means they have the potential to contribute to both portfolio returns and portfolio diversification.
- Crypto is a volatile asset class, so a little goes a long way. Our analysis suggests that an allocation to crypto of approximately 5% could help maximize risk-adjusted returns for investors who would otherwise hold a balanced portfolio of stocks and bonds, although allocating to crypto will also tend to increase portfolio risk.
- Investors should consider their own circumstances and financial goals before investing in crypto. The asset class should be considered high risk, and may not be suitable for investors with near-term capital needs and/or high risk aversion.
When putting together a portfolio of financial assets, the average investor is usually offered some standard advice: own a diversified mix of stocks and bonds, with typically more stocks early on and more bonds as when approaching retirement, use tax-advantaged accounts when possible, avoid trying to time the market, and look for the best investment product in each category. If stocks and bonds both produce healthy and uncorrelated returns, this advice should lead to good results.
But today’s investors face a new set of challenges. For one thing, the long decline in inflation that began around 1980 is over. In this environment, bonds may struggle to produce returns comparable to the last forty years. Moreover, many assets are now more highly correlated, so investors typically lose out on some of the diversification benefits from owning them together in a portfolio. Large institutional investors have tried to address these challenges by moving into private asset markets (e.g. private equity, real estate, venture capital) or by deploying leverage (i.e. borrowing to enhance returns), but these options are not typically available to the average saver.
At Grayscale, we believe that the crypto asset class can be one way to address these challenges when thinking about a modern, future-friendly financial portfolio. Bitcoin and other digital assets are high-risk/high return-potential investments, accessible to anyone in public markets, often with a low correlation to stocks. Grayscale Research believes including a moderate allocation to the crypto asset class in a diversified portfolio may help improve both total returns and risk-adjusted returns, while also contributing to portfolio risk. Every investor has unique goals and should consider their own circumstances, but an analysis by Grayscale Research suggests a crypto allocation of approximately 5% may help to optimize a typical portfolio’s risk-adjusted returns.
Five Challenges for the Modern Investor
For the last generation of US-based investors, holding a balanced portfolio of domestic assets—typically a 60/40 mix of stocks and bonds—worked well. For example, in the forty years from 1980 to 2019 (i.e. from the start of the disinflation period until the covid pandemic), a 60/40 portfolio of US stocks and government bonds produced an annualized return of 8.6%—more than double the return on cash. At Grayscale Research, we see several reasons why the current generation of investors may find it harder to find high returns and diversification strategies in traditional markets.
- End of the bond bull market. In 1979 the Federal Reserve, led by Paul Volcker, decided to get serious about bringing down inflation. These efforts succeeded: inflation peaked in 1980 and longer-term Treasury yields peaked the following year (Exhibit 1). Over the subsequent decades both inflation and bond yields steadily declined, hugely flattering bond returns. In our view, we are now in a different regime: inflation is higher and more volatile, and the Federal Reserve has explicitly adopted a policy that will sometimes aim for an inflation rate above its target. Rising inflation can be detrimental to fixed income returns, and since 2019, buying US Treasuries has lost investors about 1% annually. Bonds will remain an important part of many investors’ portfolios, but the long bull market that started in the early 1980s seems over.
Exhibit 1: Long secular decline in bond yields is over
- Increasingly narrow equity gains. Although bonds have struggled recently, stocks have continued to produce solid returns. The problem is that these gains are becoming extremely narrow. Across major asset classes, only US stocks have produced compelling returns since 2010, the period since the 2008-09 financial crisis (Exhibit 2). Moreover, within US equities markets, only a small number of stocks are still performing. Last year, for example, the “Magnificent 7” mega-cap tech stocks (AAPL, MSFT, AMZN, NVDA, GOOGL, META, and TSLA) were up 107%, while the remaining 493 stocks in the S&P 500 were up just 5%. Investors in US market cap-weighted indexes are now highly exposed to the outlook for these seven companies.
Exhibit 2: US stocks have been the only game in town
- Higher correlations. By holding a basket of low-correlation assets, an investor can potentially achieve better risk-adjusted returns than by holding any of the individual assets. However, correlations across assets have increased, so the diversification benefits for investors are getting smaller: stocks are more correlated with bonds, and international stocks are more correlated with US stocks (Exhibit 3). Building a portfolio with attractive risk-adjusted returns gets harder as cross-asset correlations rise.
Exhibit 3: Rising correlations mean fewer diversification benefits
- Shrinking public markets. Although the US economy has grown over time, the number of public companies has not. According to the World Federation of Exchanges, the number of public companies in the US peaked in 1997 and has mostly fallen since that time (Exhibit 4). Initial public offerings (IPOs) can be a way for investors to gain exposure to innovative companies with relatively high return potential (and sometimes lower correlations to other equities). But, for a variety of reasons, more companies are avoiding going public or delisting (i.e. being acquired and going private). Although institutional investors may still be able to access these opportunities in private markets, most individual investors cannot.
Exhibit 4: Innovative companies favoring private markets
- Elevated macro risks. Economists refer to the period from the mids-1980s to the 2008-09 financial crisis as the Great Moderation: these were the halcyon days of strong GDP growth and mild recessions, low and stable inflation, increasing openness to free trade and capital flows, and geopolitical dominance by the United States. Needless to say, these macro conditions are favorable for investors. But unfortunately, in our view, the coming years may bring a less favorable mix of economic and political outcomes. Today’s investors may have to navigate higher and more volatile inflation, large government debt burdens, as well as higher tariffs and frictions on international capital movements, each of which could affect portfolio returns.
Crypto Can be a Useful Ingredient in a Modern Portfolio
Public blockchains are a groundbreaking technology that we expect will eventually transform the global financial system. From an investing standpoint, what savers will tend to consider are the risk and return characteristics of blockchain-based tokens—the components of this new asset class. Although there are many different tokens, each with their own use cases, as a whole their return characteristics suggest that investing in the crypto asset class may help investors overcome some of today’s modern portfolio construction challenges.
In traditional asset markets, investors face a well-known trade-off between risk and return (Exhibit 5). For example, fixed income assets generally offer lower returns for lower risk, while equity markets offer higher returns for higher risk. In an effort to help improve the risk/return tradeoff, in recent years many institutional investors have allocated to private markets (e.g. private equity, real estate, venture capital), or employed strategies that incorporate borrowing/leverage to enhance returns (e.g. risk parity). These approaches have often been effective, but they are not always available to individual investors.
Exhibit 5: Traditional assets offer a familiar tradeoff between risk and return
From a risk/return perspective, the crypto asset class expands the opportunity set available to individual investors (Exhibit 6). For example, Bitcoin has produced annualized returns of about 50% with annualized volatility of about 75%; Ethereum is even further out on the risk/return spectrum. Among traditional assets, venture capital investments offer the highest risk/highest potential reward, historically. These investments on average have produced annualized returns of about 20% with annualized volatility of about 30%. Crypto assets broaden the spectrum of risk and return available to investors in public markets. In other words, for investors willing to take more risk, the crypto asset class can potentially deliver higher total returns, in the form of liquid instruments that are widely available on exchanges.
Exhibit 6: Crypto expands the risk/return spectrum in public markets
In addition, Bitcoin and other crypto assets have delivered returns with a relatively low correlation to public equities (Exhibit 7). If Bitcoin, for example, had high returns but a high correlation to stocks, incorporating it into a portfolio might improve total returns but not risk-adjusted returns. The fact that it has produced both high returns and low correlations means that Bitcoin can benefit a portfolio through both higher returns and better diversification.
Exhibit 7: Bitcoin also brings diversification benefits
A Little Goes a Long Way
When building a portfolio, investors will typically consider both total returns—whether they will be able to achieve certain financial goals in the future—as well as risk-adjusted returns—whether their returns are offering adequate compensation for risk. Because crypto is a relatively high-risk/high-return-potential asset class, adding it to a portfolio will usually improve expected total return (as well as portfolio risk). We therefore consider the amount that, under certain assumptions, results in the highest expected risk-adjusted return (although adding any allocation to crypto may result in greater portfolio volatility).
In particular, Grayscale Research considered a hypothetical investor that holds a classic 60/40 portfolio of stocks and bonds, and simulated their expected returns using Monte Carlo methods (see the technical appendix for details). We then considered how adding Bitcoin to this portfolio—subtracting proportionally from the 60/40 mix of stocks and bonds—changes its Sharpe Ratio, a measure of risk-adjusted returns. The portfolio with the highest Sharpe Ratio can be considered optimal from a risk/return standpoint. Because of its longer history we used Bitcoin as the representative digital asset in this exercise, rather than other tokens.
Exhibit 8 shows these results for our baseline simulations. As Bitcoin is added to the classic 60/40 portfolio in small increments, the expected Sharpe Ratio initially rises. The reason is that, although Bitcoin is a volatile asset, it offers a high return and a low correlation to traditional assets. The Sharpe Ratio continues to rise until Bitcoin reaches approximately a 5% share of the total portfolio, then begins to level off. After that point, increasing the Bitcoin allocation is no longer expected to improve risk-adjusted returns.
Exhibit 8: Hypothetical risk-adjusted return rises as Bitcoin added to 60/40 portfolio
Naturally, this is just one simulation under a specific set of assumptions, and there is no guarantee that future returns will mirror those of the past. To stress test our result, Grayscale Research varied the expected returns, volatilities, and correlations of each of the three assets (see technical appendix for details). Each of these scenarios results in slight differences in the amount of Bitcoin that results in the highest Sharpe Ratio portfolio, and investors should consider that uncertainty before allocating to the asset class. In general, an optimal portfolio would hold more Bitcoin if it offered higher returns, lower volatility, a lower correlation to traditional assets, or a mix of these attributes.
Across our baseline simulation and stress tests, our hypothetical simulations suggest that allocating approximately 5% of a portfolio to Bitcoin results in the highest risk-adjusted returns on average, albeit with higher portfolio volatility, for investors who would otherwise hold a classic mix of stocks and bonds. Crypto is a volatile asset class, so a little goes a long way.
Buy and “Hodl”
It is important to stress that investing in digital assets may not be suitable for everyone. In this analysis we considered a representative investor holding a classic 60/40 portfolio. However, in practice there are many types of portfolios serving different financial needs. For example, some investors hold portfolios of low-volatility assets because their capital is earmarked for upcoming expenses (e.g. home purchase or college tuition). Crypto is a high volatility asset class which may produce strong returns over time, but which can also lose significant value over the short-term. Additionally, some investors favor income-producing assets like fixed income securities or dividend-paying stocks. Although some crypto assets generate income, in most cases the earnings will be low compared to the asset’s volatility—crypto is an asset class primarily held for capital appreciation.
While there are some exceptions, Grayscale Research analysis suggests that a traditional balanced portfolio may achieve higher risk-adjusted returns with a moderate allocation to crypto—perhaps ~5% of total financial assets. Because crypto is a high-risk/high-return-potential asset class with a low correlation to stocks, crypto assets can potentially help investors overcome some of the portfolio construction challenges they face today. Allocating crypto does not change other conventional thinking about portfolio construction, including to reduce portfolio volatility when approaching retirement, to use tax-advantaged accounts when possible, and to avoid trying to time the market (i.e. buy and “hodl”).
To determine the appropriate share of Bitcoin in a portfolio we simulated expected returns using Monte Carlo methods. Specifically, for each incremental addition of Bitcoin to a 60/40 portfolio, ranging from 0% to 25%, we simulated 1,000 random portfolios over 60 month periods (i.e. 26,000 five-year horizon simulations). We then took an average of the return, volatility, and Sharpe Ratio for each Bitcoin share of the portfolio (e.g. the average Sharpe Ratio when Bitcoin’s share of the portfolio was 0%, 1%, 2%, and so on).
A critical element of this analysis was considering the implications of crypto’s correlation with other asset classes—as this determines its diversification benefit in a portfolio context. Simulating correlated random variables involves more advanced statistical techniques. To adjust the correlations between Treasury bonds, the S&P 500, and Bitcoin, we employed the Iman-Conover method. This method is useful for its ability to alter the correlation structure of a set of variables while preserving their individual marginal distributions.
The key steps involved in this method are:
- Rank Transformation: Each variable's values are replaced with their ranks, transforming the data into a uniform distribution.
- Normalization and Conversion to Z-Scores: These ranks are normalized and then converted into z-scores, aligning them with a standard normal distribution.
- Correlation Adjustment: We then adjust these z-scores using the Cholesky decomposition of our target correlation matrix, aligning the data with our desired correlation structure.
- Transformation Back to Original Scale: Finally, the adjusted z-scores are transformed back to the original scale of the data, ensuring that the original distribution characteristics of each variable are maintained.
This Iman-Conover is helpful for our analysis as it allows for a realistic simulation of how different assets, especially Bitcoin, interact within a portfolio under various correlation scenarios.
For our baseline statistics, we selected Bitcoin returns data post-2014. This choice is based on the observation that around 2014, the distribution of Bitcoin returns became more stable and approximated a normal distribution (Exhibit 9). For stocks and bonds, the baseline distributions were measured since 1980.
Exhibit 9: Bitcoin’s return distribution more stable since 2014
In simulating the return distributions for our analysis, we assumed normal distributions for the returns of all assets, including Bitcoin. This assumption is a standard approach in financial modeling, providing a balance between simplicity and realism. However, we acknowledge that real-world returns, particularly for assets like Bitcoin, may not adhere strictly to a normal distribution. For Bitcoin, historical returns (especially using data prior to 2014) demonstrate evidence of positive skewness (Exhibit 10). This is a rare and attractive property for a pro-risk asset class (i.e. most pro-risk asset classes have negative skewness). If we were to incorporate Bitcoin’s positive skewness to the analysis, an optimal portfolio would hold an allocation larger than 5%, all else being equal.
Exhibit 10: Bitcoin’s historical returns show positive skewness
As discussed in the main text, we stress tested our results with a variety of alternative scenarios, reflecting the uncertainty of the future return distributions to stocks, bonds, and Bitcoin, as well as these assets’ correlations with each other (Exhibit 11). In general our stress testing supported the result that a roughly 5% allocation to crypto in a portfolio may be appropriate on average.
Exhibit 11: Our stress tests suggest 5% allocation to crypto is optimal on average
 Returns exclude fees and are based on index returns; you cannot invest directly in an index; asset returns based on the S&P 500 price return index and the Bloomberg-Barclays US Treasury total return index; annual data from 1980 through 2019; cash return based on the S&P US Treasury Bill total return index from 1990; prior years estimated from Federal Reserve data on 3m Treasury bill yields.
 Treasury coupon yields in excess of cash added 1.9% annually to Treasury returns over this period, and the secular decline in yields added another 1% annually.
 Calculated by Grayscale Research based on the Bloomberg-Barclays US Treasury total return index.
 Calculated by Grayscale Research using Bloomberg data, as of December 31, 2023. Grayscale research subtracted the contribution of the return of the seven largest stocks from the total index return.
 For more background see, for example, “Global Stock Market Linkages Reduce Potential for Diversification”, Karen Lewis, Federal Reserve Bank of Dallas Economic Letter, February 2012.
 For more background see, for example, “The US Listing Gap”, Craig Doidge, G Andrew Karolyi, and Rene Stulz, NBER Working Paper Series, May 2015.
 Returns in Exhibit 5 and 6 based on indexes; you cannot invest directly in an index; indexes include: S&P 500, Nasdaq 100, Russell 2000, MSCI ACWI, MSCI World, MSCI EM, Bloomberg-Barclays Global Aggregate, Bloomberg-Barclays US Aggregate, Bloomberg-Barclays US Corporate, Bloomberg-Barclays US High Yield, Bloomberg-Barclays Euro Aggregate, Bloomberg-Barclays Japan Aggregate, Bloomberg-Barclays EM US Aggregate, JP Morgan GBI-EM Global Diversified, Deutsche Bank Cross Asset CTA Trend, Deutsche Bank EM FX Equal Weight, S&P/GSCI, GSAM FX Carry, FTSE Venture Capital, Advanced Research Risk Parity, Preqin Capital Private Equity, Preqin Capital Real Estate, and Hedge Fund Research 400.
 Source: Grayscale Investments based on Coin Metrics data; Bitcoin returns from January 2014 through December 2023; Ether returns from January 2019 through December 2023. For best assets, returns and volatilities in their very early history may overstate what investors could expect prospectively. For more Bitcoin specifically, see the appendix for more details on the asset’s historical return distribution.
 Based on the FTSE Venture Capital Index from January 1996 through December 2023. Returns do not include fees. Indexes are unmanaged and it is not possible to invest directly in an index.
 We assumed a return to cash of zero in our simulations.
Investments in digital assets are speculative investments that involve high degrees of risk, including a partial or total loss of invested funds. Investments in digital assets are not suitable for any investor that cannot afford loss of the entire investment.
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HYPOTHETICAL SIMULATED PERFORMANCE RESULTS HAVE CERTAIN INHERENT LIMITATIONS. Unlike an actual performance record, simulated results do not represent actual trading or the costs of managing the portfolio. Also, since the trades have not actually been executed, the results may have under or over compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general
are also subject to the fact that they are designed with the benefit of hindsight. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS.
The hypothetical simulated performance results are based on a model that uses inputs that are based on assumptions about a variety of conditions and events and provides hypothetical not actual results. As with all mathematical models, results may vary significantly depending upon the value of the inputs given, so that a relatively minor modification of any assumption may have a significant impact on the result. Among other things, the hypothetical simulated performance calculations do not take into account all aspects of the applicable asset’s characteristics under certain conditions, including characteristics that can have a significant impact on the results.
Further, in evaluating the hypothetical simulated performance results herein, each prospective investor should understand that not all of the hypothetical assumptions used in the model are described herein, and conditions and events that are not accounted for by the model may have a significant adverse effect on the performance of the assets described herein. Prospective investors should consider whether the behavior of these assets should be tested based on different and/or additional assumptions from those included in the information herein.
The S&P 500 Index is a market-capitalization-weighted index that measures the performance of 500 of the largest publicly traded companies in the United States. The Nasdaq 100 Index is a stock index of the 100 largest companies by modified market capitalization trading on Nasdaq exchanges. The Russell 2000 Index is composed of the smallest 2000 companies in the Russell 3000 Index, representing approximately 8% of the Russell 3000 total market capitalization. The MSCI ACWI captures large and mid cap representation across 23 Developed Markets (DM) and 24 Emerging Markets (EM) countries. The MSCI Emerging Markets Index is designed to measure the financial performance of companies in fast-growing economies around the world and tracks mid-cap and large-cap stocks in 25 countries.The Bloomberg-Barclays Global Aggregate Index is a market-weighted index of global government, government-related agencies, corporate and securitized fixed-income investments.The S&P Goldman Sachs Commodity Index is a composite index of commodity sector returns representing an unleveraged, long-only investment in commodity futures that is broadly diversified across the spectrum of commodities. Indexes are unmanaged and it is impossible to invest in an index.The Advanced Research Risk Parity Index tracks the performance of a multi-asset strategy that balances risk equivalently among four broad asset classes: global equities, commodities, U.S. Treasury Inflation-Protected Securities (TIPS) and U.S. Treasury Futures. With 2,946 constituents, the index covers approximately 85% of the global investable equity opportunity set. Indexes are unmanaged and it is impossible to invest in an index. The Hedge Fund Research 400 index is a global, equally-weighted index of hedge funds that are open to new investment by US investors. The Preqin Capital Real Estate Index measures the return earned on invested capital in private real estate funds. The Preqin Capital Private Equity Index measures the return earned on invested capital in private equity funds. The FTSE Venture Index measures the value of the US-based venture capital private company universe. The GSAM FX Carry Index tracks the equally-weighted returns of G10 and EM FX carry strategies based on ranked implied yields vs the US Dollar. The Deutsche Bank EM FX Equal Weight Index measures the total return of 21 EM currencies vs the US Dollar. Deutsche Bank Cross Asset CTA Trend Index measures the FX-hedged excess return of Commodity Trading Advisor (CTA) strategies. The JP Morgan GBI-EM Global Diversified Index measures the total return of local currency government bonds in emerging markets. The Bloomberg-Barclays EM US Aggregate Index measures the return of US Dollar denominated government bonds issued by emerging markets. The Bloomberg-Barclays Japan Aggregate Index measures the return of investment grade fixed income securities in the Japanese market. The Bloomberg-Barclays Euro Aggregate Index measures the return of investment grade fixed income securities in the Euro Area.The Bloomberg-Barclays US High Yield Index measures the return of non-investment grade corporate bonds.The Bloomberg-Barclays US Corporate Index measures the return of investment grade corporate bonds. The Bloomberg-Barclays US Aggregate Index measures the return of investment grade fixed income securities in the US market. Indexes are unmanaged and it is impossible to invest in an index.
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Certain of the statements contained herein may be statements of future expectations and other forward-looking statements that are based on Grayscale’s views and assumptions and involve known and unknown risks and uncertainties that could cause actual results, performance, or events to differ materially from those expressed or implied in such statements. In addition to statements that are forward-looking by reason of context, the words “may, will, should, could, can, expects, plans, intends, anticipates, believes, estimates, predicts, potential, projected, or continue” and similar expressions identify forward-looking statements. Grayscale assumes no obligation to update any forward-looking statements contained herein and you should not place undue reliance on such statements, which speak only as of the date hereof. Although Grayscale has taken reasonable care to ensure that the information contained herein is accurate, no representation or warranty (including liability towards third parties), expressed or implied, is made by Grayscale as to its accuracy, reliability, or completeness. You should not make any investment decisions based on these estimates and forward-looking statements.
There is no guarantee that the market conditions during the past period will be present in the future. Rather, it is most likely that the future market conditions will differ significantly from those of this past period, which could have a materially adverse impact on future returns. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS. We selected the timeframe for our analysis because we believe it broadly constitutes the most complete historical dataset for the digital assets that we have chosen to analyze.