Bear markets are tough.
They’re especially tough for people who have invested in the wrong assets.
“Don’t put all your eggs in one basket,” they say.
We've all heard about diversification as a risk-management strategy, which means you spread capital across multiple assets.
But while there’s plenty of data showing the benefits of portfolio diversification, there’s virtually none explaining the differences between holding 2 and 20 assets.
We wanted to find out how the performance of a portfolio changes based on the number of assets in your metaphorical basket.
Our curiosity led us to investigate this topic by running 40,000 backtests to figure out how the number of assets in your portfolio impacts performance.
This study will focus on analyzing the market throughout 2022: a year-long bear market.
As a bonus, we will show you how periodic portfolio rebalancing stacks up against a simple buy-and-hold strategy at each level of diversification.
This case study was made with the help of Shrimpy's native backtesting solution. You can use Shrimpy to analyze thousands of cryptocurrencies and compare their performance against different strategies. Backtesting is the easiest way to analyze the potential performance of your portfolio without having to deploy real capital.
Backtesting is a way of figuring out which investing or trading strategies work without having to deploy real capital. You can backtest strategies by using historical price action to compare their performance. The fundamental idea behind backtesting is to understand how a strategy historically performed. That way, we can make better decisions in the future.
Keep in mind that past performance is not a guarantee of future results.
Portfolio diversification represents one of the most popular investing strategies. Diversification is a strategy that minimizes risk by spreading capital across a range of different assets. The idea is to reduce the overall risk of the portfolio by not putting all your eggs in one basket.
Although portfolio diversification has been a long-standing investing strategy, there hasn’t been significant research conducted to fully understand the impact of diversification on a crypto portfolio. While the idea of diversification reducing risk has been posed, our hypothesis is that these strategies continue to hold strong in crypto.
For example, if you invest all your money in an asset, and that asset performs poorly, you could lose a significant chunk of money. However, if you invest in a variety of assets, you can spread your risk and potentially minimize the impact of any investment's poor performance on your overall portfolio.
But how many assets should a portfolio contain to minimize risk? Is it enough to hold 5 assets, or do you need 20? At what asset number does portfolio diversification stop being efficient? Is more better, and if so, why?
We didn’t have answers to these questions, and the internet provided us with no clues. Unsatisfied, we decided to find the answers on our own.
We have analyzed the market and put together a case study that compares crypto investing performance based on the number of assets in your portfolio. We have additionally compared HODL-ing a diversified portfolio against rebalancing a diversified portfolio.
This study focuses on portfolio diversification during a bear market. We have analyzed the performance of 10 portfolios that range from 2 to 20 assets (2-asset portfolio, 4-asset portfolio, 6-asset portfolio, etc.)
We’ve also run a periodic rebalancing strategy for each portfolio group consisting of the following rebalancing frequencies:
The study also compares the performance of each rebalancing frequency for each portfolio group against a HODL strategy.
The assets in each backtest are completely randomized. We’ve run a total of 1000 backtests per rebalancing period and asset size. This means that we ran 1000 backtests for 40 different settings, amounting to a total of 40,000 backtests.
Each portfolio group consists of a certain number of assets. This case study analyzes portfolios ranging from 2 to 20 assets, amounting to 10 portfolios in total:
Each portfolio is evenly distributed. For example, a 2-asset portfolio has a 50/50 allocation. A 4-asset portfolio is divided into four even quarters of 25%, and so on.
During the rebalancing process simulated in the backtest, trades are executed in order for each portfolio group to maintain its targeted allocation.
Note that the study takes into account a trading fee of 0.1%.
Each portfolio starts with an initial balance of $5,000.
The results of this case study show the value of each portfolio by the end of the backtest period (January 1st, 2022 - December 31st, 2022.)
The asset selection process in this case study is completely randomized for the purposes of objectivity and accuracy.
Our list of assets includes all cryptocurrencies that were available on the top 10 crypto exchanges during the backtest period.
Each backtest picked random assets for each portfolio group based on the list of assets available at that time. This is done so that the focus of our analysis is placed not on the assets themselves but on the strategy.
Each backtest outputs two results. One result shows a portfolio's final value if it had been rebalanced, while the other shows a portfolio's final value if it had used the HODL strategy.
To determine how these strategies compare, we calculate the performance of the rebalancing strategy against the HODL strategy by using the following formula:
Performance = ((R - H) / H) x 100
You can read the formula as:
Our results contain graphs that show the relationship between the number of assets held in a portfolio with the median value of the portfolio by the end of the backtesting range. We have results for HODL, monthly rebalancing, weekly rebalancing, daily rebalancing, and hourly rebalancing.
Our final results (Portfolio Rebalancing vs. HODL) compare portfolio rebalancing against the HODL strategy. This section focuses not on the median value of each portfolio by the end of the backtest, but on the performance of a rebalanced portfolio compared to the same portfolio utilizing a HODL strategy.
Please note that any values displayed in this section are not relative to the starting value of a portfolio but to the same portfolio had it been HODL’ed. If a value of 5% is displayed, that means the final result for the rebalanced portfolio is 5% higher than the HODLed portfolio, and not 5% higher than the initial portfolio fund.
As mentioned previously, our case study focuses on the 2022 crypto bear market.
The backtest period lasts from January 1st, 2022, to December 31st, 2022.
Below is the weekly BTC/USDT chart, which shows how the market trended during the aforementioned time period.
Considering that the year opened at $46,230 and closed at $16,528, simply holding Bitcoin implied a net loss of 64.24%. For our portfolio size, that means ending the year with $1,788. Kindly note that the losses are far more prominent for diversified portfolios because they hold altcoins - which took far heavier losses.
Read our previous blog post to review the results of a case study with a similar setup.
We will start by showing results for all portfolio groups based on the strategy they had utilized:
These results show the final median value of each portfolio group by the end of the basktest period.
After that, we show you the combined results of all strategies and portfolio groups.
Our final results compare each portfolio rebalancing strategy with a HODL portfolio. The values here are percentages, not dollars. The values are relative to a portfolio utilizing HODL – the performance difference between a rebalanced portfolio and a HODL’ed portfolio – and not to the initial value of a portfolio.
This graph shows the results of a $5,000 portfolio using the HODL strategy after one year in a bear market. The X-axis shows the number of assets for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.
Portfolios with 8 assets or more utilizing the HODL strategy have performed considerably better than portfolios with a lower number of assets. The performance impact of diversification stops after 14-asset portfolios.
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This graph shows the results of a $5,000 portfolio that was rebalanced on a monthly basis after one year in a bear market. The X-axis shows the number of assets for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.
Portfolios rebalanced on a monthly basis show consistent but gradual increases in performance beyond 10-asset portfolios.
20-asset portfolios have performed the best, having a performance boost of 5.55% when compared to 8-asset portfolios.
This graph shows the results of a $5,000 portfolio that was rebalanced on a weekly basis after one year in a bear market. The X-axis shows the number of assets for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.
Portfolios rebalanced on a weekly basis performed the best when holding 16 assets.
There is a minimal decline in performance beyond 16-asset portfolios.
The performance curve grows rather gradually on diversified portfolios with weekly rebalancing. But when compounded, the effects of higher-count asset portfolios are rather large.
This graph shows the results of a $5,000 portfolio that was rebalanced on a daily basis after one year in a bear market. The X-axis shows the number of assets for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.
Portfolios rebalanced on a daily basis show significant improvements in performance when holding 8 assets or more.
20-asset portfolios have performed the best, showing a minimal performance increase of 3.46% compared to 8-asset portfolios.
The curve in performance increase is incredibly steep leading up to 8-asset portfolios. There is a 26.32% increase in performance between 2-asset and 8-asset portfolios.
Our results show that portfolio diversification has had the biggest impact on portfolios that used the daily rebalancing setting.
This graph shows the results of a $5,000 portfolio that was rebalanced on an hourly basis after one year in a bear market. The X-axis shows the number of assets for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.
Portfolios rebalanced on an hourly basis performed the best when holding 14 assets or more.
20-asset portfolios have performed the best, showing a minimal performance increase of 2.5% compared to 14-asset portfolios.
The impact of portfolio size is noticeably bigger on higher-frequency rebalancing. In this case, the rise in performance is far more gradual compared to daily rebalancing.
This graph shows the combined results of all the previous strategies for a $5,000 portfolio after one year in a bear market. The X-axis shows the number of assets for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.
The combined results of all rebalancing strategies, along with HODL, show that daily rebalancing has performed the best during the 2022 bear market.
Daily rebalancing performs better than any other strategy for portfolios with 8 assets or more.
The biggest difference in performance between daily rebalancing and other strategies is noticeable for 8-asset and 10-asset portfolios.
HODL proves to be by far the worst strategy after 10 assets and more.
As for portfolio size, our results show that portfolios between 14 and 20 assets had the best performance in 2022.
The trend implies that there is no noticeable improvement in performance beyond 20-asset portfolios.
The graph above compares how well each rebalancing strategy has performed against HODL at varying portfolio sizes.The X-axis shows the number of assets for each portfolio group. The Y-axis shows the performance, defined in percentages, of a rebalanced portfolio compared to a HODL portfolio at the end of the backtest period.
Daily and weekly rebalancing outperforms HODL right away.
All strategies outperform HODL beyond 8-asset portfolios – except monthly rebalancing.
Hourly rebalancing begins outperforming HODL at portfolios with 8 assets or more.
It has the best performance among all the other strategies after 16 assets and more. At its best, hourly rebalancing outperforms HODL by 7.11%
Daily rebalancing, much like the previous setting, has a steep boost in performance between 6-asset and 8-asset portfolios. The graph shows a decline in performance after 8-assets, until the portfolio reaches 20 assets. It’s worth noting that daily rebalancing has the most consistent performance, outperforming every other strategy until 16-asset portfolios. At its best, daily rebalancing outperforms HODL by 6.61%
Weekly rebalancing shows the best results at 14 assets or more. Further improvements are negligible. There is also a decline in performance between 4-asset portfolios and 10-asset portfolios. At its best, weekly rebalancing outperforms HODL by 3.63%
Monthly rebalancing shows minimal improvements in performance beyond 10-asset portfolios. It is also the strategy with the worst performance out of all the rebalancing strategies. At its best, monthly rebalancing outperforms HODL by 1.01%.
Higher frequency rebalancing periods, such as daily and hourly rebalancing, stand out the most. Both have consistently higher performance than other strategies. Their performance curve is also extremely steep. These rebalancing periods benefit the most from including more assets in your portfolio.
Our case study shows that diversification has a noticeable impact on cryptocurrency portfolios.
Portfolios with a smaller number of assets benefit much more from further diversification than portfolios with an already large number of assets.
Diversification has, on average, a negligible impact on performance beyond 14-asset portfolios.
When combined with rebalancing, diversification has had the biggest improvement on high-frequency rebalancing. Hourly and daily rebalancing have benefited the most from diversification, showing steep improvements in performance leading up to 8-asset portfolios.
The backtests and rebalancing strategies were carried out using our very own portfolio rebalancing tool, Shrimpy.
Shrimpy is an automated portfolio management platform that helps you not only rebalance but also diversify your crypto portfolio.
You can connect over 25 exchange accounts and wallets with Shrimpy and start rebalancing your portfolio right away. Shrimpy is one of the easiest to use rebalancing tools in the industry.
Sign up now by clicking here.
Each day Shrimpy executes over 200,000 automated trades on behalf of our investor community. And joining them is easy.
After you sign up and connect your first exchange account, you’ll deploy an investment-maximizing strategy in as few as 5-minutes.
Whether you create your own rebalancing strategy or completely custom automation, the ability to walk your own path belongs in the hands of every crypto investor.
Our latest case study analyzes the performance of three popular crypto investing strategies: threshold rebalancing, periodic rebalancing, and HODL.
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Diversification and rebalancing have a positive impact on portfolio performance. Discover which portfolio sizes and rebalancing periods are the best.