Evaluating Crypto Portfolio Performance Based On Asset Market Capitalization
“In God we trust. All others must bring data.” — W. Edwards Deming
The following study will provide a glimpse into how market capitalization of crypto assets affects the performance of a portfolio. The data presented is based on actual market data. This allows us to accurately calculate the past performance of strategies in the crypto market without speculation.
Our last article evaluated the performance implications of diversifying a portfolio. You can read more about this topic here:
The design for this study was such that assets were divided into 3 categories; large ($70M — $26B), mid ($9M — $69M), and small ($900k — $7.8M) market capitalization. The capitalization ranges were defined by dividing the assets into 3 even groups based on the market cap of each asset on May 4, 2017.
The following constraints were used when performing each backtest.
Trade Fee: .25%
Data: Market data was collected from exchanges over the last year.
Data Time Period: May 4, 2017 to May 3, 2018
Asset Distribution: Evenly weighted among all assets.
Trade Path: All trades are performed through BTC for simplicity.
Asset Selection: Random within each market cap group.
Assets Included: The complete list can be found in our backtest tool.
Initial Investment: Each portfolio is seeded with a $5,000 investment.
Number of Backtests: 1,000 for each portfolio size, strategy type, and market capitalization grouping.
A more in depth discussion of the backtest procedure and study setup can be found in our previous article:
Four separate groups were evaluated: Large, mid, small, and combined market cap assets. Combined market cap represents all assets regardless of market capitalization.
Large Market Cap
In this study, large market cap coins consist of assets which fit into the $70M — $26B valuation range. Each valuation was taken on May 4, 2017.
The results of this group indicate there was no observable performance boost through simply increasing the number of assets in a portfolio which used the HODL strategy. However, we see a clear trend that as the rebalance frequency is increased, the performance increases as well. The largest of these performance boosts were observed with a 1 hour rebalance period.
Rebalancing a large market cap crypto portfolio resulted in up to a 1140% return over the last year.
Mid Market Cap
In this study, mid market cap coins consist of assets which fit into the $9M — $69M valuation range. Each valuation was taken on May 4, 2017.
Mid market cap coins demonstrated the highest return of any group over the last year. Not only do they present a strong case for diversifying even when HODLing, they demonstrated impressive growth when rebalanced frequently. One hour rebalances resulted in a 156% increase in portfolio value when compared to HODL.
Rebalancing a mid market cap crypto portfolio resulted in up to a 3980% return over the last year.
Small Market Cap
In this study, small market cap coins consist of assets which fit into the $900k — $7.8M valuation range. Each valuation was taken on May 4, 2017.
Small market cap coins presented interesting results. HODLing a small market cap portfolio demonstrated the lowest returns of any backtest group over the last year. However, increasing the rebalance frequency provided significant improvements. Although HODLing performed far worse than large market cap assets, a 1 hour rebalance period proved to result in impressive gains over large market cap assets.
Rebalancing a small market cap crypto portfolio resulted in up to a 2820% return over the last year.
Combined (Any Market Cap)
Combining all market caps provides a general overview of the market. We can see that mixing assets with different market caps into a portfolio creates a middle of the road performance.
Rebalancing a crypto portfolio resulted in up to a 2340% return over the last year.
Conclusions & Interpretations
The data set we obtained shows that mid market cap portfolios outperformed small, large, and mixed market cap portfolios over the last year. While this could simply be an anomaly based on the assets which were included in the pool, it may also indicate something about the market.
Mid market cap portfolios had the highest returns over a 1 year period.
Although some people may have expected that small market cap assets would have the highest potential for returns over the last year, this was far from the truth. These results illustrate a striking development.
HODLing small market cap portfolios resulted in the worst returns over a 1 year period.
Lastly, although HODLing a large market cap portfolio proved to outperform a small market cap portfolio, this was not the complete story. A large market cap portfolio under performed all other portfolio groups when rebalanced frequently.
Large market cap portfolios had the worst results when rebalanced every hour over a 1 year period.
Rebalancing with Shrimpy
The last year has proven that rebalancing a diverse portfolio can improve performance. Shrimpy simplifies the entire portfolio management and rebalancing process to a point and click interface. Quickly select assets, instantly allocate a diverse portfolio, and rebalance on a scheduled time period. Best of all, Shrimpy is completely free to use right now!
Sign up by clicking here.
If you still aren’t sure, try out the demo to see everything we have to offer!
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Leave a comment to let us know your experiences with rebalancing!
The Shrimpy Team