The Setup

Instead of stopping at 10, we went up to 40 assets (our preferred general term for cryptocurrency) in each portfolio this time. That’s 100,000 backtests. The results of those backtests have been broken down by strategy type. We also converted the graphs to a simple line graph that shows the relationship between the number of assets in a portfolio and the median value of the portfolio at the end of a one year period. The initial investment for each backtest was set to $5,000.

Additional information regarding the setup for the backtests can be found here:

Rebalance vs. HODL: A Technical Analysis

HODL

This graph shows the results of a $5,000 initial investment that used the HODL strategy for one year. Each data point on the graph is 1,000 backtests which were run by randomly selecting the number of assets on the x-axis.

This plot shows that HODLing approached an asymptote around $45k after a one year period. As the number of assets increased past 16, there was a minimal observable difference in value.

1 MONTH REBALANCE

This graph shows the results of a $5,000 initial investment that used 1 month rebalances for one year. Each data point on the graph is 1,000 backtests which were run by randomly selecting the number of assets on the x-axis.

This plot shows that a 1 month rebalance had an apparent asymptote around $60k after a one year period. As the number of assets increased past ~22, there was a minimal observable difference in value.

1 WEEK REBALANCE

This graph shows the results of a $5,000 initial investment that used 1 week rebalances for one year. Each data point on the graph is 1,000 backtests which were run by randomly selecting the number of assets on the x-axis.

This plot shows that a 1 week rebalance had an apparent asymptote around $65k after a one year period. As the number of assets increased past ~16, there was a minimal observable difference in value.

1 DAY REBALANCE

This graph shows the results of a $5,000 initial investment that used 1 day rebalances for one year. Each data point on the graph is 1,000 backtests which were run by randomly selecting the number of assets on the x-axis.

This plot shows that a 1 day rebalance had an apparent asymptote around ~$73k after a one year period. As the number of assets increased past ~14, there was a minimal observable difference in value.

1 HOUR REBALANCE

This graph shows the results of a $5,000 initial investment that used 1 hour rebalances for one year. Each data point on the graph is 1,000 backtests which were run by randomly selecting the number of assets on the x-axis.

This plot shows that a 1 hour rebalance had an apparent asymptote around ~$145k after a one year period. As the number of assets increased past ~18, there was a minimal observable difference in value.

COMBINED RESULTS

This graph shows the results of a $5,000 initial investment that used the strategies as discussed above. Each data point on the graph is 1,000 backtests which were run by randomly selecting the number of assets on the x-axis.

This plot compares the rebalance periods and their performance over the last year. We can see that 1 hour rebalances had significantly higher returns than other periods. However, regardless of the strategy, this data suggests that a portfolio ranging from 14 to 22 assets had the highest performance potential per asset over the last year. Above this range adding more assets didn’t provide a large increase in value, although it does provide some benefit. Assets below this range resulted in a sharp decline in portfolio value.

Conclusions

The median portfolio value generally tended to increase with the number of cryptos over the last year. Portfolios with a smaller number of assets typically benefited more from adding additional assets than those with a larger number of assets.

One concern that some people expressed was that there may be an inflection point. This would be a point at which adding more assets to a portfolio decreases the median value. The results don’t appear to indicate any such inflection point.

Over the last year, portfolios holding more assets tended to outperform those holding fewer assets.

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