Visualizing Returns in the Crypto Market

This study is a follow-up of the articles Can You Beat the Crypto-Market? and Can You Still Beat the Crypto-Market? by Anton Muehlemann, PhD. Anton attempted to deduce the ROIs for different types of asset allocations, such as investing in large cap or small cap coins, by equal amounts or by amounts varying with market cap.

Seeing that, I had an idea: what if we discard the data in between and just take the prices at the days of investment and profit realization. This would give us the ability to visualize the returns for a continuous range of asset allocations.

Let me clarify with an example: Let’s say we have 1000 coins in CoinMarketCap, sorted by their market capitalizations. You have $10,000 and want to invest in a range of coins. You can have different choices of investment:

1. All of them: If you were to invest in every coin with an equal asset allocation, you would have invested $10 to every coin.
2. Mid 60%: You invest ~$16.7 to every coin between the ranks 200–800.
3. Top 20%: You invest $50 to every coin between the ranks 1–200.
4. Top 0.1%: You invest $10,000 to a single coin, which in this case, is Bitcoin.

After a month or a year, your investment would perform differently for these 4 options. A handy tool would be one that can show the performance of these portfolios and all the values in between. Let’s take a quarter of a circle, and define a polar coordinate system. Let the radius r denote the amount of coins invested, and angle θ denote the position of our investment in the total range of 1000 coins:

Legend for the return slice. 1, 2, 3 and 4 correspond to the different portfolios given in the example above. To find the ROI when you invest in a range between a^th and b^th coins, follow the reference lines down from the top arc until they intersect.

Now, we have a coordinate system to lay our ROIs. And we don’t have to make a precise definition of low-cap coins vs high-cap coins. If there is an optimal value in between, we should be able to see it clearly. Below is an example for January 2017.

ROIs for January 2017. Value increases are shown by shades of red, whereas decreases shades of blue.

From this figure, we understand that for January, among all 80 of the sufficient volume coins, the low cap ones were the most profitable. Investing in the bottom 20% — which has 4 of the top 10 increases in value — would have made you more than 50% profit in one month. Furthermore, if you open the image in a new tab and zoom in, you would see that the highest ROI belongs to Decred with 5x, followed by ZCoin with 2.7x.

Notice how high ROI coins paint a triangular region starting from the top. That region corresponds to allocations containing that coin.

Below is a return slice for the entire 2017.

ROIs for 2017. The scale was adjusted to take into account the 57x increase for 100% asset allocation.

2017 was the year of ICO bubbles, and there was a phenomenal increase in the capital entering the market. The bubble burst 2 months later, with massive sellouts reducing the total market cap by ~50%.

ROIs for March 2018. It’s all blue :(

This marked the beginning of a new bear market, and restoration of sanity.

Conclusion

I invented this way of visualization to see whether there were a way to detect patterns and find an optimal range of asset allocation.

I couldn’t find any. Even if there were a pattern to speculative investment, it wasn’t worth investigating. Many of the increases were due to scams, aggressive marketing and pump-and-dump groups. The only way to win consistently in this market is to learn about the tech itself, and get in early when something promising appears. Following this study, I stopped looking at prices altogether and started reading.

Originally published at osolmaz.com on August 22, 2018.