Allocation of Assets

A brief overview of how the assets are allocated.


It is well known that indexes very often outperform hedge funds in tradFi. Popular studies also show that the S&P500 and other indexes have a positive return on investment over time. The reason for this is the rebalancing mechanism. Thus, for instance, shares that increase in price are used to buy cheaper ones or those that have declined in price, on an ongoing basis. The mathematical effect of this is that the total risk and volatility exposure are reduced. Since risk is lower, return/risk tends to increase. Of course, this is not financial advice, we encourage readers to make their own research before investing in any financial instrument (fiat, index, stocks, crypto, etc).
Hereby we compile a series of automated strategies that are initially available. However, users are also able to build their own asset allocation.

Overview of Automated Strategies

Three of the most popular asset allocation strategies are Market Cap (MC), Price-Weighted (PW), and equally-weighted (EW) portfolios. We have also created a combination of them that can adapt according to market conditions following optimization techniques, such as Sharpe and Martin ratios.

Market Cap (MC)

An MC-weighted portfolio assigns the weights of the distribution of assets proportional to their global market cap. Thus, in the crypto world, for instance, BTC will have the largest allocation and then ETH, and so on. This strategy is used by the S&P500 and has shown to work well over several decades for the stock market.

Price-Weighted (PW)

As its name stands for, the weights are calculated proportionally to their current price. This distribution has been used in the Dow Jones over time and has also shown to be providing some return on investment over decades.

Equally-Weighted (EW)

This strategy assigns all weights equally. It is very useful to increase the exposure to lower cap protocols/stocks/crypto and not miss out on any high rewarding returns in case they jump up in price. Some simulations have shown that this strategy outperforms the MC over the last decades. Therefore, it deserves to be taken into consideration.

Dynamic Strategy (DS)

Our dynamic strategy consists of a combination of the previous ones and adapts according to the market conditions. The predicted weights by each strategy are transformed by a mapping function so that they can be compared and combined. The system evaluates the best-performing case daily for the last month and sticks to it.

Assets in the Portfolio

At the moment the assets are fixed: BTC, ETH, NEAR, SOL, and USDC, in the NEAR protocol; and BTC, ETH, MATIC, LINK, and USDC, in the Polygon Network. They were chosen by ensuring that they have enough liquidity to be swapped in the DEXs to avoid price slippages, and correspond to the native tokens of different chains to diversify. USDC is part of the portfolio to hedge against market turmoil. In the future, users will be able to select their assets.
Note: when mentioning BTC, ETH, NEAR, SOL, and USDC, in reality, we are referring to their wrapped versions in the NEAR protocol chain, and the same applies to the Polygon Network. This may change in the future when cross-chain contract calls are implemented.