Total value locked can help investors decide crypto allocation

Digital asset management will greatly benefit from the techniques and experience from traditional finance. From portfolio construction methodologies to regulatory frameworks, leveraging best practices from decades of research in traditional asset management will help accelerate crypto’s wider adoption.

However, in certain ways, unlike traditional asset classes, blockchain assets may warrant a closer look beyond familiar concepts. It includes the use of market capitalization as a weighting methodology for passive portfolios.

Portfolios across both traditional and digital asset classes often use market capitalization to determine how much to invest in each underlying asset. Doing so gives investors a simple passive exposure to the overall market. For digital assets, however, complementing market value with some measure of a blockchain’s usage can improve portfolio construction.

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One way to do that is with Total Value Locked (TVL), which represents the value of assets deposited on a blockchain. A higher TVL suggests greater economic activity and potentially better prospects for future activity or a larger active user base. (A lower TVL implies the opposite.)

By taking the ratio of market value to TVL (MC-TVL), we can get a more fundamental sense of an asset’s utility value beyond the superficial view of market value, similar to how equity investors use ratios such as price-to-book (P/B) to discern a stock’s value. A higher MC-TVL suggests that an asset’s capitalization may be inflated, with a value that disproportionately exceeds its use. Conversely, a lower MC-TVL may imply an undervalued blockchain, where the markets have not yet priced in the activity.

We ran a simulation on a top-10 index weighted by market capitalization against one weighted by MC-TVL. The results are below:

The MC-TVL approach outperformed over the period in this hypothetical scenario, driven by outsized positive performance in 2021. Over the period, daily returns between the two had a correlation of 0.85, suggesting that although the weighting methodologies are alike (by design), meaningful differentiation still exists between them. In the long term, integrating blockchain usage into passive products can improve overall market exposure and help investors better adapt to the crypto fundamentals.

This experiment, while a highly simplified and mostly illustrative simulation, is intended to encourage more nuanced analyzes of crypto-specific characteristics and how they can be integrated into portfolio construction. Despite the limited duration of the backtest, in the long run lower MC-TVL may prove to be a useful indicator of assets with greater network usage versus higher MC-TVL assets, whose size alone may not fully reflect value in the digital asset universe.

As crypto’s track record unfolds in real-time and new, richer on-chain data emerges, investors should monitor how fundamental adjustments to portfolio construction can help digital asset investment management.

Description of simulation: Data is for the period 1 January 2021-31. March 2023. These indices represent hypothetical backtests that are rebalanced monthly and do not take into account transaction costs or whether assets are investable. The indices exclude stablecoins, wrapped/pegged tokens, centralized exchange tokens and any assets that have not received a price in the last 365 days. Indices only include proof-of-stake assets for which TVL data is readily available. “Market value” refers to the circulating market value of an asset. TVL includes all forms of how assets are used, or “locked” on a chain, including stakes, unstaked assets held in wallets, assets sitting in DeFi protocols, dapps or smart contracts, and so on. This article only briefly describes TVL, but there are ways in which it can be further quantified and more richly defined. This hypothetical backtest has been prepared by Truvius for illustrative purposes only. Truvius makes no representations or warranties as to the accuracy or completeness of this information or its construction, and shall have no responsibility for any representations (expressed or implied) regarding information contained in, or for omissions from, this information. Past performance does not guarantee future performance.