Fundamental Valuation Approaches: DCF | by Aenigma Capital | Medium

With the first part of our report on Fundamental Valuation Approaches, Ænigma Capital brings you our summary of the Discounted Future Cash Flow model of network value.

The Discounted Future Cash Flow Component


Many investors find fundamental valuation of crypto assets difficult, believing they do not generate tangible direct payments of traditional cash flows to token holders.

In fact, the cryptoeconomic token models of certain distributed autonomous corporations (“DACs”) have cash flow-like features similar to those of traditional companies. Effective cash flows from holding digital assets may take several forms, but the fundamental valuation relationship remains constant: Fair Value = Discounted Future Expected Cash Flows.

We illustrate this concept with four DCF sub-components:

Figure 1. Discounted Future Cash Flow Subcomponents.

In practice, the calculation of the discounted cash flow sub-components is dependent on individual token economics.

For example, DACs often require that service fee payments be made by users of the network. Many of these payments are made to groups of participants (“workers”) who perform certain tasks or assume some level of capital risk. Per the applicable protocol, workers may be required to stake tokens for security or reputational purposes as part of the barrier to functioning as a master node or validator. The potential service payments create the incentive for workers to purchase and hold tokens as required by network protocol.

Staking requirements are the digital equivalent of a new partner being required to purchase and hold shares in the firm in order to receive a dividend of company profits. Similarly, the workers in a DAC should be willing to pay a price for staking tokens that reflects the effective salary payments and profit distributions expected to be received.

Each of these market opportunities has emerged because of the cash flow-like qualities of digital assets. That said, it is worth examining two underlying assumptions of the discounted future cash flows component.

Assumption 1: Payments made in coins and tokens are cash flows.

To take service payments as an example, fees are remitted in cryptocurrency coins or tokens and not as fiat cash flows. Regardless, they constitute payments of value that are appropriate to the underlying asset and qualitatively similar to cash flows. Before a worker can receive service payments, they must first have purchased the network token via ICO, mining, or the open market. To the extent that a market for resale exists, the user has effectively injected value into the anticipated currency prior to receipt, as service fee payments may be re-exchanged for value in the form of actual cash flows.

The requisite amounts and timing of liquidity in many cryptocurrencies do not yet allow for a seamlessly fluid coin to cash flow exchange. But in a well-functioning market for a coin that is demanded for a real, constant, and predictable use case, the adoption of service fee payments as a proxy for certain cash flows will produce materially accurate valuations.

To identify the portion of excess value that becomes trapped in the network due to lack of liquidity and sufficient trading volume or due to network users holding tokens, we would further analyze the utility usage model of supply, demand, and velocity and the discounted future cash flows component.

Assumption 2: Distributions of value related to holding coins and tokens are cash flows.

Much like traditional companies, DACs such as Factom and Stellar regularly perform equity-like token transactions with effective profit and loss impact that is passed on to token holders in the form of network value. Some amount of user tokens is destroyed in exchange for services like file storage or transaction processing. The network protocols then pay out newly issued tokens to specified workers in their systems. This type of system in crypto is often described as a “burn and mint model.”

The financial impact of the burn and mint process can be understood as a traditional profit and loss accounting flow:

Network Revenue: Senders of transactions incur fees that are paid by destroying network tokens. The purchase of tokens to pay fees is an external cash flow value entering the network much like revenue entering a company. The reduction in token supply is similar to a treasury stock purchase. The net effect of the transaction is the recognition of revenue passing through the network as upfront profit used to buy back shares in the DAC.

However, just as company revenue is not equal to net income, in many networks, the buyback cost is not the value ultimately retained by token holders. Instead, the gross buyback cost must be adjusted for applicable expenses — and in the crypto economy, expenses are often dilutive shares issued as part of the token inflation process.

Network Expenses: The ledger distributes fees to workers in accordance with network protocol as part of the scheduled inflation of the pool of circulating tokens. In traditional terms, the distribution is similar to a company granting stock compensation to employees from its treasury stock, a portion of which is recognized as expense on the income statement. These shares should be considered in-kind cash flows so long as a resale market exists.

Network Net Profit and Value: As with a traditional company, the market capitalization and price are determined by the net profit that network token holders expect to receive from this process. Once the shares are given out, the accounting flow is complete, and the net profit can be calculated as follows:


Figure 2. GAAP to Crypto Accounting Profit and Loss Model.

Based on this understanding of profit, loss, and value, crypto investors should broaden their view of cash flows to include effective cash flows, which are any distributions of value that a token holder receives as a result of owning the digital asset. The value of these expected cash flows should be reflected as a component of the value that investors would ascribe to the token price.

Next up: Ænigma’s macro cryptoeconomic thesis and the other components of network value.