Token Valuation Methods

Now that we’ve covered the building blocks of the ecosystem, let’s discuss how to evaluate and invest in its major players.

A common complexity when dealing with emerging technologies is the ability to accurately forecast the future value of a project that may have utility and growing adoption but lacks the standard metrics used for asset, earnings, and market-based valuation. Regardless of a token’s stats on CoinMarketCap, prudent investors should perform the following due-diligence before buying.

Fundamental Analysis

A quantitative and qualitative evaluation of an asset’s intrinsic value.

Key Fundamentals:

• Whitepaper: Use Case for Decentralization, Tokenomic Model, Governance Structure
• Market Share: Total Addressable Market (TAM), Market Cap, Liquidity, Active Users, Transaction Volume, Fees or Revenue Generated
• Team: Founders, Leadership, Developers, Engineers, Investors, Advisors, Business Development, Marketing, Partnerships, Community Engagement

Evaluation Example: Chainlink

• Description: Chainlink is a decentralized oracle network connecting smart contracts to the off-chain data feeds, APIs, and payment systems required for real world application.
• Total Addressable Market: Let’s consider the international payment network SWIFT, which has been in discovery to integrate Chainlink in its financial messaging system for bond payments since 2017, as a proxy for one of its addressable markets. In Feb 2020, SWIFT recorded an average of 36.7M FIN messages per day — assuming just 10% of this message volume is related to Chainlink’s initial scope of bond payments, the SWIFT partnership alone would represent over 3M transactions per day. In comparison, the entire Ethereum network averaged roughly 750K transactions per day over the last year with an average market cap of $20B (about 20x the current market cap of Chainlink). Note: Chainlink’s TAM extends far beyond bond payments (see Partnerships below). LINK Marines (Chainlink community members) anticipate that Chainlink will become the TCP/IP of blockchain.
• Use Case for Decentralization: Smart contracts are only as reliable as the data they use to trigger execution — if a smart contract uses a centralized oracle for its data feed, then there is a single point of failure for malicious actors to attack. For example, if a $1M superbowl bet is placed using a smart contract with a centralized data oracle, the bettor only has to successfully manipulate the game score reported by one source in their favor to trigger the automatic transfer of funds to their account (regardless of the real world outcome of the game). Chainlink mitigates this risk by using a decentralized oracle network to provide accurate inputs and outputs for enterprise-grade smart contracts.
• Tokenomic Model: Chainlink’s native token (LINK) is used to compensate the data providers and payment networks servicing the network. LINK is awarded to nodes with accurate responses and taken away from those with inaccurate/incomplete data. This system establishes a reputation score for oracles and allows high value smart contracts to require larger amounts of LINK as collateral from node operators to better ensure data accuracy. This makes LINK an asset with scarcity, utility and passive income opportunities whose value is directly related to usage of the network.
• Team: Sergey Nazarov (CEO) and Steve Ellis (COO) are tenured leaders with significant expertise in their roles, respect from the community, and years of experience in smart contracts. They have secured first mover advantage in the decentralized oracle network as well as critical acquisitions such as Town Crier and smartcontract.com. The Engineering and Operations team has a proven track record in software and blockchain tech with support from the industry’s leading technical advisors in Ari Juels (co-director of IC3), Evan Cheng (co-creator of LLVM for Apple, Google, Intel, etc.), Hudson Jameson (Community Manager at the Ethereum Foundation), and Andrew Miller (leading researcher and advisor at Zcash and Tezos). Non-technical advisors include Tom Grosner (Founder of DocuSign), Jake Brukhman (CTO at Triton Research), and Brian Lio (CEO of Smith & Crown). Business Development efforts led by Dan Kochis have debatably secured more significant partnerships than any project in the space, with Marketing/Community Management achieving similar success among token investors. The Chainlink community (aka LINK Marines) is widely recognized as one of the most loyal and engaged constituencies in crypto.
• Partnerships: Chainlink continues to announce partnerships with some of the biggest names in Crypto, Legal, Insurance, Internet, Software, Retail, and other industries, including: Google Cloud, Oracle, Open Law, Credits, Binance, ZeppelinOS, Dapps Inc., Matic Network, Web3 Foundation (Polkadot), Synthetix, and dozens more.
• Price Prediction: Based on Chainlink’s TAM, Tokenomic Model, Network Activity (in terms of both users and transactions), Team, and Promising Partnerships, I’m targeting a base case token price of $15 and best case of $30 by 2022.

While Fundamental Analysis is critical for any investment, particularly cryptoassets, let’s take a more quantitative look at projects with the cash flow and competition required to tailor existing methods like Price to Earnings (P/E) and Discounted Cash Flow (DCF) for token valuation.

Revenue produced by DeFi networks is typically driven by usage based fees rewarded directly to liquidity providers or used to burn the native token (reducing total supply). In order to apply these traditional frameworks to crypto, I’ll be using data aggregated by Token Terminal to drive model assumptions.

(Image Credit: Token Terminal — April 13th, 2020)

Price to Earnings Ratio (P/E)

• Formula: In Crypto, P/E = Liquid Market Cap / Annualized Revenue
• Description: P/E ratio is a simple and widely used investment heuristic to quickly compare the relative value of an asset to its competitors or its own historical performance. While lower P/E ratios are generally preferred by investors as they represent a lower share price per dollar of earnings — higher P/E ratios may indicate that traders anticipate future growth. Willy Woo and Chris Burniske introduced the first crypto adaptation of this ratio, NVT (Network Value to Transaction Volume), in 2017. NVT uses Transaction Volume as a proxy for Earnings for cryptocurrencies like Bitcoin whose primary function is payments and store of value. Since fee structures can vary between DeFi projects, we’ll use Fee Revenue as our denominator (NVF) to yield a ratio that can be compared from project to project without adjusting for different fee structures.
• Use Cases: Exchanges, Prediction Markets, and other cash-flowing networks
• Best Practices: When using Relative Ratios like NVT or NVF to compare investment options, it’s best practice to calculate medians for each category as a baseline for what numerical ranges could indicate under or over-valuation. Extremely high ratios like those of Tezos and Cosmos above can indicate overvaluation as they highlight a competitive discrepancy between the network’s current value and the propensity of its tokenomic model to generate fees, relative to similar protocols.
• Challenges: Network effects from the limited availability of fiat onramps can impact investment allocation (i.e., the Coinbase Effect), giving first movers (like 0x) the advantage.

Valuation Example: Synthetix

• Platform Overview: Synthetix is a decentralized exchange for trading synthetic assets (Synths) whose prices track the direct and inverse (long and short) movement of fiat, crypto, and commodities, with equities, indices, and other derivatives on the road map. Synths are collateralized by the network’s native token SNX which derives its value from Synth trading fees. SNX holders are incentivized to stake their tokens as they are paid a pro-rata portion of the fees generated on Synthetix.Exchange.
• Growth Potential: Synthetix’ 2020 Road Map features the addition of Leverage and Synths for equities (TESLA), Indicies (S&P 500), and Derivatives (Binary Options, Futures). Given that the total addressable market (TAM) for derivative trading is estimated at $600T annually, Synthetix is poised to capture share in the largest market on earth as the only DEX with infinite liquidity and zero slippage.
• Price Prediction: The following forecast estimates a price of $6.44 (just over 9x the current price of $0.70) in 2022 under these assumptions:
• Synthetix reaches a daily exchange volume of $10M (BitMEX is currently over $1B)
• Traders price SNX at a NVF Ratio of 158 (MakerDAO is currently valued at 214 and 0x is over 15,000 — neither of which directly offer leveraged derivatives)

Image Credit: Keegan Selby (April 26, 2020)

Discounted Cash Flow Analysis (DCF)

• Formula: DCF = CF1/(1+r)1 + CF2/(1+r)2 + CFn/(1+r)n. Where, CF = the cash flow for the given year, CF1 is for year one, CF2 is for year two, CFn is for additional years, and r = the discount rate.
• Description: DCF is an absolute valuation method that discounts future cash flows to estimate present value. Unlike the relative P/E ratio, DCF does not require comparison to industry peers — it is simply compared to the current value of the asset. If the present value of future cash flows is higher than the asset’s current value, the investment is estimated to result in a positive return.

Valuation and Price Prediction: Synthetix

• Assuming high growth in the next five years as Synthetix eats into the gigantic Derivatives market and a discount rate of 25% to account for the higher risk premium of decentralized trading platforms, the Present Value of Cash Flows is roughly $1B compared to the current network value of $138M. Dividing the Projected Network Value by the Total Token Supply yields a Token Price of $4.42 (roughly 6x the price at time of writing).

Image Credit: Keegan Selby (April 26, 2020)

Token Velocity (Monetary Equation of Exchange)

• Formula: M = PQ/V. Where M = Currency Value (Market Cap), V = Currency Velocity, P = Token Price, Q = Token Quantity (Total Supply)
• Description: The Monetary Equation of Exchange (MV=PQ) has been used to model future token valuations since the early days of Bitcoin. I recommend Chris Burniske’s commonly cited article Cryptoasset Valuations which includes a free downloadable model.
• Use Cases: To use the Quantity Theory of Money for token valuation, we need to calculate the Market Cap in each future year, divide by the expected outstanding float, and then discount to the target year. Generally speaking, the equation implies that tokens with lower velocities (meaning those that are held in the same wallet for longer periods of time) will accrue higher prices due to appreciation of value (M), all else equal.

Valuation and Price Prediction: Ethereum

• Context: As tokens like Ethereum transition to Proof of Stake (POS), users will be incentivized to hold Ether to earn staking rewards — driving some traders to cite the Token Velocity thesis for higher price predictions (assuming staking reduces velocity). However, as quantifying Ethereum’s TAM is largely guesswork given the broad scope of layers and dApps that could use the Triple-Point Asset, some analysts limit the scope to programmable money while others envision Ethereum addressing a broader market of web-based applications from ecommerce to content-streaming. Since ETH is used as collateral for so much of the DeFi ecosystem (1.5 ETH required for every DAI minted) — one could argue that the ETH market cap will always have to be some multiple higher than the combined market cap of all DeFi tokens using ETH collateral. Since a growing amount of ETH will become illiquid to support overcollateralization and staking, its velocity should theoretically fall despite rising demand. Combine this with the introduction of burning as a mechanism to reduce ETH inflation (perhaps even resulting in a negative issuance rate, i.e. deflation) and you have a very bullish case for ether using the Monetary Equation of Exchange.
• Valuation and Price Prediction Example: The model built by a reddit user below applies an adoption curve to a $366B primary market (annual revenue of the top 10 internet companies at the time) and uses a velocity of 1.6 for Ether (based off Vitalik Buterin’s approach to measuring velocity, i.e. the number of times that an average coin changes hands every day). The model produces a sensitivity analysis estimating at 5% adoption of the primary TAM by 2030 (risky enough to justify a 26% discount rate for present value calculations), the token price of Ethereum would be $1,827 (roughly 10X its current price).

Image Credit: TraderSubs (1/21/2018)

Shortcomings of Traditional Methods for Cryptoasset Valuation:

• Novel token economic models present additional variables and complexity that don’t easily translate into existing valuation methods
• Tokenomic models often change rendering previous valuation models obsolete (e.g., Eth 1.0 used Proof of Work while Eth 2.0 will use Proof of Stake)
• As an emerging technology with unproven adoption and scalability, defining the TAM for cryptoassets is largely guesswork
• Limited and inconsistent data history on asset performance and correlations makes it difficult to determine industry averages
• Crypto is still an immature and irrational market — often driven more by hype or FUD, than quantitative value indicators

Conclusion

While accurately forecasting token prices has always been a long-shot given the modeling risks noted above — the experiment itself leads to a better understanding of the interrelated drivers behind token value. Producing a decent sensitivity analysis will shed light on the range of assumptions (market size, fees generated, etc.) necessary to achieve various price ranges. For these reasons, I prefer price predictions based on educated quantitative assumptions to the bulk of those issued by twitter traders simply putting their fingers to the wind and proclaiming “LINK will be worth $50 one day!”

As the ethos of DeFi turns traditional finance on its head returning system design and control to its constituents, our approaches to forecast the value captured through various tokenomic designs must be reevaluated as well. While teams like The Block and Token Terminal make strides in aggregating, analyzing and exposing actionable on-chain data — analysts continue trying to crack the code of token valuation. Whoever succeeds in this effort will not only prosper financially but will likely have their names immortalized in the economic textbooks of the future. As Chris Burniske once said back in 2017, “People win Nobel Prizes for that kind of thing.”

In my next post, I’ll discuss how to earn passive income from token investments using strategies like lending, staking, and options trading.

Hope you enjoyed and thanks for reading!

Disclaimer: All of the information (above and linked) is for entertainment purposes only and is not to be taken as investment or financial advice. I hold long positions in the projects mentioned and abide by a no trade policy 3 days before and after publishing of this article.