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Colossus (Invest Like the Best / Business Breakdowns)Podcast7 Nov 2017Source: traffic.libsyn.comHost: Patrick O'Shaughnessy

Chris Burniske - How to Value a Cryptoasset - [Invest Like the Best, EP.62]

In plain words

This episode explains how to value cryptoassets using the equation MV=PQ, treating each network like a mini-economy. Chris Burniske says the key is to estimate the network's total economic output (like Filecoin's storage fees), then divide by the velocity of money to find the token's fair value. He likes Filecoin (needs to predict storage price and user adoption), Bitcoin (about $1B daily on-chain transactions, but 60% held as savings), and Aragon (an overlooked tool for managing organizations on the blockchain). He warns that high velocity is bad for investors because it can make tokens worthless.

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Chris Burniske, on the Invest Like the Best program, explored a valuation framework for crypto assets, with the core idea being the use of the Equation of Exchange as a starting point for assessing utility value. He distinguishes between cryptocurrencies, crypto commodities, and crypto tokens, and e

~12 min full read · 11 sections
Deep Analysis

Chris Burniske - How to Value Crypto Assets - [Invest Like the Best, EP.62]

At a Glance

Chris Burniske is a former ARK Invest analyst (once the only traditional buy-side analyst covering Bitcoin) and now a partner at Placeholder. The main thread of this episode: using the equation of exchange (MV=PQ) to build a valuation framework for crypto assets, distinguishing among three asset types: cryptocurrencies, crypto commodities, and crypto tokens. Chris Burniske argues that the key to valuing crypto assets is not predicting price, but quantifying the GDP of the network economy (the PQ side), then using velocity (V) to back out the required monetary base (M)—this is conceptually homologous to traditional DCF models, but the object shifts from corporate cash flows to the scale of the protocol economy.


Theme 1: The Equation of Exchange – The Foundation of Crypto Asset Valuation

Chris Burniske argues that MV=PQ is the starting point for valuing crypto assets, treating each protocol as a "micro-economy" whose GDP is determined by the total value of goods or services provided by the network.

  • Mechanism Breakdown: M = monetary base (e.g., ~$4 trillion for the USD), V = velocity of circulation (e.g., 5–6 times per year for the USD), P = average price of goods, Q = quantity of goods. MV=PQ is used in traditional macroeconomics to measure money flow in fiat economies. For crypto assets, Chris maps this to protocol economies: taking Filecoin as an example, P is the price per GB of storage (forecasted based on historical cost decline curves), Q is the storage volume (based on TAM and S-curve penetration assumptions), and PQ represents the network's "GDP."
  • Data Chain: Chris points out that valuing Filecoin requires first forecasting "price per GB × storage volume" to derive the annual economic scale, then dividing by velocity to obtain the required monetary base (M), and finally dividing by the number of tokens in circulation to arrive at the current utility value per token.
  • Extrapolation and Uncertainty: Chris emphasizes that velocity (V) is the most uncertain variable in the model — "We don't have enough data to say whether a velocity of 5 is reasonable, or 10, 20, or 100. That's a huge assumption." He recommends using a high discount rate of 30–50% to discount future utility value back to the present.

Theme 2: Bonding and Circulating Supply Adjustment — Removing "Dormant" Tokens from Float

Chris Burniske argues that when valuing a token, one must subtract from the total supply those held as a store of value (velocity of zero) and those staked for consensus, because only the "active float" participates in price discovery.

  • Mechanism Breakdown: Bonding is the core mechanism of Proof of Stake (PoS) — participants must lock up a certain number of tokens (e.g., Ethereum's plan requires 1,000 ETH) as collateral, which is slashed if they act maliciously. Chris believes this is more efficient than Proof of Work (PoW): "PoW assumes everyone is a bad actor and continuously consumes energy to punish them; PoS requires you to stake assets to prove you are a good actor, or else your deposit is slashed."
  • Data Chain: Chris cites analysis with Coinbase, estimating that approximately 60% of Bitcoin is held purely as a store of value (velocity of zero). For example, if the total supply is 100 million tokens, with 60% held and 20% staked, only 20%, or 20 million tokens, constitute the active float. If the required monetary base is $20 billion, the utility value per token = $20 billion ÷ 20 million = $1,000.
  • Implication: Chris argues that the staking mechanism not only enhances network security but also supports token prices by reducing the float — "All assets are priced at the margin, based on future utility. Staked tokens do not participate in daily transactions and therefore should not be counted in circulating supply."

Theme 3: Decomposing Velocity — Bitcoin's "Hidden Velocity" Is Much Higher Than the Surface

By decomposing Bitcoin's velocity, Chris Burniske reveals a counterintuitive fact: as a medium of exchange, Bitcoin's actual velocity may be as high as 15 times per year, far exceeding the overall velocity of 5–6 times.

  • Data Chain: Bitcoin's current daily on-chain transaction volume is approximately $1 billion, annualizing to about $360 billion; the network value is roughly $90 billion (taking the full-year weighted average at about $60 billion), so overall velocity = 360 ÷ 60 = 6. However, if 60% of Bitcoin is held (velocity = 0), then the remaining 40% serving as a medium of exchange must satisfy: 0.6 × 0 + 0.4 × V = 6 → V = 15. If the holding ratio rises to 80%, the velocity of the medium of exchange would need to reach 30.
  • Historical Context: Chris draws a comparison with the velocity of the US dollar — around 10 before the 2008 crisis, halving to about 5 after the crisis due to monetary base expansion. Bitcoin's overall velocity falls within the 5–6 range, similar to the current level of the dollar.
  • Implication: Chris points out that high velocity is unfavorable for investors — "If velocity is infinite, M = PQ ÷ ∞ means the required monetary base is zero, and the token's value goes to zero." Therefore, he focuses on whether the protocol has built-in mechanisms to reduce velocity (such as staking). "We want lower velocity, so that M is larger and the token's value is higher."

Theme 4: NVT Ratio – The "P/E Ratio" of Crypto Assets

Chris Burniske introduced the NVT ratio (Network Value to Transactions), proposed by Willy Woo, as a valuation metric for crypto assets, analogous to the P/E ratio in traditional equities.

  • Mechanism Breakdown: NVT = Network value (market cap) on a given day ÷ on-chain transaction volume on the same day. Chris explains: "Historically, Bitcoin has bottomed around an NVT of 50. After a bubble bursts, NVT spikes—because prices remain high, but people are afraid to trade, shrinking the denominator." Before a bubble bursts, NVT may actually soften, as arbitrage trading inflates transaction volume (the denominator), though this does not reflect genuine economic use.
  • Data Snapshot: Bitcoin's current network value is approximately $90 billion, with daily transaction volume of $1 billion, yielding an NVT of 90. Chris believes the ratio "needs more data for validation," but it already serves as a trackable starting point.
  • Extrapolation: Chris hopes to calculate NVT for the top 100 crypto assets in the future, but this requires syncing nodes and pulling on-chain data—a massive undertaking. He is currently collaborating with a professor to build a dataset.

Theme 5: Three Key Variables for Long-Term Investment — Technology, Governance, and Cryptoeconomics

Chris Burniske argues that, from a 10-year investment perspective, technology is the "entry ticket," governance is the core, and the cryptoeconomic model determines the long-term trajectory of token value.

  • Mechanism Breakdown:

1. Technology: The developer's capability in distributed systems — "Is it trying to solve a problem that no one has cracked in the past 20 years, or does it have a more feasible roadmap?"

2. Governance: Chris considers this the most critical factor — "All discussions about forks ultimately boil down to governance issues. Is the asset distribution fair? What is the process for software update participation? Who gets the newly issued tokens? If governance is unfair, it is easily forked, and value flows to competing protocols."

3. Cryptoeconomics: The utility value curve of the token — "Is it upward and to the right, stagnant, or even downward? This depends on the balance between the adoption curve (unit economic growth), the cost decline curve, and the inflation rate."

  • Deduction: Chris likens investing in crypto assets to "betting on the GDP growth of a miniature economy" — "What if I could invest in the GDP growth of cloud storage, not as a country, but as a closed network?"

Theme 6: Aragon — The Underrated "Delaware on the Chain"

Chris Burniske believes Aragon is an overlooked project that offers a decentralized organizational management framework and could become the "VeriSign" of the blockchain world.

  • Mechanism Breakdown: Aragon is an ERC-20 token running on Ethereum. It allows organizations to register on-chain, manage shareholder registries, pay employees, and ensure transparent use of funds. Chris describes: "It is like a decentralized Delaware — ICO projects can use Aragon to manage funds and operations, which in itself acts as a seal of trust."
  • Extrapolation: Chris argues that as the concept of decentralized autonomous organizations (DAOs) matures, Aragon's use cases will expand — "In the future, many organizational functions will be encoded and run transparently on the blockchain, and Aragon is moving in that direction."

Theme 7: Survival Risk – From 51% Attacks to Regulatory "Whack-a-Mole"

Chris Burniske systematically analyzes the survival risks of crypto networks, arguing that the most realistic threat is "kidnapping core developers," rather than technical attacks.

  • Risk Classification:
  • 51% Attack: Using Bitcoin as an example, Chris notes – "To rebuild the network's total hashrate, 200,000 to 400,000 ASIC miners are needed, costing hundreds of millions of dollars, but ASIC production capacity is limited. Even if the attack succeeds, core developers can release a software update to change the PoW algorithm, rendering the attacker's ASICs obsolete."
  • Regulatory Attack: Cutting off fiat on-ramps and off-ramps – "But this is a game of whack-a-mole: if one country cracks down, a neighboring country will raise its hand and say, 'Come to us.' Achieving global coordinated suppression of a sovereign protocol is extremely difficult."
  • Personal Attack: Chris considers this the most realistic risk – "Kidnapping core developers or miners, coercing them to shut down the network. This is grim, but more feasible than the previous two."
  • Extrapolation: Chris references Balaji's article on centralization and decentralization, emphasizing that assessing network resilience requires examining "how different forms of centralization are distributed."

Mentioned Positions

Position Analyst View Key Data
Filecoin Bullish (as a crypto commodity case) Requires forecasting per GB price decline curve, TAM, and S-curve penetration rate
Bitcoin Bullish (as a cryptocurrency case) On-chain daily transaction volume ~$1 billion, NVT ~90, overall velocity ~6, medium-of-exchange velocity ~15
Steem Bullish (undervalued crypto token) 2/3 of block rewards go to content creators, 1/6 to curators; has undergone 19 hard forks
Aragon Bullish (overlooked project) ERC-20 token, provides on-chain organizational management framework
Augur Neutral (as a crypto token case) Prediction market, censorship-resistant, but needs to cross the consumer adoption chasm
Ethereum Neutral (as a crypto commodity case) Plans to transition to PoS in Q1 2018, requires staking 1,000 ETH

Judgments Worth Remembering

1. "Crypto asset valuation is not about predicting prices, but quantifying the GDP of the network economy." (Chris Burniske) — Using the MV=PQ framework, first calculate PQ (value of goods × quantity), then back-calculate M (required monetary base), and finally divide by circulating supply to derive the token's utility value.

2. "PoW assumes everyone is a bad actor and continuously consumes energy; PoS requires you to stake assets to prove you are a good actor, or else face penalties." (Chris Burniske) — The staking mechanism is more efficient and supports token prices by reducing circulating supply.

3. "Bitcoin's medium-of-exchange velocity may be as high as 15 times per year, 2.5 times the overall velocity (5-6)." (Chris Burniske) — Because 60% of Bitcoin is held (velocity = 0), the remaining 40% must circulate at high speed to sustain on-chain economic activity.

4. "Governance is the most critical factor for long-term investment — if governance is unfair, the protocol can easily be forked, and value flows to competing networks." (Chris Burniske) — Technology is the entry ticket, but governance determines who survives.

5. "The NVT ratio (Network Value to Transactions) is the P/E ratio of crypto assets; Bitcoin has historically bottomed around 50." (Chris Burniske, citing Willy Woo) — NVT surges after a bubble bursts but softens before the burst (arbitrage trading inflates the denominator).

6. "The most realistic existential risk is not a 51% attack or regulation, but kidnapping core developers." (Chris Burniske) — ASIC capacity constraints make a 51% attack hard to sustain; regulation is a whack-a-mole game; personal attacks are the most feasible threat.

7. "If velocity is infinite, M = PQ ÷ ∞ means the token's value goes to zero." (Chris Burniske) — Therefore, protocols should embed mechanisms to reduce velocity (e.g., staking), and investors prefer lower velocity.

8. "Someone will win a Nobel Prize for this — maybe not me, but someone in the crypto space will win it in 10-20 years." (Chris Burniske) — Analogous to the Black-Scholes model, crypto asset valuation requires its own theoretical breakthrough.