A Primer on Bitcoin Investor Sentiment and Changes in Saving Behavior

  • Relative Unrealized Profit/Loss Ratio (≈investor sentiment)
  • HODLer Position Change (≈insider buying/selling)

A History of Bitcoin Valuation Research

  • In 2010, Bitcoin users tried calculating the “value” of one Bitcoin by estimating the electricity cost of mining it. However, the usefulness of this was quickly dismissed, as the cost of mining goes up when investors bid up the price of Bitcoin.
  • In 2011, early investors came up with the idea of calculating Bitcoin’s market cap as a valuation tool, and with the concept of ‘Bitcoin Days Destroyed’. The latter was dubbed an “indicator of market health and participation and it was the first valuation metric that considered the age of addresses. There was also discussion about a “Price over Difficulty” ratio, to determine whether it was better to mine than to buy BTC, and forum threads emerged about how many lost coins there might be.
  • In 2012, Trace Mayer suggested the 200 Daily Moving Average of Bitcoin’s market capitalization as a value indicator, because it filters out the long-term secular uptrend.
  • In 2013, various authors explored the idea that Bitcoin’s price is in a long-term parabolic uptrend, and that deviation from that trend line is indicative of over- and under valuation.
  • On January 1st, 2014, user gbianchi proposed “Network Value” as the ratio of Bitcoin’s address growth and its market capitalization — similar analyses followed later that year.
  • In November 2014, developer Jon Ratcliff published his analysis of the blockchain, showing the distribution of bitcoins based on age of last use, and commented “This graph shows … how many bitcoins are actively moving at any one time over time.”
  • In September 2017, Willy Woo and Chris Burniske published research around the NVT ratio, which was called a “PE Ratio for Bitcoin” as it focused on comparing Bitcoin’s on-chain volume with its market cap.
  • In March 2018, Dmitry Kalichkin suggested a variation on NVT which he dubbed the 90-day NVT ratio. Two months later he introduced the Network Value to Metcalfe ratio (NVM) which was based on Daily Active Addresses.
  • In April 2018, Dhruv Bansal updated Ratcliff’s work on UTXO age distribution, and suggested the concept of HODL waves. He commented: “It is not possible to make charts such as the one above for traditional asset classes. It’s only Bitcoin and other public blockchains that meticulously track these data throughout their whole histories. This enables post-hoc analyses of large-scale market behavior.”
  • In October 2018, inspired by Pierre Rochard, Nic Carter and Antoine Le Calvez created the Bitcoin “realized cap” which is the aggregate value of the UTXOs priced by their value when they last moved. Soon after, Bitcoin “thermocap” or “accumulated security spend” was suggested, which is the aggregated miner revenues over the entire history of Bitcoin.
  • That same month, Murad Mahmudov and David Puell published work on the Bitcoin Market-Value-to-Realized-Value (MVRV).
  • In December 2018, Tamás Blummer introduced the concept of Liveliness, which reflects how much a given blockchain is used for meaningful transaction settlement.

Goal: Measure Changes in Saving Behavior

Limitations and challenges of existing valuation methodologies

  • With cryptocurrencies, information about real circulating supply is opaque, exchange listing requirements are often extremely loose, and dilution schemes can be stretched to extremes. Assigning a “market cap” to a cryptocurrency (mined coins × token price) doesn’t at all create an objective comparison tool — a coin’s “market cap” doesn’t teach us anything about the commitment of coin holders. To illustrate: a centralized coin with a premined supply of 1 billion tokens and a single recorded sale of one token for $10 would yield a $10 billion market cap, identical to a decentralized coin with a large community of long-term savers. This “market cap” measure is also blind to lost coins, which stretches the comparison with the securities world where the assets are held by transfer agents, making loss a very rare phenomenon.
  • The challenge with using the number of active addresses or transaction volumes (e.g. NVT, NVM) is that these data sources don’t allow us to separate behavior that is long-term oriented from behavior that is short term oriented. These measures don’t directly differentiate speculators from value investors, and can conceivably be gamed or inflated by moving a large amount of coins back and forth, or by creating a flurry of small on-chain transactions.


Relative Unrealized P&L (≈investor sentiment)


  • A blockchain that during its lifetime has not yet seen a transaction other than issuance, has a Liveliness of 0%. Likewise, a blockchain where only one recent balance is systematically moved back and forth would produce a very low Liveliness — in other words, this measure is unforgiving for lack of meaningful transactions. Bitcoin has high Liveliness if it facilitates the transfer of large amounts of old coins on a regular basis.
  • A blockchain where all the coins move within a single block has at that moment a Liveliness of 100%. A blockchain of two years old with no new block rewards, and where exactly one year ago all coins moved within a single block and no transactions moved since, would have a liveliness of 50%. In other words, the measure fluctuates relative to the total lifespan of the blockchain.
  • The total circulating supply also impacts Liveliness: if in the previous example 20% more new coins were created in the year since all the coins were moved, then the Liveliness today would not be 50% but only 40%. So this measure also warns us about blockchains with high inflation/dilution.

HODLer Position Change (≈insider buying/selling)





Bitcoin Alpha, Market Research

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