Blockchain Analytics to Help Curb Crypto Misuse, Says HashCash CEO

Since the crypto industry is growing at a frantic pace, blockchain analytics can help fill the void of curbing money laundering and cybercriminal activities, according to Raj Chowdhury, the CEO of HashCash Consultants.

“There has been a conscious effort in implementing stricter crypto regulations worldwide. Blockchain analytics will play a crucial role in decision-making processes for organizations dealing with crypto and blockchain technology,”  said Chowdhury. Blockchain analytics is believed to be constructive in establishing order and propelling sustainable growth in the crypto sector. 

Blockchain analytics render actionable insights that help enterprises comply with regulatory protocols regarding cryptocurrencies. Chowdhury said:

“The playing field required for innovation must not compromise the achievements we have made so far. Like any technology, blockchain is not immune to misuse. Hence the regulation is a necessity not only for AML compliance but also for developing blockchain research and the global crypto-community.”

As the cryptocurrency space continues grappling with the challenge of various lending and DeFi projects facing bankruptcy, Chowdhury has advocated the importance of crypto education when averting high-APY DeFi scams.

Rand Low, a quantitative risk modeller and senior fellow at the University of Queensland Business School, recently highlighted the importance of regulation and capital controls in fast-growing crypto lending platforms.

Low acknowledged that this would prevent depression and crashes in the market because the uncertainty rocking crypto lending entities like BlockFi, CoinLoan, and Celsius Network was causing panic selling. 

A recent Wall Street Journal (WSJ) report disclosed that Celsius took more risk than it could handle because it had a total asset base of $19 billion. In contrast, its equity contribution was pegged at just $1 billion. Therefore, blockchain analytics can help prevent such trends by rendering more transparency and insights. 

Image source: Shutterstock


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Bitcoin’s Correlation to Tech Stocks Surges Amid Macro Uncertainty: Analytics Firm IntoTheBlock

The price of Bitcoin (BTC) is increasingly correlating with that of tech stocks amid widespread uncertainty in the crypto markets, according to analytics firm IntoTheBlock.

In a new article, the market intelligence agency says that Bitcoin’s congruence with the Nasdaq 100 has reached a level it hasn’t seen in nearly two years and that the anticipation of looming regulations is causing investors to be skeptical.

“Bitcoin’s correlation vs the Nasdaq 100 reached its highest level since April 2020…

Now that artificially high monetary conditions are coming to an end, uncertainty is growing and buying interest is fading in anticipation of rate hikes and quantitative tightening.”

Source: IntoTheBlock

The market insights platform also says that based on their In/Out of the Money metric, they can find BTC’s key support and resistance levels.

“Based on this, we see high resistance around $38,000 where 1.27 million addresses previously bought 835,000 BTC. If Bitcoin clears that level, a move to $42,000 is likely.

On the other hand, some support can be expected at $35,000 where 291,000 BTC was acquired by 714,000 addresses. If this level fails to hold, Bitcoin should revisit its recent lows.

Momentum is still on the bearish side, though, with twice as many Bitcoin holdings near current price being held by addresses losing money on their positions.”

IntoTheBlock adds that investors can expect a potential upcoming supply shock of BTC due to the rate at which traders are currently moving the top crypto asset by market cap out of exchange platforms and into cold wallets or yield-generating protocols.

“Comparing the drawdowns experienced during May-July of last year and the current, the exchanges’ net flows paint [this] picture:

Between May and June of 2021, there were significant inflows of Bitcoin into exchanges (net amount of 130,000 BTC), coinciding with the sell-off that happened during that period.

This time, net outflows of 80,000 BTC suggest that less Bitcoin is available to buy at exchanges, as users tend to move these assets to cold storage or yield-generating strategies.

Ultimately, this suggests strong buying activity from holders, resulting in a potential supply shock as Bitcoin shifts from being held by short-term speculators to long-term investors.”

Bitcoin is exchanging hands at $41,490 at time of writing, an over 10% increase from its seven-day low of $36,920.

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Valuing Bitcoin Based On HODLer Behavior

October 25, 2021

Defining Money

After 12 years of adoption, the concept of bitcoin as digital money is now widely known. Ironically, when learning about bitcoin, many individuals are forced to (re)consider what money is. One example of a definition that they may run into is:

Bitcoin’s digital nature allows a seamless transfer of value across space. Its 21 million maximum supply makes it dilution-resistant and perfectly scarce, also allowing it to maintain purchasing power over time ​​— assuming the future demand does not decline. So far that hasn’t been the case.

Quite the opposite, actually. In a world that is choking on the side effects of endless money printing and ever-growing mountains of debt, bitcoin’s hard money properties give it a gravitational pull from which it is difficult to detach. The resulting adoption improves its salability and market liquidity, repeatedly opening doors for even larger market participants to dip their toes into a pool that keeps expanding.

With bitcoin currently being added to the balance sheets of publicly traded companies and even countries, an increasing number of people are trying to answer the question “what gives bitcoin value?” and thus what a fair price is.

Valuing Bitcoin

When Bitcoin was just one week old, Hal Finney became not only the first person besides Satoshi to mine bitcoin and receive the first transaction, but also the first to publicly speculate about its long-term value. By comparing its target market to a rough estimate of the worldwide household wealth, he envisioned a potential $100 trillion to $300 trillion market cap, which would give bitcoin a value of around $10 million per coin.

Since then, there have been many attempts at modeling both the short-term and long-term bitcoin price. Perhaps the most well-known models are the Stock-to-Flow (S2F) and S2F cross-asset (S2FX) models by PlanB that predict a price for the current halving cycle (2020-2024) of around $100,000 and $288,000, respectively. Although the statistical and methodological validity of either model can be debated, the models facilitated a narrative around scarcity as the central property that gives bitcoin value.

Others have attempted to predict the bitcoin price via regression models that use time as an input variable. However, the predictions of time-based models tend to vary depending on the time period that is used as input for the model, providing unstable predictions based on methodologically invalid models.

Another approach is to extrapolate futures price via statistical regression, but to adaptively value it in comparison to a baseline for “fair value” that adjusts as more information becomes available. An example of such a dynamic model is the Bitcoin Price Temperature (BPT), which attributes a relative valuation to price in comparison to its four-year average. Since the bitcoin price tends to move in four year cycles (at least historically), comparing prices to their four-year trend can help estimate how overheated or undercooled prices are. A downside of using just price is that it assumes that these trends are stable, which is not necessarily the case. Changes in market participants’ behavior can completely reverse a previously strong trend, which such purely price-based valuation models are only sensitive to after a lag.

An interesting aspect about Bitcoin is that its timechain is a public ledger of all transactions that were ever made. It provides a database about which legacy economists can only dream. In February 2017, Willy Woo first leveraged this by introducing the Network Value to Transactions (NVT) Ratio. In doing so, Woo pioneered the on-chain analysis field that has become very popular since then. The NVT Ratio compares the value of the bitcoin market to the value of all coins that are transacted weekly. Therefore, this models the bitcoin price based on one of the defining properties of money: the ability to transfer value.

Since the introduction of Woo’s NVT Ratio, Lightning Network adoption is changing Bitcoin’s on-chain footprint. An increasing amount of value is no longer being transacted directly on-chain but flows via channels on a layer on top of Bitcoin. As a result, the NVT ratio is gradually losing accuracy, creating a need for us to come up with alternative valuation methods.

HODLer Behavior As A Measurement Stick

If scarcity is a key aspect that makes a money valuable by allowing it to transfer value across time, investigating the behavior of those that have provably experienced this use case may provide meaningful insights into how it is valued by those that seem to understand it.

In March 2020, on-chain data intelligence company Glassnode made a first attempt at this. By analyzing the age of bitcoin transactions, they found that above a cut-off point of around 155 days, unspent transaction outputs (UTXOs) had a very low likelihood of moving on-chain again. Based on this, they created a metric they called Long-Term Holder (LTH) supply, which is the total amount of bitcoin that falls into this basket. In November 2020, Glassnode improved upon the metric by no longer looking at individual UTXOs, but instead utilizing (proprietary) algorithms and on-chain forensics to look at the average coin age of entities instead. They also applied a more fluid threshold for coins to age into this LTH supply.

A month later, in December 2020, Glassnode again iterated upon this concept by introducing a new metric called illiquid supply. Where the LTH supply looks at an entity’s average unspent bitcoin age, the illiquid supply looks at the entity’s spending history and classifies the entity as either illiquid, liquid or highly liquid. Figure 1 displays the circulating bitcoin supply (black), LTH supply (blue) and illiquid supply (red).

Figure 1: The circulating bitcoin supply (black), illiquid supply (red) and long-term holder supply (blue)

Figure 1: The circulating bitcoin supply (black), illiquid supply (red) and long-term holder supply (blue)

As can be seen in Figure 1, Glassnode’s algorithm for the illiquid supply appears to apply a more liberal method when it comes to classifying an entity as unlikely to spend.

Knowing how much supply is in the hands of these long-term holders and illiquid entities, we can calculate the Long-term holder Value (LV) and Illiquid Value (IV), which represent the total value of the LTH and illiquid supply (LTH or Illiquid supply * price), respectively. Since the bitcoin price can be volatile, applying a moving average over the LV and IV is helpful to better grasp its long-term trends. Figure 2 visualizes the LV and IV with a 1-year moving average that accounts for seasonal effects (e.g., seasonal effects on bitcoin mining, tax seasons, etc) on a yearly basis.

Figure 2: The bitcoin Market Value (MV, black) and 1-year moving averages of the Illiquid Value (IV) and Long-term holder Value (LV)

Figure 2: The bitcoin Market Value (MV, black) and 1-year moving averages of the Illiquid Value (IV) and Long-term holder Value (LV)

As can be seen in figure 2, the yearly average of the total value of the bitcoin supply that is in the hands of long-term holders and illiquid entities tends to be where the bitcoin price finds support during market downturns.

The reason for this can be attributed to a phenomenon called “HODLing,” which stems from a meme that finds its origin in a 2013 Bitcoin Forum post. Historically, bitcoin bear markets have proven to be tough, causing it to be declared dead 432 times at the time of writing. During bear markets, speculators that only bought bitcoin to try and get rich quick sell their coins. As a result, the market is flooded with excess supply that it may have difficulty absorbing after overly euphoric market conditions when the demand from these same speculators that drove up price falls away. Price then trends down until the low-conviction holders are all shaken from their positions and only “HODLers of last resort” remain. By holding onto their coins no matter what, this group effectively sets the price floor that was visualized in Figure 2. After all, thanks to the inelasticity of the bitcoin supply, price can only move up when there are no sellers left while there still is some demand.

Comparing Market Value To Illiquid And LTH Value

Similar to how David Puell and Murad Mahmudov created the Market-Value-to-Realized-Value (MVRV) Ratio that the anon account “Awe & Wonder” then standardized into the MVRV Z-Score, it is possible to compare the bitcoin market value to the illiquid and LTH value.

This is done by first calculating the difference between the Market Value (MV) and the Long-term holder Value (LV) and Illiquid Value (IV), respectively. That number is then divided by the standard deviation of the MV, creating the Market-Value-to-Long-term-holder-Value (MVLV) and Market-Value-to-Illiquid-Value (MVIV) metrics. The resulting MVLV and MVIV metrics therefore represent the number of standard deviations that the market value is (over)extended in comparison to the total value of the LTH and illiquid supply (figure 3).

Figure 3: The Market-Value-to-Illiquid-Value (MVIV) and Market-Value-to-Long-term-holder-Value (MVLV) metrics

Figure 3: The Market-Value-to-Illiquid-Value (MVIV) and Market-Value-to-Long-term-holder-Value (MVLV) metrics

Due to the similarity in the LV and IV metrics, both fundamentally and data-wise, the MVIV and MVLV are similar metrics, where the MVIV is the most expressive. The choice to use either should be based on the degree to which one feels that coin ageing should be considered to determine whether an entity is likely to sell their coins since that aspect is more strongly reflected in the LV than in the IV.

Both metrics allow historical comparison of the overall market value in comparison to the value of the supply that is in the hands of entities that are unlikely to sell. As can be seen in Figure 3, bear markets tend to bottom out at values around 0 (which is the 1-year moving average of the IV and LV itself) and have historically topped out at values of about 8 and higher. Although the cyclicality in Bitcoin’s market valuation is mesmerizing and seduces many to assume that history will repeat, there are no guarantees that this (four-year) cyclicality will necessarily continue.


Now that we have a metric that quantifies the relative valuation of the bitcoin market in comparison to the value of the LTH and illiquid supply, it is possible to map the bitcoin price at each respective MVIV/MVLV level on top of the price chart, allowing us to graph how much room for growth or decline there is for price to reach certain MVIV/MVLV levels again. This was done before with the BPT Bands and MVRV Bands that were discussed above.

This is done by adding a multiple of the standard deviation of MV to the IV or LV itself, where the multiple represents the MVIV/MVLV value that you want to visualize. The resulting numbers are then divided by the circulating bitcoin supply to get the valuations per bitcoin. When plotted on top of the price chart, these values represent the “Bands” in the MVIV Bands and MVLV Bands concepts that are visualized in Figures 4 and 5, respectively.

Figure 4: The bitcoin price (black) and Market-Value-to-Illiquid-Value (MVIV) Bands (colored)

Figure 4: The bitcoin price (black) and Market-Value-to-Illiquid-Value (MVIV) Bands (colored)

Figure 5: the bitcoin price (black) and Market-Value-to-Long-term-holder-Value (MVLV) Bands (colored)

Figure 5: the bitcoin price (black) and Market-Value-to-Long-term-holder-Value (MVLV) Bands (colored)

Comparing Floor Models

With the MVIV and MVLV Bands added to the mix, we now have four bitcoin valuation models that each use different baselines to estimate its “fair value.” Figure 6 displays the baseline values of the MVIV, MVLV, MVRV and BPT Bands models.

Figure 6: The bitcoin price (black) and the 0-bands of the MVRV (blue), MVLV (green), MVIV (orange) and BPT (red)

Figure 6: The bitcoin price (black) and the 0-bands of the MVRV (blue), MVLV (green), MVIV (orange) and BPT (red)

As can be seen, the MVRV Bands baseline is the most responsive, since it is the only metric that does not include a one-year (MVIV & MVLV) or four-year (BPT) moving average component.

While relevant, that does not necessarily mean that it is the superior model to rely on. As can be seen in Figure 6, the baselines of both the illiquid and LTH supply value are currently above that of the MVRV, which has historically only briefly occurred late 2014 and late 2018 during peak bear market conditions, and never during a market uptrend towards all-time highs as is currently the case.

An explanation may be that a shift in how the world sees bitcoin may be happening. As can be seen in Figure 7, the trends for the percentage of the circulating bitcoin supply that is not on exchanges (blue) or that is labelled illiquid (green) have dramatically changed since roughly March 12, 2020.

Figure 7: The illiquid and non-exchange supply as a percentage of the circulating bitcoin supply (source)

Figure 7: The illiquid and non-exchange supply as a percentage of the circulating bitcoin supply (source)

On that day, global financial market sell offs triggered a cascade of long liquidations that took the bitcoin price down over 50% in two days and cleared the market of all excess leverage. Since then, publicly traded companies and now even a country have adopted bitcoin, while central banks have turned on their money printers heavily in their attempt to combat the economic downturn, creating a gigantic asset bubble instead.

In a time where bitcoin is making strides to replace gold as the go-to hard money shelter against monetary inflation, an increased adoption of bitcoin as an asset to transfer value over time means that coins become less likely to move on-chain. That trend may be exacerbated by Lightning Network adoption, which reduces the need to transact on-chain even further. As a result, unspent transactions may take more time to realize value via an on-chain footprint as is quantified in the MVRV metric. Simultaneously, their likelihood of being included in Glassnode’s illiquid or LTH supply increases.

If these trends continue, it is possible that the MVRV baseline will start lagging and that the presented MVIV and MVLV metrics may provide a more reliable estimate for the bitcoin floor price. It is therefore nice that we now have multiple similar options to fall back on that utilize this valuation method from different angles. For the time being, these metrics are very similar — especially when the bitcoin market value deviates further from the respective baselines (Figure 8).

Figure 8: Bitcoin MVRV, MVLV, MVIV and BPT metric comparison

Figure 8: Bitcoin MVRV, MVLV, MVIV and BPT metric comparison

The similarity between the floor models that are depicted in Figure 7 and the resulting metrics of Figure 8 can also be seen as a form of confluence. The MVRV, MVLV and MVIV all incorporate the lifespan of the underlying coins. These metrics therefore reflect investor time preference and hold valuable information about the relative bitcoin valuation in comparison to the price floor that is set by HODLers.

A limitation of the presented MVLV and MVIV Bands metrics that we need to be cognizant of is that proprietary algorithms were used by Glassnode to construct the illiquid and long-term holder supply metrics. It is likely that Glassnode will keep improving upon those algorithms to optimally service their clients, which would mean that both future and historic values may be subject to change over time. Charts representing MVIV and MVLV (Bands) metrics therefore should be seen as a snapshot in time that uses the most up-to-date method to quantify the supply that is in the hands of entities that are unlikely to spend it, and not to be compared to prior visualizations of the same metric.

At the time of writing there is no web-based version of the metric available yet (Glassnode’s Workbench currently does not support an expanding standard deviation), but the R code for the metrics and charts presented here is available on GitHub.

Special thanks go out to @Anoi30604540, @_Checkmatey_ and @WClementeIII for providing feedback on the draft of this article.

Disclaimer: This article was written for educational and informational purposes only and should not be taken as investment advice.

This is a guest post by Dilution-proof. Opinions expressed are entirely their own and do not necessarily reflect those of BTC, Inc. or Bitcoin Magazine.


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Coinbase signs new $1.36M contract with US Customs enforcement agency

Leading U.S. cryptocurrency exchange Coinbase has secured a contract to develop tech for the Department of Homeland Security worth as much as $1.36 million.

Under the agreement, Coinbase has been contracted to deliver “application development software as a service” for the U.S. Immigration and Customs Enforcement division (ICE).

The contract took effect on Sept. 16 and will see Coinbase receive $455,000 from the department. However, the contract could be extended to last for up to three years in total, which would see Coinbase receive up to roughly $1.36 million.

The deal is the second partnership inked between Coinbase and ICE, with the exchange having secured a $30,000 contract to provide “computer forensics services” to the agency in August.

The news has received backlash from the crypto community, with Human Rights Foundation chief strategy officer Alex Gladstein asserting the compensation is relatively low given the scale of Coinbase’s operations and the reputation risk posed to the exchange by the partnership:

“This isn’t very much money for Coinbase in the grand scheme of things. Strange that they would risk much reputationally such a relatively small sum.”

The news has also resurrected criticisms concerning Coinbase’s 2019 acquisition of blockchain analytics startup, Neutrino.

During the year of the acquisition, it was reported that the people behind Neutrino had previously been part of Hacking Team — a company revealed to have helped authoritarian regimes to spy on journalists.

Neutrino CEO, Giancarlo Russo, was the ex-COO of Hacking Team while its CTO, Alberto Ornaghi, was at the company for more than 8 years. According to the Washington Post, the Italian company was implicated in the murder of a number of journalists in the Middle East between 2013 and 2018.

In March 2019, Coinbase CEO Brian Armstrong said that Neutrino staff with prior connections to controversial firm Hacking Team would transition out of their new roles at the exchange.

Responding to Coinbase’s new contract with ICE, Kraken CEO Jesse Powell, tweeted:

“Even more bizarre is the acquisition they made and reputational hit they took to be able to offer this service to the government.”

Related: Coinbase CEO Defends Licensing of Analytics Platform to Gov’t Agencies

Since its acquisition of Neutrino, Coinbase has also inked contracts with the U.S. Secret Service — which announced the creation of a Cyber Fraud Task Force in July 2020. The task force has been mandated to investigate the use of cryptocurrency for criminal purposes, stating later that year:

“Cryptocurrency presents a troubling new opportunity for individuals and rogue states to avoid international sanctions and to undermine traditional financial markets, thereby harming the interests of the United States and its allies.”

Coinbase is currently embroiled in a regulatory tussle with the Securities Exchange Commission, with the regulator taking umbrage with its planned stablecoin lending product and threatening to take the company to court.