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How Cryptocurrencies Gain Value

How a cryptocurrency gains value is a mechanical question, not a mystical one. This page is the spine of a short series that expands the Matrix from what these chains are into how any of them comes to be worth something. It is written for someone who has never traded, and it gives no price predictions.

The short version: a coin has no value because it exists. It gains value when somebody wants it more than they want what they are holding, and the only place that preference becomes a number is a market. Everything below is about where that wanting comes from, and what turns it into a price that holds.

1. Price is made at the edge, not across the supply

The first thing to unlearn is the headline figure. Market cap is supply × last price, and the last price is whatever one person most recently paid for possibly one coin. It is not a pile of money that exists somewhere. The Matrix page shows what that does at our own scale, and Market Cap vs Fully-Diluted Valuation takes the measurement apart.

Price is set at the margin: by the best bid and the best ask sitting in the order book right now, and by whoever crosses the spread. A coin with a half-billion supply and a coin with seventy thousand can print the same last price while describing completely different objects. The number that tells you whether a price is real is not the cap — it is the depth, covered in Volume, Liquidity, and Depth.

2. Where demand actually comes from

There are only a few honest sources of sustained demand, and it is worth naming them separately because they behave differently.

A chain that has only the third and fourth gets a price and loses it. A chain that has the first two can survive the absence of the others, which is the whole design argument for building sinks before building hype.

3. The velocity problem — why "lots of people using it" is not enough

This one is counter-intuitive and it defeats a lot of well-meaning token designs.

If a coin is used purely as a medium of exchange — you receive it, you immediately spend or sell it — then the same coin can service an enormous amount of activity while almost nobody ever holds it. High velocity behaves like a larger effective supply, and value per unit falls even as usage climbs. A token can be genuinely busy and genuinely worthless at the same time.[1]

The fix is a reason to stop moving — a "velocity sink": staking, locking, collateral, a fee that consumes the token, a game that takes it out of your hands for a while.[2] Every design on this chain that looks like friction — staking LP to earn MWALI, veKULA locking, the burn in the lottery — is a velocity sink wearing a different hat.

4. Value accrual, and the honest limits of burning

"Value accrual" is the question of whether activity on the system reaches the token at all. A protocol can be enormously used and its token capture none of it.

The common tools are buyback (protocol revenue purchases the token on the market) and burn (supply is destroyed). The serious literature is more sceptical of these than crypto marketing is, and the caveats matter:

[7]

[8]

[9]

<ref>This project's "Economics 101" Bitcointalk thread (immakingacoin, 2018) — the toll-booth/immigration-line framing of the Bitcoin fee bottleneck, the BitPay $100 floor, and the monopoly-chokepoint argument</ref>

The rule that follows, and the one this ecosystem actually encodes in its contracts as `MintSinkGuard`: every emission is paired with a sink. A burn financed by real usage is a different object from a burn announced to move a price. Ours are the former by construction — the lottery burns MWALI that was earned by supplying liquidity, so the burn is a by-product of the thing being used.

Low float, high FDV, and the unlock cliff

The most documented way a token is destroyed is not a hack — it is its own supply schedule, and it is worth understanding before judging anybody's launch including ours.

The pattern: launch with a tiny circulating float against a large total supply. The small float makes the first price easy to push up, and multiplying that price by the full supply produces an enormous fully diluted valuation. Then the locked supply unlocks on a schedule, and every unlock is new sell-side pressure arriving on a book that never grew to match. Binance Research described exactly this in May 2024 — low initial circulating supply inflating the launch price, with steady unlocks creating structural downward pressure afterwards.[7]

The outcome data is bleak. Keyrock found that 88% of tokens launched with airdrops declined in value, most of them crashing within 15 days, and attributed much of it to thin liquidity rather than to the airdrop itself; lower-FDV launches eroded far less.[8] A separate analysis of 16,000-plus unlock events reportedly found negative pressure beginning around 30 days before the unlock date, as the market front-ran it.

The counterpoint, which belongs here because a one-sided version of this would be propaganda: an analysis by Gate found that float size at launch did not meaningfully predict appreciation one year out, and that only about a third of tokens retained value since their first airdrop — suggesting float is one variable among several rather than the cause.[9]

Why it is on this page: it is the exact inverse of the design argument in Holders, Rarity, and Distribution. A low float with a big unlock queue is scarcity that expires. A float that is small because coins are staked, locked or burned by people using the system is scarcity that has to be undone one decision at a time by thousands of separate people. Those two charts look identical on day one and diverge completely afterwards, and the thing to check in any project is simply: is the supply off the market because somebody chose to use it, or because a contract has not released it yet?

5. Fees, bottlenecks, and the demand that lands on other coins

This is the demand source nobody puts on their tokenomics slide, and it is the one that built most of the altcoin market.

The toll booth

A blockchain fits a limited number of transactions in a block. When more people want in than there is room, a queue forms, and the fee becomes the priority lane — the toll booth and the immigration checkpoint described in Economics 101 and 102 §7. Pay more and you are waved through; pay too little and you wait or get returned.

The miners run the booth. They choose which transactions go in, and they choose by fee, because they want more money — which is not a conspiracy, it is the incentive the system was built with. A block space auction run by people paid from the auction has exactly one direction under congestion.

What that looked like on Bitcoin at peak congestion: $5 or more to send anything, more for speed, low-fee transactions rejected and returned, and BitPay refusing payments under $100 because the fee ate the value of the payment.

The economic consequence: the fee becomes a price floor on usefulness

A transaction fee is a minimum viable transaction size. At a $5 fee, no sane person sends $3. Every use case below the fee is not made expensive — it is abolished. Tipping, micropayments, posting, voting, small in-game actions, paying a creator a dime: all of it stops existing on that chain, at that price, no matter how much anyone believes in it.

And the demand does not evaporate. It moves. People who need to do small things with money go and find a chain where small things are affordable. That is not speculation and it is not loyalty — it is someone with a job to do, choosing a cheaper tool, which makes it the stickiest demand in crypto. It also means a congested chain's fee market is a continuous subsidy to its competitors.

Why this is the structural argument for the chains we run

Usability is throughput plus fees, and the Graphene design answers both: four-second blocks and no per-transaction fee at all. Instead of auctioning block space to the highest bidder, bandwidth is rationed by Resource Credits that regenerate against your staked coin. See MELEK Blockchain and Graphene Blockchain Framework.

Read that as a pricing mechanism rather than as a feature and the significance is clearer. On a fee-market chain you rent access, repeatedly, from miners, at a price that rises exactly when the network is most useful. On a Resource-Credit chain you hold access: stake the coin once and the capacity is yours, permanently, regenerating. That converts the fee from an operating expense paid to miners into a reason to acquire and hold the coin — which is a utility in the §2 sense, and the cleanest one there is.

The honest limits, because this cuts both ways:

6. What is already running, and what is being built on top of it

The markets here are young and thin — that is a measurement, and §1 through §5 are mostly about reading it correctly. It is not the same thing as having no market, and the difference matters because the machinery below is live, on-chain and checkable right now.

Running today, with addresses and counters anyone can read:

What is still being built is the demand side, and Utilities and Sinks lists it with the status of each item marked, including the parts that are specified and not deployed.

So the four things a young chain actually controls:

  1. Scarcity that is real rather than claimed — no pre-mine, supply that is earned. MELEK's live supply at the time of writing is 2,527,236.964 MELEK at block 1,932,147, all of it issued by the chain rather than allocated to founders.
  2. Distribution — more holders, each holding less. The reason is arithmetic and it is in Holders, Rarity, and Distribution.
  3. Places to spend it — the utilities in Utilities and Sinks, built before the demand they are meant to serve.
  4. Depth in the two-sided market — a bid and an ask have to exist before a price does, and then the book has to get deep enough that the second trade is worth making. That is what KulaSwap and the gauge are for.

The current prices, named

Read from the live markets on 30 October 2026. HIVE's median feed is $0.048 per HIVE, which anchors the engine side in USD.

A correction to an earlier revision of this section. It published KULA at $3.4450 × 10⁻¹⁷ and wMELEK at $4.0000 × 10⁻¹⁸. Those were wrong by a factor of 10¹⁰. `wVKBT` and `wCURE` are 8-decimal tokens while KULA, WPRANA and wMELEK are 18-decimal, and the first pass divided every raw reserve by 10¹⁸. The figures below use each token's own `decimals()`.

Observed prices — an actual trade happened at these:

{| class="wikitable"

! Asset !! Last trade !! USD !! Top bid

|-

| VKBT || 0.00000041 HIVE || $0.0000000197 || 0.00000041 HIVE for 3,220,171 VKBT

|-

| CURE || 0.00002220 HIVE || $0.0000010656 || 0.00002350 HIVE for 444 CURE, then 0.00002342 for 5,000

|}

Theoretical prices — no exchange listing required. `wVKBT` and `wCURE` can be bridged back and sold on Hive-Engine, so the KulaSwap reserve ratios convert KULA, WPRANA and wMELEK into USD by arithmetic. On an AMM the reserve ratio is the price.

Spot ratios from the exact reserves:

{| class="wikitable"

! Asset !! via the wVKBT route !! via the wCURE route

|-

| KULA || $3.444977 × 10⁻⁷ || $4.546614 × 10⁻⁷

|-

| wMELEK || $4.001149 × 10⁻⁸ || $5.280638 × 10⁻⁸

|-

| WPRANA || $5.372137 × 10⁻⁷ || —

|}

And it gives a market cap

Two different derivations, and it matters which is which.

VKBT and CURE are capitalised on Hive-Engine itself — no bridge, no pool, no PRANA. Supply × the last traded price, denominated in HIVE, then converted at the median feed:

{| class="wikitable"

! Token !! Supply !! Cap in HIVE !! Cap in USD

|-

| VKBT || 2,352,205 || 0.964404 HIVE (× 0.00000041) || $0.046291

|-

| CURE || 72,440 || 1.608168 HIVE (× 0.00002220) || $0.077192

|-

| CURE at the top bid || 72,440 || 1.702340 HIVE (× 0.00002350) || $0.081712

|}

MELEK, KULA and WPRANA are capitalised through the pools, because they have no direct listing — supply × the theoretical price derived above:

{| class="wikitable"

! Asset !! Supply !! Cap (wVKBT route) !! Cap (wCURE route)

|-

| MELEK || 2,527,236.964 || $0.1011 || $0.1335

|-

| KULA || 267,009.132 || $0.0920 || $0.1214

|-

| WPRANA || 13,001.000 (the wrapped portion only) || $0.0070 || —

|}

The two pool routes run through different pools and different anchor assets and land within 32% of each other, which is the check that makes them usable. A further cross-check: pool 3 prices wCURE at 40.36 wVKBT against the engine market's 54.15, so the wrapped pools sit at about 75% of the market ratio.

A caution that applies to every row above, and it is the point of Volume, Liquidity, and Depth: a market cap is supply × a price, and the price is the last marginal trade. These caps describe what the supply would be worth if all of it could clear at that price, which it cannot — the next section shows a single unit losing half its value to slippage.

What one MELEK actually realises

The spot ratios above are quotes. This is the executed number, using the Uniswap-V2 constant-product formula with its 0.3% fee and the exact reserves:

  1. 1 wMELEK → 0.054937471 KULA in pool 4. Note why the loss is so large: pool 4 holds 0.90000000 wMELEK, and `wMELEK`'s entire total supply is 0.90000000 — all of it is in that pool. A single unit entering is more than the whole reserve, so it moves the price the full quadratic amount described below.
  2. Then either:

#* → 0.9587454 wVKBT in pool 1. Sold at the 0.00000041 HIVE bid (which has depth for 3,220,171 VKBT): 0.0000003931 HIVE = $0.0000000189.

#* → 0.02336881 wCURE in pool 2. Sold at the 0.00002350 HIVE bid (depth 444 CURE): 0.0000005492 HIVE = $0.0000000264.

So one MELEK, bridged, swapped and sold, realises about $0.0000000264 on the better of the two routes. Spot said $0.0000000528 — the realised figure is 49.9% of spot, and the 50.1% difference is slippage in pool 4, entirely because the swap is larger than the reserve it hits. The sell side on Hive-Engine is not the constraint; the bids absorb these sizes with room to spare.

Why early chains reprice by orders of magnitude

This is arithmetic, not optimism, and it follows directly from §1: price is made at the margin.

On a constant-product AMM, buying against a reserve moves the price quadratically. If `Rx` is the reserve of the asset you are spending and you spend `Δx`:

new price = old price × (1 + Δx / Rx)²

{| class="wikitable"

! Buy size (× the quote reserve) !! Price multiple

|-

| 0.5× || 2.25×

|-

| 1× || 4×

|-

| 2× || 9×

|-

| 10× || 121×

|-

| 100× || 10,201×

|}

Applied to the deepest pool we have — pool 0, quote reserve 10,661.9964 WPRANA:

And on the engine side the same effect runs through the float rather than a pool. CURE's liquid float is roughly 20,800 units, which at $0.0000010656 is $0.0222 in total. $1,000 of buying is about 45,117× the entire liquid float. There is no amount of supply to absorb it at anything like the current price.

This is the mechanism behind the price history in Economics 101 and 102 and in §6 of Mining Hardware, ASICs, and the Cost of Production: Bitcoin went $5 → $30 → $100, then to a thousand, then to ten thousand, through the era when the whole network was small and the float was held by a few thousand forum readers. Each of those steps looked impossible from the step below it — the operator's own account records Bitcointalk regulars arguing it would never reach $1,000, then never $10,000. The repricing was not sentiment outrunning arithmetic; it was arithmetic. A small float plus a quadratic price-impact curve means new capital arriving produces multiples, not percentages.

The same formula is symmetric, and that is the whole reason Volume, Liquidity, and Depth exists: the multiple that takes a price up on the way in is the multiple that takes it down on the way out, and depth decides which direction you can actually transact in. The figures above are what a thin market looks like in both directions at once.

7. Read next

Not investment advice

This page explains mechanism. It is not a claim that any token here is undervalued, not a prediction of any price, and not a suggestion to buy or sell anything. Education and mechanics are in scope; individualised financial advice is not.

Sources

[1]

[4]

[3]

[5]

[2]

[6]

[10]

The Matrix: Supply, Holders, and Market Cap">[11]

Coverage

Covers the five sources of demand including fee-driven flight from congested chains, price formation at the margin, the velocity problem and velocity sinks, value-accrual mechanisms with the sceptical literature on burns and buybacks, the low-float/high-FDV unlock failure mode with its counterpoint, the fee-bottleneck argument for Resource Credits with its honest limits, and what a pre-market chain can actually build. Live supply figure captured 30 October 2026; treat it as of that date. Gives no valuation verdicts and predicts no prices.

Videos

Watch videos about How Cryptocurrencies Gain Value on YouTube ↗

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References

  1. https://www.freecodecamp.org/news/single-biggest-problem-with-token-models-part-2-52c0eca2115c
  2. https://superex.medium.com/superex-educational-series-understanding-velocity-sink-9445ead6dceb
  3. https://23stud.io/blog/how-to-design-token-economics-that-work
  4. https://members.delphidigital.io/reports/more-than-just-governance-unpacking-value-accrual-mechanisms
  5. https://chainscorelabs.com/blog/history-of-money-and-the-crypto-thesis/monetary-evolution-and-scarcity/why-tokenomics-often-gets-scarcity-wrong
  6. https://arxiv.org/pdf/2601.09961
  7. https://www.binance.com/en/research/analysis/low-float-high-fdv-how-did-we-get-here
  8. https://keyrock.com/insights/airdrops-are-they-worth-it/
  9. https://www.gate.com/learn/articles/low-float-high-fdv-is-it-really-the-culprit/
  10. Live chain read: melek.salon/rpc `get_dynamic_global_properties`, block 1,932,147, 30 October 2026
  11. [[The Matrix: Supply, Holders, and Market Cap]]

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