Harga TreatTREAT

𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐄𝐜𝐨𝐧𝐨𝐦𝐢𝐜𝐬 𝐚𝐧𝐝 𝐓𝐨𝐤𝐞𝐧 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝟏. 𝐅𝐫𝐨𝐦 𝐂𝐥𝐚𝐬𝐬𝐢𝐜𝐚𝐥 𝐭𝐨 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐓𝐨𝐤𝐞𝐧 𝐌𝐨𝐝𝐞𝐥𝐬 Classical economics assumes rational actors, perfect information, and linear decision-making. Quantum Economics says instead that agents exist in overlapping states of preferences, with behavior influenced by observation, uncertainty, and context. Tokens create environments where utility, speculation, and governance are entangled. Users hold contradictory intentions simultaneously. 𝟐. 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬 𝐚𝐧𝐝 𝐓𝐡𝐞𝐢𝐫 𝐄𝐜𝐨𝐧𝐨𝐦𝐢𝐜 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭𝐚𝐭𝐢𝐨𝐧 𝟑. 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐓𝐨𝐤𝐞𝐧 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐃𝐞𝐬𝐢𝐠𝐧 • Multi-State Tokens: Tokens designed with dual utility: governance and collateral. • Probabilistic Incentives: Instead of fixed rewards, employ random or probability-weighted token rewards to model uncertainty. • Entangled Token Models: For cross-protocol tokens, LSTs, for example, design systems where burning, locking, or other demand mechanisms for tokens in Protocol A auto-impacts Protocol B. 𝟒. 𝐕𝐚𝐥𝐮𝐞 𝐑𝐞𝐜𝐚𝐩𝐭𝐮𝐫𝐞 𝐅𝐥𝐨𝐰𝐬 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐋𝐞𝐧𝐬𝐞𝐬 Traditional frameworks treat value flow linearly Work → Reward → Exit. Quantum economics operates on a cyclical, recursive value flows. Staking → Restaking → Looping → Yield Farming → MEV Impact Flow direction is probabilistic and reversible. 𝟓. 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞, 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐭𝐢𝐨𝐧, 𝐚𝐧𝐝 𝐌𝐚𝐫𝐤𝐞𝐭 𝐂𝐨𝐥𝐥𝐚𝐩𝐬𝐞 • Observation In tokens: Heavy investor scrutiny (whale wallet tracking, governance vote rumors) changes market outcomes. • Design implication: Need for obfuscation layers or prediction-resistant systems. 𝟔. 𝐓𝐨𝐤𝐞𝐧 𝐕𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐌𝐚𝐫𝐤𝐞𝐭 𝐃𝐞𝐬𝐢𝐠𝐧 Classical discounted cash flow or network models fail in quantum systems. • Suggest a model where the expected value is a probability cloud influenced by events, sentiment waves, and narrative shifts. Finally, tokens aren’t static assets, they exist in overlapping states influenced by narrative, sentiment, and participation. Quantum Economics provides a better lens to model unpredictable markets. Thanks for reading!

More kind of news to confuse people. ✍️ My take is : ranging for couple of days and get the trap even stronger. No key levels as been taken, treat all trade as scalp and manage risk accordingly.

Still not convinced until USDT.D makes another LL and preferably closing below 4.76% There is still that inverted 3 drive pattern in play and all these LL/LH could mislead many traders. Treat all new trades as scalps, either side.

Wtf even is this, and why does it make @JoshMandell6's $444,000 Bitcoin prediction look less crazy? It's been widely observed that Bitcoin's price growth over the last 15 years follows a power curve--something like y=ax^b--which differs from other common functions, such as linear (y=ax) or exponential (y=ab^x). When the relationship between variables is fundamental (e.g., gravitational force F=Gm₁m₂/r²), we often call it a "power law." I'll leave it up to you to decide if this long-term trend qualifies as a "law," but regardless, I find value in the fit due to its longevity. Long-term fits in U.S. dollars are skewed by the changing value of the dollar—see "inflation." One way to adjust for this is to measure an asset’s value relative to an inflation-resistant asset, like the price of an ounce of gold. The idea is that gold’s price should rise to offset the dollar’s decreasing value. Here, I’m measuring the value of the Bitcoin network (market cap) in gold ounces and fitting that value to a power curve. On a log-log plot, a power curve appears as a straight line—see the top left subplot. My preference is to fit the lower values using a 0.05 quantile regression and treat that as a "support" trendline. The white line (upper left plot) is the power curve fit of Bitcoin’s market cap in gold ounces. Today’s fit value is 557,039,533 gold ounces. Since we typically value assets in U.S. dollars, it’s convenient to convert that figure. Knowing the current Bitcoin supply and the current price of gold, we can translate those 557M ounces into dollars: 557,039,533 (gold ounces) × $3,040 (dollar value of an ounce of gold) ÷ 19,839,907 (Bitcoin supply) = $85,353 (BTC-USD fit value). If you repeat this process for all past days, you get the squiggly white support line in the subplot on the right. It’s not smooth because gold’s price isn’t smooth. The blue band represents a time shift of the white support line. Simply slide the white support line left by five years. Each white line in the blue band represents a one-year shift. Doing this, we see that the peak at the end of 2017 (~$20,000) touches the "five years ahead" line. Five years later (end of 2022), the white support line equals ~$20,000. Not every peak reaches five years ahead, but we did once, so maybe we could again. So, what’s the connection to Josh? Coincidentally—if you believe in such things—Josh predicted Bitcoin would hit $84,000 a few days ago (which it did) and followed up with a price prediction of $444,000. That sounds crazy, and it is, but it’s also surprisingly close to the "five years ahead" value shown here ($462,557). Since this fit is relative to gold’s price, gold’s rise from $2,000 (2023) to $3,000 (2025) is pushing the values in the right subplot higher. If Bitcoin’s network value measured in gold continues to follow a power curve, and gold holds its current value, and Bitcoin’s price returns to "five years ahead of support," we could hit Josh’s $444K this year. That’s a lot of "ifs," but it’s fun, and I want to believe.

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