Curve DAO Token (CRV)

In the previous post, we established why constant product AMMs fail to efficiently handle stable assets, and why @CurveFinance had to rethink the entire pricing problem from first principles. Now we can finally look at what Curve actually built instead. The StableSwap Invariant is a hybrid system that blends two fundamentally different market behaviors into a single continuous curve. To understand why this matters, it helps to revisit the two extremes we discussed earlier. On one end, there is the constant product market maker. It assumes that price should always respond to imbalance. As one asset is removed from the pool, the remaining reserves become increasingly expensive. This ensures liquidity is always preserved, but at the cost of higher slippage. On the other end, there is the constant sum model. Here, trades occur almost perfectly at a fixed ratio. There is virtually no slippage near equilibrium. But this comes at a critical cost: liquidity can be completely drained from one side of the pool witho

In the previous post, we established why constant product AMMs fail to efficiently handle stable assets, and why @CurveFinance had to rethink the entire pricing problem from first principles. Now we can finally look at what Curve actually built instead. The StableSwap Invariant is a hybrid system that blends two fundamentally different market behaviors into a single continuous curve. To understand why this matters, it helps to revisit the two extremes we discussed earlier. On one end, there is the constant product market maker. It assumes that price should always respond to imbalance. As one asset is removed from the pool, the remaining reserves become increasingly expensive. This ensures liquidity is always preserved, but at the cost of higher slippage. On the other end, there is the constant sum model. Here, trades occur almost perfectly at a fixed ratio. There is virtually no slippage near equilibrium. But this comes at a critical cost: liquidity can be completely drained from one side of the pool witho

Altcoins went a bit deeper than initially anticipated but I reentered longs at a better price, exact same setups on both LTC and CRV. Things really looking close to major rallies. https://t.co/nisoHqwFms

In the previous post, we looked at why @CurveFinance was created and the problem it set out to solve. Now let's take a closer look at why existing AMMs couldn't solve that problem in the first place. Most decentralized exchanges rely on a constant product market maker, commonly represented by the formula x · y = k. It's one of the most elegant ideas in DeFi. As one asset leaves the pool, the ratio between the two reserves changes, causing the price to adjust automatically. No order books. No centralized market makers. Just a mathematical invariant that continuously discovers prices through supply and demand. For assets whose prices naturally fluctuate against each other, like ETH and USDC, that model works remarkably well. Price discovery is exactly what the market needs. If demand for ETH increases, the AMM should make ETH more expensive. If demand falls, the price should decline accordingly. The invariant continuously reflects those changing market conditions. Now imagine a completely different market. U

In the previous post, we looked at why @CurveFinance was created and the problem it set out to solve. Now let's take a closer look at why existing AMMs couldn't solve that problem in the first place. Most decentralized exchanges rely on a constant product market maker, commonly represented by the formula x · y = k. It's one of the most elegant ideas in DeFi. As one asset leaves the pool, the ratio between the two reserves changes, causing the price to adjust automatically. No order books. No centralized market makers. Just a mathematical invariant that continuously discovers prices through supply and demand. For assets whose prices naturally fluctuate against each other, like ETH and USDC, that model works remarkably well. Price discovery is exactly what the market needs. If demand for ETH increases, the AMM should make ETH more expensive. If demand falls, the price should decline accordingly. The invariant continuously reflects those changing market conditions. Now imagine a completely different market. U

Over the next couple of days/weeks, I'm going to give you a deep dive into @CurveFinance. By building an understanding from the ground up. My goal is simple, by the end of this series, you should understand not only what Curve is, but why it became one of the most important pieces of infrastructure in DeFi. The more I learned about Curve, the more I realized that it was built to solve a very specific problem and that's exactly why it became so successful. Imagine you hold a million USDC and want to swap it for USDT. On a traditional automated market maker, a trade of that size would move the price significantly. The larger the trade, the more value you lose to slippage. Curve asked a simple question, What if both assets are supposed to have almost the same value in the first place? If USDC and USDT are both designed to trade around one dollar, why should swapping between them become increasingly expensive as trade size grows? That question became the foundation of Curve. Instead of optimizing for eve

Good yields? https://t.co/8Ml2dshKsP

Yes indeed, Curve is live on @RobinhoodApp chain. Happy to see major players joining the future! https://t.co/Iw1tx5iPPA

Yes indeed, Curve is live on @RobinhoodApp chain. Happy to see major players joining the future! https://t.co/Iw1tx5iPPA

$CRV If $0.17 marked the start of the HTF impulsive uptrend, early June’s wave 1 advanced +56% to $0.2655. Wave 2 has retraced -31.68% so far, equivalent to 88% of wave 1’s length. When wave 2 retraces this deeply in an impulse, wave 3 is likely to extend. To estimate an order of magnitude for wave 3 and avoid exiting a trade too early, I apply a mathematical formula based on the Elliott Wave Principle’s equality guideline. Let’s assume wave 4 will retrace a similar percentage to wave 2. In an impulse, wave 4 is not allowed to enter the price territory of wave 1, then the goal is to find the minimum wave 3 top that prevents wave 4 from closing back into wave 1’s territory if it retraces the same percentage as wave 2’s. Formula used: Wave 3 top = wave 1 top ÷ (1 – wave 2 retracement %) With wave 1 top = $0.2655 and wave 2 retracement = 31.68%, then: Wave 3 top = $0.2655 ÷ (1 – 0.3168) = $0.3886 This means wave 3 needs to push beyond ~$0.3886 for wave 4 to be able to retrace the same percentage as wave 2