
1/ Buy-and-burn is becoming the default ‘capital return’ strategy in crypto. I think this is a big mistake. Stop it. Get some help. Profitable protocols shouldn’t shrink their balance sheets when they can do productive things instead.
Carlos Zendejas
2.1K posts

@CLZen
CEO & Co-Founder at Deep Q Digital | QBTC -- Quant Trading + AI + Nebraska Cornhuskers are my happy place

1/ Buy-and-burn is becoming the default ‘capital return’ strategy in crypto. I think this is a big mistake. Stop it. Get some help. Profitable protocols shouldn’t shrink their balance sheets when they can do productive things instead.

We price the future. Now you can lever it. Perps are coming to Polymarket. Sign up for early access 👇

1/ PropAMMs and the Next Chapter of Permissionless Market Structure For years, onchain trading won on access, lost on execution. Some feel better performance requires moving backwards to centralized systems PropAMMs on @solana are proving permissionless can outcompete centralized


Ten executives and employees from four cryptocurrency market-making firms—Gotbit, Vortex, Antier, and Contrarian—have been indicted by the U.S. Department of Justice for allegedly manipulating token trading volume and prices through wash trading. Three of the defendants have been extradited from Singapore to the United States.




Meanwhile on LinkedIn (This is a 24 year old with zero finance experience. Yes I am a patronising old git. No this won't end well)


Vanderbilt wins that game easy if it’s played and reffed on a neutral court

Quant interview question: Describe what factors you use. What is your most profitable signal? Can you explain how it works?





I feel like I google "Tesla minivan" every other week. When is Mr. Pro-Natalist @elonmusk going to make an 8-seater Tesla?

You're not "smart" if you don't know about these 4 formulas - the code is here - Quants now use the Monte Carlo method most often, but there are 3 other high-quality formulas besides it. So you don't trade on Polymarket or another prediction markets as if it were a biased coin. // • 1. Probability assessment (Monte Carlo) \[ \hat{p} = \frac{1}{N} \sum_{i=1}^{N} 1_{\{A_i\}} \] - What it does: Calculates the probability of an event through simulations. - How to use it: If you are modeling an outcome (e.g., a macro event, elections, BTC > 100k), you get a numerical estimate rather than a “70% feeling.” Compare: - Your estimate is 0.68 - the market is 0.61 = if the difference is stable → an edge is possible. • 2. Standard error of estimate \\[ SE = \\sqrt{\\frac{p(1-p)}{N}} \\] - What it does: Shows how noisy your estimate is. - How to use it: If you got 0.68, but SE = 0.02, and the market is 0.66 → your edge is within statistical error. This protects you from entering trades without a real advantage. • 3. Brier score \[ BS = \frac{1}{N} \sum (p_i - y_i)^2 \] - What it does: Checks whether your predictions are really accurate. - How to use it: Write down your probability before entering. After resolution, calculate the Brier score. If your Brier score is worse than ~0.20 → you are not systematically outperforming the market. This is a filter for the illusion of edge. • 4. effective sample size (particle filter) \\[ ESS = \\frac{1}{\\sum \\tilde{w}_i^2} \\] - What it does: Shows how “live” your probability update is when new information comes in. - How to use: If you update the probability based on news/data: Don't react to every price movement; the estimate should change in proportion to the strength of the signal. This protects against: Emotional overreactions and noise trading. // You must study the article by @gemchange_ltd if you want to use quantum formulas.