Mr. Quant | Minara QR @MrTokenAI

Appreciate the time you spent testing the product. Minara already models fees, funding, borrow and slippage, supports out-of-sample and walk-forward testing, and carries risk controls from paper to live execution. Capacity modeling and proprietary inputs are valid requests, and we’re building them. The article benchmarks an accessible research platform against a full institutional stack, then treats the gap as proof that the product has no value. I don't think it makes any sense. What Minara does is make the research loop much faster: find factors (coming soon), turn them into strategies, backtest, test live, learn, and repeat. Faster iteration doesn’t guarantee alpha. But it gives you more shots on goal, and a better chance of finding it. BTW if you can't make a good one, feel free to subscribe or fork mine: minara.ai/app/strategy/d…

Regardless, I have initiated a partial position in SK Hynix during today’s Korean market session as a tactical entry.

After SK Hynix and Micron experiencing ~50% drawdowns, an interesting pattern emerged⬇️ From the start of this memory bull market (Apr 2025 → now) and the earlier breakout (Aug 2024 → now), Fibonacci retracement levels appeared to mark key support zones. During tonight’s selloff, both stocks bottomed almost precisely at major Fib levels (0.5 / 0.618 / 0.786) across different timeframes, then bounced sharply. Coincidence, or did Fibonacci once again identify the bottom? Keep a close eye on tech fundamentals and the Fed’s next moves in the coming weeks.

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We can create a model to follow correlation of price and funding rate to adjust arbitrage position dynamically.

@riuonsol Maybe this is the reason x.com/TechFlowPost/s…

TechFlow 深潮｜APP 已上线 @TechFlowPost

2 weeks ago

Hyperliquid 上，多头正在宣誓效忠长鑫存储，而空头正在顶着极高费率做空。 CXMT 永续合约的资金费率目前打到了 -0.1775%，年化算下来是 -1552%。 这是什么概念？如果你拿 1 万美元做空，按这个费率每次结算就要给多头交 17.75 美元。一年交 15 万。 你猜头铁的做空派来自哪里？ 据 Allium

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A -0.2% Funding Rate means A 2000% APY for long position of $CXMT

$GOOGL reported earnings today: EPS: $9.11 actual vs $2.91 expected - retail reactions to EPS blowout is kinda just accounting noise, since $SPCX, Anthropic, and others were likely large contributors. Revenue: $119.7B actual vs. $116.98B expected Google Cloud Revenue: $24.77B +82% Y/Y, vs. 63-65% expected ($22.2-$22.6B) - this is a very large beat and most material part so far. Cloud Operating Income: ~$8.81B, implying 35.6% margin vs. 32.9% Q1. Capex: $44.92B vs ~$44.15B (basically in line). So initial read through is Google Cloud accelerating growth with expanding margins is genuinely bullish for AI demand. Their former $180-$190B capex guidance is already extremely large, and as long as we get around these numbers in the earnings call + forward projections... Should be good to go for $LITE and the other optics/networking trade. (eg. last earnings, they said DC and networking would be ~40% of capex spend). Hyperscaler earnings transcripts are probably the most important thing to pay attention to with the AI capex trade. And that should be in 3 minutes.

$INTC and $AMD to sign CPU LTAs with Chinese customers for AI DCs (Reuters). - Prices of some CPU products have risen more than 40% in China since the start of the year from sources. - Month-on-month increases topping 10% for some products CPUs were already a bottleneck, following CPU ratios due to AI inference... But the broader trend of LTAs seems to be appearing from: - Memory, with $MU, Samsung, $SNDK, and SK Hynix signing DRAM/NAND LTAs. - Photonics, with $LITE, $COHR signing EML LTAs. And recent Trendforce reports that $AMD and hyperscalers are now pursuing CW LTAs. And I'm sure there's many more from MLCCs to all the way to substrates. +1 for the bottleneck investors... hard to be a "bubble that pops" if you have take or pay demand spanning multiple years.

传说中的 122% 年化 BTC 策略上线了！ 不会还有人不知道@circle支持的 AI 策略平台 @minara 能跟单，根据一句话、一个想法、自由创建属于你的策略吧？ 我刚上了我的策略回测两年拿到了高达 1000% 的年化，在广场获得了最佳回报徽章！ // 大家可以来跟单👇 策略一、 $BTC 122% 年化 minara.ai/app/strategy/d… 策略二、 $HYPE 44% 年化 minara.ai/app/strategy/d… // 从现在起叫我策略大神 ✌️

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Minara AI @minara

4 weeks ago

Welcome our very first batch or strategy creators 🫡 Explore their strategies and more at ↓ minara.ai/app/top-strate… 👀

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x.com/i/article/2077…

Introducing Minara Strategy Marketplace: where alpha, edge, and capital meet.✨ All the best strategies from the best traders, now open to everyone. Follow, fork, or run them directly in your Minara autopilot. Traders earn a profit share without leaking their code. Subscribers get the best-performing strategies, validated on-chain. It's a new paradigm for strategy sharing. It's a new era of financial equality. It's Minara Strategy Studio 2.0. 🔮

Hold $ORCL for 6 months: -6.26%. A strategy we built in Strategy Studio, same window: +84.44%. Same Ticker. Two outcomes. Code in the next tweet. Want to build your own?↓ strategy.minara.ai

A good time to add more dots.

Finally, CLARITY🇺🇸🧙‍♀️

Chainlink @chainlink

3 months ago

JUST IN: The U.S. Senate Banking Committee voted to advance the CLARITY Act to the Senate floor.

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已经不止有多个项目找我测一测他们的AI trading架构了 我就简单说几点吧 1. 拿长期实盘出来,短期妖币这种没有 max dd 的不代表什么,幸存者偏差而已。随便挑一个已经归零的币倒着回测,曲线一样漂亮 2. 如果 Sharpe ratio > 5,基本上可以确定是过拟合、look-ahead bias 或者数据泄漏。Medallion 常年也就 2-3,你一个人在家跑出 7,自己心里要有b数 3. 你拿一段 crypto bull market 的数据去测,和你拿一段大类市场的数据回测是不一样的,完全的 overfitting,基本我不看。最起码 2018、2022 两轮熊市能走通,再跑一轮 walk-forward,才算一个策略 4. 手续费、滑点、funding rate 都得建进去。Binance 的 maker/taker、VIP 档位、BNB 折扣一层层算下来,模型不准的话 backtest 和实盘能差出一倍年化,这是常态 5. 策略容量比收益率更值得看。10 万刀跑得动,不代表 100 万刀还能跑。小币深度就那么点,你一进场自己就把自己的信号打掉,backtest 里完全 reflect 不出来 6. 确实 crypto quant 没那么卷,但套利机会一直在被蚕食——funding arb、现货期货 basis、跨所价差,基本已经被做市商和 HFT 吃干净了。高频做不了,纯因子也没空间,剩下能做的只有趋势和 mean reversion 这两条老路 7. Alpha 有半衰期。策略上线三个月还能跑,算及格;半年还在,算不错;一年还有,大概率是运气好或者你的规模还没到引起注意的量级。别把一次 bull run 的红利当永续 alpha，你还没有那么牛逼 8. Grid search 出来的"最优参数"99% 是过拟合。真正稳的参数,是你在一个区间里随便挑都能跑,而不是精确到小数点后两位才 work。参数稳健性比单点收益重要一百倍,这点做过的人都懂 9. 2017 ICO、2020 DeFi summer、2021 meme、2022 LUNA/FTX、2023 AI 叙事,每一段市场结构完全不同。你在上一段拟合出来的"规律",换个 regime 直接归零,还倒亏手续费 10. 交易所风险永远比你想的大。FTX 归零、API 限流、插针爆仓、小所跑路、币安突然下架,这些都是"一次就结束游戏"的事。你年化 50% 抵不过一次交易所暴雷,这跟策略多牛逼没关系，做山寨的就要考虑到流动性和“下架风险” 11. backtest 上曲线波动看着很美,真到自己账户里连续三周净值下跌,90% 的人会关掉程序手动调参 12. 分清楚你赚的是 alpha 还是 beta。牛市里所有人都是 quant 大师,熊市一来只剩 beta 的人全被冲走。把多头暴露剥离出来单独看 alpha 曲线,大多数所谓"策略"根本没 alpha,就是变相 long BTC 加一点波动率。 13. ML 在 quant 里有大量虚假繁荣。LSTM、Transformer、强化学习被吹上天,实际在 SNR 极低的金融时序上,一个朴素动量因子加合理风控,能打过你调一万次的 XGBoost 真JB学习起来，quant是真的难得一笔

@creatine_cycle Partly Solved

@MartinShkreli @minara solved🧙‍♀️

Quant trading is solved. Introducing: Minara Strategy Studio. Design strategies, backtest, compare PnL, avoid brutal drawdowns, optimize parameters, go live, all in plain words. Join the closed beta: strategy.minara.ai 🧵

x.com/i/article/2046…