Matic

币圈爆仓后做陪玩赚钱，赚了钱的快来消费。好玩不贵！！！！

[Nico @nicos_ai]

GOOGLE HA LIBERADO EN SILENCIO UNA IA QUE PREDICE PATRONES

Ventas. Precios de mercado. Tráfico web.
Demanda energética. Volatilidad cripto.

Se llama TimesFM:

→ Entrenada con 100B de datos reales
→ Forecasting zero-shot, sin fine-tuning
→ Corre en local.

100% Gratis y Open Source.

Enlace abajo👇

[Alter Ego @AlterEgo_eth]

How to Turn Ensemble Underdispersion into Consistent Profit on Polymarket Temperature Markets (BLACK BOX STRATEGY)

If you’re still trading Polymarket temperature markets using only a single number from GFS or ECMWF - you’re leaving one of the fattest and most sustainable edges of 2026 on the table

The real quant alpha on the 24–48 hour horizon isn’t in the temperature itself. It’s in Ensemble Spread and especially in Underdispersion - when the model shows a too-narrow range while reality is much wider

>Why This Works So Well on Short Horizons

On tomorrow and day-after-tomorrow markets, chaos hasn’t fully kicked in yet, so:

• Ensembles frequently underestimate real uncertainty (underdispersion)
• The market sees a “tight” forecast and heavily overprices central buckets
• Tail buckets (extremes) end up ridiculously cheap

This is a repeatable mispricing that happens almost every single day

> How to Exploit Underdispersion in Practice

1. Look at raw ensemble spread

GEFS (31 members) + ECMWF ENS (51 members) are your main sources

2. Compare the width of the distribution

• If ensemble spread is only 3–4°C but historically in this synoptic situation it should be 6–8°C → strong underdispersion signal

• When the model is “too confident” - tails are almost always underpriced by the market

3. Simple entry rule

High underdispersion + tail buckets trading below 12–14 cents = aggressive buy

Central buckets are usually overpriced in these moments

> Real example (NYC, max temp for day after tomorrow):

• ECMWF mean = 23°C, spread only 3.8°C
• Historical spread in this setup ~7°C
• Market pricing the >27°C bucket at 7 cents

Tail was heavily undervalued. These setups deliver excellent edge

> Mini-formula for your bot

dispersion_ratio = historical_typical_spread / ensemble_spread
if dispersion_ratio > 1.6 and tail_price < 0.13:
edge = high # enter

You can layer NGR (Non-homogeneous Gaussian Regression) on top - it quickly corrects underdispersion and makes probabilities much more honest

> When This Edge is Strongest

• Transition days (fronts, air mass changes)
• Cities with complex local effects (NYC, LA, Hong Kong, Cape Town)
• Day-after-tomorrow markets - where spread adds the most value

This approach barely depends on latency. You can even enter several hours after a new run and still keep the edge

Underdispersion + proper calibration is one of the few strategies that still works consistently in 2026, even after most latency edges have died

Save this post - you’ll want to come back to this black box strategy

[石头 @Stone141319]

石头量化回测实验室 v2.1 上线，已开源欢迎大家交流使用！！！现在新版本已经支持自动生成网页分析报告（具体可以看截图）。昨天开源的第一版反馈还不错，由于我也是新手第一次开源分享，总感觉自己做的不好，所以我昨晚又强迫症发作，把它升级到了 v2.1，希望能把它做的越来越完美，如果能够帮助到大家，欢迎点点关注，感谢支持！！

这次主要做了三件事，现在它已经从一个基础回测脚本，进化成一个本地策略体检工具了👇

1. 网页可视化报告
以前看回测结果，基本就是盯着一堆数字看，收益多少、回撤多少、交易多少，看完还是有点抽象。

现在回测结束后可以直接生成 HTML 报告，打开就能看收益卡片、资金曲线、回撤曲线、盈亏分布、K 线图、入场标记、因子差异和全部交易明细。

策略怎么赚钱，在哪里亏钱，哪几笔交易比较离谱，现在都能直接看出来。

2. 参数研究与鲁棒性测试
加了参数网格搜索、遗传算法风格参数探索、Monte Carlo 鲁棒性模拟、多参数组合自动排名、策略得分和尾部风险分析。

这块我主要想解决一个问题：
一个策略看起来赚钱，到底是逻辑真的有效，还是刚好撞上了一组幸运参数。

很多回测最骗人的地方就在这里，换几个参数还能不能活，换个市场环境还能不能扛住，必须拆开看。

3. 真正的 Walk-forward 验证
核心引擎新增了 --start-date 和 --end-date，现在可以按真实时间窗口切数据。

一段时间训练参数，下一段时间验证结果，然后窗口继续往前滚动。

这比拿最近 N 天反复测要严谨很多，也更接近真实交易里的决策过程。

——————————————————

目前 v2.1 已经支持： OKX 现货 + USDT 永续、链上 Token（GeckoTerminal）、DEX Pool、多币种组合、多空双向、完整成本建模（手续费+滑点）、动态杠杆/保证金、止盈止损、时间退出、回撤熔断、常见因子内置、参数搜索、Monte Carlo、Walk-forward，以及一键生成 HTML 可视化报告。

这次升级之后，我对它的定位更清楚了，它成为了一个策略体检工具。

收益率只是第一眼，后面还要继续看成本能不能扛、回撤能不能接受、参数有没有过拟合、换个环境还能不能活、每一笔交易到底发生了什么。

后面我会继续把它当成自己的策略实验室慢慢打磨。

开源地址： https://t.co/8L2pYo189n

有需要的朋友可以直接 clone 跑起来试试，跑完欢迎提 Issue 或反馈建议～

如果这个工具对你有帮助，也欢迎点个关注，谢谢大家的支持！
#量化交易 #回测工具 #加密货币 #开源

[加密晚风 @Min040824]

百年数学封神！马尔可夫链Bot 30天狂赚46万美金，碾压人工交易

真正顶级的交易套利，从不靠预测行情，而是靠百年硬核数学模型吃尽市场低效红利。

1922年离世的俄罗斯数学家安德烈·马尔可夫，当年用于研究随机过程的数学公式，在百年后的Polymarket预测市场，成为了最强收割武器。

顶级量化Bot Bonereaper，依托马尔可夫链模型交易BTC、ETH一小时级别行情，30天净利润高达468228美元。

交易账号：https://t.co/IY3lYiULuo

核心交易数据

- 累计交易：14671笔
- 固定下单仓位：1500–2900份
- 运行模式：24小时每分钟高频扫描市场

独家双重入场铁律（必须同时触发）

这套Bot从不猜涨跌、不赌方向，只抓市场定价失衡漏洞，双条件严格风控入场：

1. 概率缺口达标：Δ = p̂ − q ≥ 0.05，出现明确套利价差
2. 市场状态稳定：p(j, j) ≥ 0.87**，行情状态足够稳固无波动风险

双条件同时满足，系统自动秒级进场，零犹豫、零情绪化操作。

碾压人类的核心优势

人会休息、会疲惫、会主观预判行情，但市场永不眠。

凌晨低谷时段，散户全面停盯盘，5分钟级别币价最容易出现定价错位。而这正是该Bot的核心套利窗口——精准捕捉「市场休眠、流动性真空」的低效时刻，低位卡位收割收益。

顶级交易真相

绝大多数人交易亏损，败在主观预判、情绪博弈、盯盘滞后。

而这套百年马尔可夫链模型，只用纯粹的概率数学、稳态逻辑、高频执行力，系统性吃掉预测市场的所有漏洞。

不用比别人聪明，只是把百年经典数学原理，落地在了普通人看不懂、抓不住的市场空档里。
机器守规则，数学定胜率，时间换复利。

[Roan @RohOnChain]

GOLDMAN SACHS open-sourced most dangerous quant repo on the internet.

THE EXACT FRAMEWORK THEIR INTERNAL DESKS USE TO BUILD &amp; RUN TRADING STRATEGIES.

They even left their Claude skills inside. Plug them in &amp; you've a Goldman Sachs quant building strategies for you. BOOKMARK.

[Paone @paonx_eth]

found a polymarket setup that pays out whether bitcoin goes up OR down

you buy YES and NO on the same market at the same time - if both fill under 100c total, you collect 100c no matter what happens

i didnt believe it either, so i ran it 52 times

45 wins, 7 losses, 86% hit rate. and the 7 losses only happen when one leg fills and the other doesn't - which a stop loss handles

the math is simple:

-> YES at 20c + NO at 20c = 40c locked in
-> market resolves, the winning side pays 100c
-> you keep the 60c gap, every time both sides fill

the catch:

doing this by hand on 5-minute markets is impossible. the prices move too fast to place both legs in time

@TycheTerminal automates the whole thing. you set the two prices and a stop loss, it works the recurring markets on its own

this 86% run was its limit-bid mode on autopilot

right now almost nobody is running this. that's exactly why the gaps are still there

test it yourself: https://t.co/qSQXjGTrk4

[阿台BlueBird🕊️ @QT9277]

「负债狗救命稻草」。零成本做视频

说白了就是个零成本自动做视频的神器，TikTok、Reels、YouTube Shorts 一条龙全自动。素材、剪辑、配音、字幕，你只管输入文案，剩下的它全包了。

GitHub 标星已经冲到 13k+，免费、开源、还能本地跑，不用充一分钱会员。

对于阿台我这种在币圈亏成狗的穷逼来说，这就是天上下来的馒头。

零成本，能白嫖就绝不花钱。 具体咋用，自己点进去看：
🔗 https://t.co/QmhJaDfjoc

[Dexter's Lab @DextersSolab]

There's a way to win on Polymarket no matter who wins.

Buy YES in one place, NO in another.

If they don't add up to a dollar, you locked a profit.

Before the event even happens.

Here's how the arbitrage actually works and how to master it:

This is the closest thing to free money on Polymarket.

Every market has a YES and a NO.

One of them MUST resolve to $1.
The other goes to zero.

So in theory, YES + NO should always cost exactly $1.

But in thin or messy markets, they don't.

Sometimes you can buy:

> YES at 0.48
> NO at 0.49
> total cost: 0.97

This guy does it every day: [https://t.co/DtRLSFXsGs]

He also uploaded a full guide on how to build the same bot.

One side pays you $1 at resolution no matter what.

He spends 97 cents to guarantee a dollar.

That 3 cents is locked, risk-free.

There's also the cross-market version.

The same event sometimes has two separate markets at different prices.

Buy the cheap YES in one, the cheap NO in the other, and pocket the gap.

Sounds easy, right?

But here's the honest part:

These gaps close in about 2.7 seconds now.

By the time you click by hand, a bot already took it.

So the manual version only really survives in low-liquidity markets the bots ignore.

The fast version?

That lives in compiled code with a VPS sitting next to the exchange.

If you can code, this is one of the cleanest edges i know.

If you can't, stick to the thin markets where speed matters less.

Good luck!

[孤桜ETH @GYLQ520]

搞 AI 算命这行的朋友注意了，这个开源项目可能就是你要找的那块拼图。

有人把倪海夏《天纪》那套体系整个搬进了代码里——51.8 万条命盘样本、四化飞星规则、1100 多行格局判定逻辑，连骨髓赋原文都一并塞进去了。

想自己搭排盘网站的直接拿去用，想训练命理 AI 的直接当语料。TypeScript 写的，Next.js 14 框架，代码质量不用操心。

🔗 https://t.co/brV0QTxge0

[Blockchain Surfer ☝️ @0xSurferX]

i'm 21.

dropped out of the university.

started vibe coding and tried prediction markets.

studied the simplest arbitrage.

now my bot is printing $600 daily.

life hits different now.

[Punisher @0x_Punisher]

6/7 AI models agree your strategy is a winner.

Feels bulletproof, right?

But it's confident garbage.

Here's why consensus doesn't fix a broken backtest:

The setup looks perfect.

A swarm of frontier models analyzes the trade, votes and spits out a clean confidence score.

6 out of 7 say go.

But voting does not create truth.

It just averages whatever the models were handed.

So what were they handed?

The same broken backtest every AI runs.

It looks at your entry price and the resolution price, draws a straight line and calls it a win rate.

That's the whole model.

No order book depth.
No fill probability at your price.
No latency and slippage.
No adverse selection.

Seven models staring at the same fantasy will confidently agree on the same fantasy.

Garbage in, consensus garbage out.

A vote is not a backtest.

It's seven opinions about a number that was already wrong.

You don't get real confidence by adding more models.

You get it by adding real data.

Record the actual book at every tick.

Model real fills, real slippage, real latency.

Then ask one honest question instead of seven flattering ones.

My sweeper bot hit $27k PnL only because of right backtesting and tool.

Here's the one i use: <https://t.co/crzsdhL1YE>

It helped me develop my sweeper so now it prints passively.

The only thing left for me is just monitoring and updating.

Public wallet: <https://t.co/yCsjRsOAXJ>

The market does not care how many models agreed.

It only cares what your order actually hit.

Leaving a full guide on how to build your own sweeper bot below.

[Gary💙CoinAnk @garyvgroup]

我问你赚了还是赔了，你说悟了是什么意思？

你如果现在开始每天打开CoinAnk学习5分钟，你会得到：

一星期后，你大概了解了交易逻辑
一个月后，你可以选择成为一个KOL。
三个月后，你超越了90%的散户。
六个月后，你会是一个合格的交易员

牛市来临，你会加入A9的行列，所有教程免费。

[Punisher @0x_Punisher]

I made 6 figs on Polymarket bots.

And i only used 2 indicators.

Hedge funds running cross-platform arbitrage use the exact same 2.

Different scale, identical conclusion.

Here is what they both landed on:

Forget RSI, MACD, EMA, every indicator built from price.

They are all just past price, smoothed and rewrapped.

One signal wearing five hats and lagging more with each one.

The only things that carry real information are the ones that read order flow.

The first is OBI.
Order book imbalance.

It compares the resting volume on the bid side versus the ask side.

If buyers have 100,000 contracts stacked and sellers have 1,000, price is mathematically pressured to move up before a single trade prints.

I use it as his final go or no-go before entry.

The hedge funds compute it across two platforms at once to predict which book moves next.

Second is the flow actually hitting that book.

The dev calls it CVD, the running total of market buys minus market sells.

The funds call it the micro-price, the true value once you weight each side by its volume.

Different names, same job.

They tell you who is actually being aggressive, not just who is resting an order.

OBI shows you the pressure.
CVD and micro-price show you whether that pressure is real or bluffing.

One reads the standing book.

The other reads the live attack on it.

Put them together and you know the next move before the chart does.

This is exactly what my sweeper bot is doing before executing.

Public wallet: <https://t.co/yCsjRsOAXJ>

The people winning at every level figured out the same thing.

Stop staring at the chart.
Start reading the book.

That's it.

Go through a full guide if you wanna deep dive into bot building.

[Recogard @recogard]

I found 7 free Polymarket trading bots on GitHub for 7 different trading situations…

Each of these bots comes with a detailed step by step setup and usage guide in English:

1. This bot includes 118+ ready to use strategies and tools for trading on prediction markets (Momentum, Binance-Polymarket latency, Penny Clipper, Smart Routing, Expiry Fade, DCA bots and more).

Built by a Cambridge computer science student who won a hackathon with this trading bot.

GitHub: https://t.co/2MCzD8iZG7

2. This bot automatically manages all your Polymarket limit orders to maximize liquidity rewards.

GitHub: https://t.co/nvb96dTIwx

3. A weather bot from a Chinese dev, that analyzes multiple sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the most accurate temperature data and generate a detailed weather report for a specific city and day.

GitHub: https://t.co/No3sBcqMg1

4. A bot that automatically searches for arbitrage opportunities between Polymarket and Kalshi.

GitHub: https://t.co/icWBTLTeVg

5. This is a bot-toolkit that includes copy trading, arbitrage, market making, whale alerts, spread farming, sports trading and more…

GitHub: https://t.co/p3obYeQTzO

6. A smart money trading bot - it looks for the most successful traders in selected markets, filters them by Pnl + win rate, and then creates a list for automated copy trading.

GitHub: https://t.co/qbk9l2uxLd

7. A large collection of 20+ free trading bots for prediction markets.

GitHub: https://t.co/a2WRRl8PJl

Every bot here has a Dry Run mode, so you can test it on real markets without risking any funds.

[0xSLEEPY（互fo） @PapiSleepy_RF]

这哥们用 Claude 写了个交易机器人，在 Polymarket 上已经赚了 11.5 万美元。

他的机器人专做短期的加密货币“涨 / 跌”市场，单笔交易中位数大概 5.2 美元，同时还把方向性交易和对冲结合着来。

他的策略其实不复杂：

> 用限价单进场
> 拿 BTC / ETH 的实际价格跟 Polymarket 上的价格做对比，买入被低估的那一边
> 一旦出现反转的风险，就反手再买另一边

靠着这套策略，他硬是跑出了持续的胜率，本金也跟着一直往上涨。

[Blockchain Surfer ☝️ @0xSurferX]

https://t.co/m9dJtoeEZV

[MOSS 中文 @MossAI_CN]

https://t.co/BjBkEkJ2WB

[Punisher @0x_Punisher]

AI will build you a Polymarket bot in an hour.

Then it will quietly make you poor over the next month.

You won't even see how.

Here are the 4 places your bot betrays you:

> Backtest is a fantasy

Ask AI to backtest and it does one thing:

Looks at your entry price, looks at the resolution price, draws a line between them.

"81% win rate, you're a genius."

No fill rates.
No order book depth.
No other bots taking your spot.

Your real number is 20 points lower and you deploy on the fake one.

> It overfits and calls it alpha

AI is a ruthless optimist.

Give it data and it finds tiny loophole pockets to drive a train through.

"Skip 17c up bets on Tuesdays for +38% ROI."

All bs that dies the second it touches a live market.

Bots that survive use 1 or 2 signals.
Not 9 filters stacked on a coincidence.

> Same input, different output

Trading needs determinism.

Same input must always give the same output.

LLMs don't work like that - ask twice, get two answers.

A bot that sometimes does something different is not a strategy.

It's uncontrolled risk wearing a strategy costume.

> It drags you into complexity

AI loves to add hedging, rebalancing, merging, cross-window arb, five signals.

It sounds smart and feels productive.

None of the top bots do any of that.

Every layer you add is one more thing that breaks at 3am while you sleep.

So should you stop using AI?

No, use it.
Just stop trusting it with the parts that matter.

> Let it write the plumbing

> Never let it near your edge or your backtest

> Force it to use TOML files, it kills almost all the drift.

> More than 2 signals? AI tricked you so rip them out.

I've built 1,000+ bots already.

The ones that print are the dumbest ones (the ones I let AI touch the least).

Take my sweeper bot as example: <https://t.co/yCsjRsOAXJ>

AI will hand you a bot but it will never hand you an edge.

That part is still on you.

Go through my last article if you wanna understand what 2 indicators determine EVERYTHING.

Attached below.

[Mr.RC｜𝟎𝐱𝐔 @MrRyanChi]

最近我合伙人在世界杯市场上疯狂印钱，赚的快要比我们做产品赚的多了。@dakshbigshit

我昨天终于问到了他的prompt

“对2026年世界杯进行深度FIFA分析。首先，分析第一轮（Matchday 1）已完赛的全部8场小组赛：
- A组：墨西哥 2-0 南非；韩国 2-1 捷克
- B组：加拿大 1-1 波斯尼亚；瑞士 1-1 卡塔尔
- C组：巴西 1-1 摩洛哥；苏格兰 1-0 海地
- D组：美国 4-1 巴拉圭；澳大利亚 2-0 土耳其

对每场比赛的投注进行深度分析：胜平负/独赢盘、亚洲盘、大小球（O/U）、双方进球（BTTS），以及任何你认为合适的盘口。核查这些比赛中获胜的投注者——他们是否在接下来即将开打的比赛盘口中建立了仓位？

需要预测的即将开打的比赛：
- 6月15日（周一）：西班牙vs佛得角、比利时vs埃及、沙特vs乌拉圭、伊朗vs新西兰
- 6月16日（周二）：法国vs塞内加尔、伊拉克vs挪威、阿根廷vs阿尔及利亚、奥地利vs约旦
- 6月17日（周三）：葡萄牙vs刚果（金）、英格兰vs克罗地亚、加纳vs巴拿马、乌兹别克斯坦vs哥伦比亚

给我一个关于这些比赛的精准聪明钱信号。过滤掉流动性提供者（LP）、机器人（bots）和做市商（MM）——我要的是真正的聪明钱。找到阿尔法（alpha），按需要做尽可能多的深度分析。刷新你的上下文，使用尽可能多的上下文窗口，进行自我讨论和辩论。

我有100美元。告诉我该押哪个/哪些盘口，以及如何分配本金。”

使用场所：https://t.co/sZBx1QwtZ8
直接发送prompt就可以了

[Dexter's Lab @DextersSolab]

You don't need to predict the future on Polymarket.

You just need to know how often history repeats.

The crowd trades feelings and headlines.

You trade the numbers they keep forgetting.

Here's the base-rate edge NO ONE told you about:

Most people open a market and ask what will happen.

Wrong question.

The right one is how often has this happened before.

That's a base rate.
And Polymarket is full of markets that ignore it.

Take politics.

The president's party almost always loses ground in the first midterm.

It's one of the most reliable patterns in modern history.

Yet each one gets priced like a fresh coin flip.

Or correlations:

> when a party wins the White House, they take the Senate around 85% of the time

> some outcomes basically drag others along with them

The crowd treats these as separate guesses.
They're not.

Here's the method:

> find the market
> pull the actual historical rate
> compare it to the current price
> trade the gap

If history says 85% and the market says 65%, you found an edge.

No prediction.
No insider info.
Just public numbers most people are too lazy to check.

Same boring logic behind those monthly "Largest Company" markets.

Market link: [https://t.co/BAVBElY3VM]

NVIDIA wins every time statistically.

Or the Jesus Christ market where we made 3x multiple times just after i warned you (will be quoted below).

Market link: [https://t.co/MjImaHDhhP]

History rhymes.
Prices forget.
You profit from the gap.

The gap is the trade, that's it.