On top: $NVDA CEO also called out Silicon Photonics (optical networking) with memory.
Stating that Nvidia would require “supply volumes beyond imagination”.
What a bullish read through on the SiPH supply chain from $SIVE (now upstream Nvidia ecosystem) to $SOI
11 free GitHub repos for Polymarket trading…
Here is everything you need to automate and make your trading easier:
1. This is the largest Polymarket dataset with over 107GB of real trading data, based on more than 1.1 billion trades, analyzed by 5 professors from Shanghai University.
GitHub: https://t.co/7hj5ZXRz0K
2. A working backtesting simulator that lets you test your own ideas and strategies on real historical markets to see your potential Pnl and possible risks.
GitHub: https://t.co/fmzzTgXAUl
3. This tool analyzes the real trading behavior of any Polymarket trader, finds repeated patterns in his trades, shows which strategies he uses and how you can adapt them to your own trading.
GitHub: https://t.co/SzdjHtASLt
4. This bot automatically manages your limit orders on Polymarket to maximize liquidity rewards.
GitHub: https://t.co/nvb96dTIwx
5. A weather bot from a Chinese dev that can analyze multiple sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to generate a detailed weather report for any specific city and day.
GitHub: https://t.co/No3sBcqMg1
6. This bot comes with 118+ ready to use automated strategies and tools for trading on prediction markets, including arbitrage between Polymarket and Kalshi, Polymarket - Binance price latency, Mean Reversion and more.
GitHub: https://t.co/2MCzD8iZG7
7. This is a useful tool for building your own AI agents and connecting them to your trading workflow.
GitHub: https://t.co/eItPbDlVhs
8. A trading dashboard where multiple AI agents analyze a selected market from different angles (checking news, price behavior, technical indicators and possible risks) to help you make better decision.
GitHub: https://t.co/02iWujLbxe
9. This tool lets you search for information about any historical market, price or trader across different prediction market platforms inside one dashboard.
GitHub: https://t.co/Z8I3z9sh74
10. This is a trading bot-toolkit that includes copy trading, arbitrage, market making, spread farming, whale alerts and more.
GitHub: https://t.co/p3obYeQTzO
11. The largest public list with 100+ free useful tools and services for Polymarket, from analytics tools and trading bots to AI agents and education resources.
GitHub: https://t.co/jqvVR9106v
All of these repositories are free and come with a detailed step by step installation and usage guides in English.
THE MOST EXPENSIVE ENGINEERING TEAMS ON EARTH JUST PUT THEIR FINANCIAL TOOLS ON GITHUB FOR FREE.
Jane Street. Goldman Sachs. JP Morgan. BlackRock. Hudson River Trading. Two Sigma. D.E. Shaw.
Seven firms. Seven repos. Billions in engineering talent open sourced.
Save this before you scroll past it.
1. Jane Street — magic-trace
5,300 stars. Process tracer powered by Intel PT. When your profiler is blind this sees every CPU instruction.
https://t.co/4CYCLmWNQn
2. Goldman Sachs — gs-quant
Derivative pricing the GS traders use at their actual desks. MIT licensed. Free.
https://t.co/vOxx1zaLFB
3. JP Morgan — perspective
What JPMorgan traders use to watch markets in real time. A $24,000 per year terminal. Available to anyone with a GitHub account.
https://t.co/qGtppfUzmq
4. BlackRock — lcso
Rust optimizer for portfolio problems. Where scipy gives up this works. Built for problems that break standard optimization libraries.
https://t.co/CeR0TNRb58
5. Hudson River Trading — corral
Structured concurrency for C++20. The foundation of HFT infrastructure at one of the largest US trading firms.
https://t.co/aL2Adp6FBL
6. Two Sigma — flint
Time-series joins on Apache Spark with temporal tolerance. Built for billions of ticks. The data infrastructure layer behind systematic trading at scale.
https://t.co/zpkwHOH25D
7. D.E. Shaw — pyflyby
Auto-import for IPython and Jupyter. D.E. Shaw also funded the development of IPython itself. The firm that built the tool is now giving you the enhancement for free.
https://t.co/XjrHTpw8aP
Here is what this list actually represents.
These seven firms collectively employ thousands of engineers earning $300,000 to $1,000,000 per year.
The tools they built to solve their hardest problems are the same tools you now have access to for free.
The information asymmetry that used to separate a quant at Goldman from a developer at home just narrowed significantly.
The infrastructure is free.
The edge now belongs to whoever knows how to use it.
Bookmark this before you pay for another financial data tool.
Follow @cyrilXBT for every elite engineering resource the moment it surfaces.
Hyperliquid is treasury of data. Every stop loss & take profit are available via a hyperliquid node but not via its UI
Today we are releasing realtime TP & SL visualisations for every available HL market
See better what others don't
The Polymarket Cheat Code: How I Used Opus 4.7 To Reverse Engineer A $1.8M Whale
finding every polymarket millionaire with a single script feels like stumbling onto a cheat code in a high stakes simulation. there is a specific wallet out there that just pulled in one point eight million dollars and i have the exact logic to track every move they make before the rest of the world even realizes what happened.
my name is moon dev i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading so i learned to code as in the past i spent hundreds of thousands on devs for app, thinking i would not be able to code myself. with bots you must iterate to success so i decided to learn live on youtube, and now we are here, fully automated systems trading for me instead of getting liquidated.
most traders spend their entire day staring at candles and hoping for a miracle while the real alpha is hidden in plain sight within the blockchain data. once you have the power to scan an entire ecosystem like polymarket you start to realize that the winners are not just lucky they are systematic.
i found a way to filter through thousands of participants to isolate only the top one percent of whales who are actually printing money. this is not about following a random tip on social media but about reverse engineering the actual transaction history of millionaires.
when you look at a guy who has made nearly two million dollars you have to ask yourself what they know that you do not. by pulling their specific wallet addresses into a new tab you can see every event they are betting on and exactly how they are sizing their positions.
there is a massive loop in the market where big money moves in silence before a major political or sporting event hits the news. if you are just reading the headlines you are already the liquidity for someone who saw the volume spike ten minutes earlier.
the gap between a retail trader and a whale is usually just access to information and the ability to act without emotion. code allows us to close that gap by building scanners that never sleep and never get tired of looking for an edge.
i developed a specific whale scanner script that calls my own data api to pull the most profitable traders in real time. you can set the minimum profit and loss to a hundred thousand dollars and suddenly the noise of the market disappears.
most people are too scared to touch the terminal because they think you need a computer science degree to build something useful. the reality is that the new models like opus 4.7 have turned the idea guy into a powerhouse who can ship production code with a simple prompt.
if you are still paying developers to build your ideas you are living in the past and burning capital that could be used to fund your trades. i spent hundreds of thousands on devs before i realized that i could just build the systems myself with a little bit of grit.
the most interesting thing about these whales is that they are often trading across multiple niche markets simultaneously. i saw one wallet averaging down on an international invasion prediction while another was playing high frequency sports outcomes.
you have to be careful when you start copy trading because if you do not understand the slippage you will get destroyed by the time your order fills. the goal is not to blindly follow but to decipher the underlying strategy so you can build your own automated version.
i share all of my code and ideas live because i want to show that anyone can go from being liquidated to being an operator. the secret is that you have to be willing to fail and iterate through a hundred bad bots before you find the one that sticks.
there is a hidden variable in my scanner script that most people overlook which allows you to see the true volume behind a trade. without this variable you are just looking at a surface level number that can easily be manipulated by wash traders.
the prize in this game is unlimited if you have the patience to build out your own infrastructure. jim simons did not become a billionaire by clicking buttons on a phone app he did it by building the most sophisticated data layer on the planet.
we are in a unique window of time where the tools for massive wealth are available to anyone with a laptop and an internet connection. the question is whether you are going to spend your time consuming content or building the bots that actually change your life.
i stay in the zoom every day with my community because i know how lonely and frustrating the journey can be when you are starting from zero. having a tribe of traders who are all pushing for automation makes the process of failing much more tolerable.
you can see the millionaire p and l curves start to grow exponentially once they find a specific anomaly in the prediction markets. these anomalies do not last forever which is why you need a scanner to catch them the moment they appear.
stop being the person who gets liquidated because they could not handle the stress of a losing position. automate your logic and let the machine handle the execution so you can focus on finding the next million dollar idea.
the future belongs to the coders and the builders who are willing to look at the raw data and find the truth for themselves. keep iterating and keep building until your terminal is the only thing you need to generate a life of freedom