>This year, our advanced Gemini model operated end-to-end in natural language, producing rigorous mathematical proofs directly from the official problem descriptions – all within the 4.5-hour competition time limit.
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Built a portfolio risk engine from scratch – optimized for PM workflows for equity-oriented portfolios, deployable on Mac or Windows, and structured for scale.
Parallelized architecture with modular components. No legacy code. Connects directly to your existing portfolio positions (whether that’s an excel file or a database).
Key Features:
• Forecasted Risk: VaR, CVaR, multi-horizon EWMA/GARCH/EGARCH vol forecasts, marginal & forecast risk contributions. Suitable for fat tails.
• Realized Risk: max drawdown, VaR, CVaR, up/down captures, tracking error, rolling metrics, correlation matrix, vol contribution.
• Factor Exposure: traditional factors like quality/value/size, and custom themtic factor decomposition (via proxy construction & regression)
• Position Sizing: Volatility-based position sizing with forward-looking risk constraints. Can add whatever sizing methodology you wish (like risk parity).
Built using Cursor + Claude Sonnet (state of the art AI coding platform) to accelerate development—AI handled code scaffolding and test harnesses, I provided direction and owned the math and investment logic.
Targeted at small-to-mid-sized funds and PMs without internal quant teams. DM if you want to see it in action or walk through how it could integrate with your stack.
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Deciding to hire a programmer boils down to your specific needs, technical prowess, and trading goals. If you lack the coding skills needed or if your strategy is particularly intricate, enlisting a professional could save you significant time and money. Ensure you’re transparent about your expectations and clarify all support terms upfront. Balancing these elements will help you determine if hiring a programmer aligns with your trading journey.
Remember, successful algo trading isn’t just about the code; it involves a well-rounded strategy and vigilant oversight. So, whether you go at it alone or opt for expert help, always stay informed and proactive in your trading endeavors.
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If there ever was art that encouraged contemplation, David Bowen’s installation is it. It draws you in with its bizarre allure and leaves you reflecting on the beauty and mystery of the natural world coupled with human ingenuity.
For art enthusiasts, tech lovers, and nature admirers, this installation serves as a compelling bridge connecting diverse elements of the world. It’s an invitation to see plants not merely as passive green life but as active, intelligent entities capable of interaction and influence.
So next time you gaze upon a philodendron swaying gently in your living room, let this art provoke a little wonder at the secret life it leads and the potential stories it could tell through the artful language of technology.
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Hey folks,
I’ve been digging into flash loans on Solana and wondering—can we use them for more than just memecoin flips?
Some ideas I’ve seen or thought about:
* **Sniping liquidations** on Solend or Port Finance
* **Collateral swaps** to get better interest rates
* **Self-liquidation** to dodge fees
* **Leverage loops** for farming
* **Fixed vs floating rate trades** using pTokensThese all seem possible with Solana’s speed and low fees, but I’m curious—**has anyone here tried this stuff?**
Is it doable? What tools or tips would you recommend?
Would love to hear your thoughts or see if others are exploring the same path. Let’s brainstorm
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[https://edition.cnn.com/2025/07/23/politics/fda-ai-elsa-drug-regulation-makary](https://edition.cnn.com/2025/07/23/politics/fda-ai-elsa-drug-regulation-makary)
“Six current and former FDA officials who spoke on the condition of anonymity to discuss sensitive internal work told CNN that Elsa can be useful for generating meeting notes and summaries, or email and communique templates.
But it has also made up nonexistent studies, known as AI “hallucinating,” or misrepresented research, according to three current FDA employees and documents seen by CNN. This makes it unreliable for their most critical work, the employees said.
“Anything that you don’t have time to double-check is unreliable. It hallucinates confidently,” said one employee — a far cry from what has been publicly promised.
“AI is supposed to save our time, but I guarantee you that I waste a lot of extra time just due to the heightened vigilance that I have to have” to check for fake or misrepresented studies, a second FDA employee said.
Currently, Elsa cannot help with review work , the lengthy assessment agency scientists undertake to determine whether drugs and devices are safe and effective, two FDA staffers said. That’s because it cannot access many relevant documents, like industry submissions, to answer basic questions such as how many times a company may have filed for FDA approval, their related products on the market or other company-specific information.”
