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Starting your dropshipping journey as a college student is absolutely possible, even with minimal funds. By educating yourself, leveraging free resources, and starting small, you can build a foundation for a successful venture. Balance dedication with patience, and gradually, you might find yourself not just supporting your family but gaining valuable business acumen for the future. You’re ready to dive in—go seize those opportunities!

Discussion thread.

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.

https://deepmind.google/discover/blog/advanced-version-of-gemini-with-deep-think-officially-achieves-gold-medal-standard-at-the-international-mathematical-olympiad/

>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.

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.

# “What if AI gets so smart that the President of the United States cannot do better than following ChatGPT-7’s recommendation, but can’t really understand it either? What if I can’t make a better decision about how to run OpenAI and just say, ‘You know what, ChatGPT-7, you’re in charge. Good luck.”