Stock2Trend
Research any stock in 15 minutes. Not hours.
What it does
Stock research used to take 2+ hours. Stock2Trend cuts that to 15 minutes. Most tools pick stocks for you or dump raw data with no structure. We organize your research, so you make the decisions. Daily shortlist of stocks with unusual options activity + AI analysis showing three scenarios: what could go right, what's realistic, what could go wrong. Not predictions. Structured thinking for faster, more confident investing.
Does the same job
all alternatives →
- STSave time on stock market research2023 · wallstrank.com · ▲5
- RTRead the Tape – Wordle for daytrading, five blind S&P 500 charts a dayJul 2026 · readthetape.cc · ▲70
Read the Tape gives players the same 5 S&P500 stock charts per day to predict. You select low, medium or high confidence and then call the chart UP or DOWN. It's a 1d chart which then resolves over 5 days. Alpha is scored against the Monkey Index, a basket of 11 random coin flips at low confidence which provides a tangible win/lose condition. We're two weeks in and some interesting data is being kicked up. Players like to call tops even though stonks go up- 60% of the 70 charts so far resolve higher, players' down calls have only been right 31% of the time. There's a full stats dive at…
- IBI built AI that turns 4 hours of financial analysis into 30 seconds2025 · duebase.com · ▲15
I built Duebase AI to solve a problem I kept running into in fintech - analyzing UK company financial health takes forever. The process usually goes: download PDFs from Companies House → manually extract data to spreadsheets → calculate ratios → interpret trends. Takes 3-4 hours per company and requires serious financial expertise. The technical challenge: Companies House filings are messy. Inconsistent formats, complex accounting structures, missing data, and you need to understand UK accounting standards to make sense of it all. My approach: Parse 15M+ UK company records from Companies…
- SMStock market analysis2016 · ▲9
https://www.forestpin.com/cse/ This is still experimental and is a different way of analyzing stocks in the long term. We consider Dividends, Rights Issues, Bonus Issues, and Splits to calculate the value of the share. This gives a more realistic view than simply looking at the share price variations. We reinvest cash from dividends in the same stock and sell existing shares to execute rights. It's a simple calculation but it gives a much better perspective of the stocks in the long term than simply looking at the share price. You can select a stock symbol or click on…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com