Alternatives
Products that do what QuantFit - Econometrics in pocket does
Econometrics that moves with your research.
- 1QI
2017 · quantra.io
- 2QL
Hi everyone, I wanted to share Quantus, a finance learning and practice platform I’m building out of my own frustration with traditional resources. As a dual major in engineering and finance who started my career at a hedge fund, I found it challenging to develop hands-on financial modeling skills using existing tools. Platforms like Coursera, Udemy, Corporate Finance Institute (CFI), and Wall Street Prep (WSP) primarily rely on video-based tutorials. While informative, these formats often lack the dynamic, interactive, and repetitive practice necessary to build real expertise. For example,…
2024 · quantus.finance
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OP here: I created this visualization tool as the byproduct of a supply chain class I taught at Columbia. The pedagogical exercise grew into a full blown visualization and paper about global oil trade. The model: The mechanics are the same as the financial network Eisenberg-Noe: Instead of banks, every country consumes oil interconnected via bilateral trading. Shocks propagate throughout the network, depleting oil reserves when bottleneck nodes (such as the Strait of Hormuz) are blocked. Insights: The interesting part is the mechanics of how the crisis unfolds: for example, France receives 0…
Jul 2026 · globaloilnetwork.staffinganalytics.io
- 4LW
Some technical context on what we ran into building this. MCP tools don't really work for financial data at scale. One tool call for five years of daily prices dumps tens of thousands of tokens into the context window. And data vendors pack dozens of tools into a single MCP server, schemas alone can eat 50k+ tokens before the agent does anything useful. So we auto-generate typed Python modules from the MCP schemas at workspace init and upload them into the sandbox. The agent just imports them like a normal library. Only a one-line summary per server stays in the prompt. We have around 80…
Apr 2026 · github.com
- 5TV
I am excited to announce the release of TabPFN v2, a tabular foundation model that delivers state-of-the-art predictions on small datasets in just 2.8 seconds for classification and 4.8 seconds for regression compared to strong baselines tuned for 4 hours. Published in Nature, this model outperforms traditional methods on datasets with up to 10,000 samples and 500 features. The model is available under an open license: a derivative of the Apache 2 license with a single modification, adding an enhanced attribution requirement inspired by the Llama 3 license:…
2025 · nature.com
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- 7QN
2015 · quantnews.com
- 8TF
2011 · bullbear.ca
- 9AY
2017 · terminal.quantra.io
- 10FR
2021 · github.com
- 11
- 12PS
We’ve built a Python SDK for running inference on foundation models designed for time-series and tabular data. They are new SOTA models for time-series and tabular tasks and work out of the box. They do not require model training or feature engineering. The link to the GitHub repository is: https://github.com/S-FM/faim-python-client
Dec 2025 · github.com
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Pass Quant interviews: math, coding & brain teasers
Jun 2026 · amazon.com
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QuantSignals FST is a supervised AI trading agent that connects QS Research to risk-governed brokerage execution across web, desktop, CLI, iOS, and Android.
Aug 2026 · quantsignals.xyz
- 17OC
Hi HN, Here is the open source repo of the data pipelines built in dbt to model profitability at the level of an order. Covers sources like: Shopify, Facebook Ads, Fedex, Paypal, Manufacturing Costs, VAT etc. Benefits for ecomm - Precise Granular Revenue and Profit analysis at the level of orders. - Template to automate Profits calculation saving you 100s hours of manual work in Excel or GSheet. - Increase ROI on Paid Marketing: By understanding hidden costs like VAT and shipping, you can make smarter decisions on ad spend across different countries. Hope this is useful!
2024 · github.com
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- 21QT
Today we're releasing Quant (https://sourcetable.com/quant), an AI analyst that connects to 600+ exchanges with 1000+ built-in analysis tools. Andrew, CTO, has a background building software at hedge funds so we put his knowledge and experience into this application. The core idea: if you already know spreadsheets, you shouldn't need to learn Python/R or set up complex infrastructure to do serious quantitative analysis. One way to think of Quant is a low-cost Bloomberg Terminal alternative. What's inside: Portfolio optimization (including Dalio's risk parity approach),…
Oct 2025
- 22
Free resume templates built for economics students
Apr 2026 · econstudentresumetemplate.netlify.app
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Quant trading using Python and Block Code. Live and Backtest
Jul 2026 · quantstudio.trade
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