Alternatives
Products that do what HRMV does
Trading framework built from real losses, not theory
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2024 · useequityval.com
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Numscript is a simple, declarative language that helps you model financial transactions. You can do quite a few things with it, such as modeling: * Payments involving vouchers and a user's prepaid balance * Complex funds destination scenario where the customer gets cash back * Configurable user credit balance spending transactions The main idea is to take the pain out of describing of a system dealing with money movements should behave in traditional languages such as JS/TS/Go/Ruby etc, landing an expressive way to model these movements of value. It is voluntarily broad in…
2024 · playground.numscript.org
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Hi there. I built a company that makes algorithmic trading strategies for its users to invest with. --> https://justfor.fund Advice and feedback are very much welcomed! Disclaimer: New born business with its first beta version (12 users) currently live. Details: - I'm the sole developer and founder - I applied to YC S22 batch on the last day - Currently facing a big KYC compliance wall (code and protocols) - My priority right now is obtaining funds to cover minimal operational cost's. Need to pay for broker partnership costs too. - I have essentially no funds to cover cost's right…
2022 · justfor.fund
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Post-Opus 4.6, LLMs feel much better at using bash, code, local files, and tools. So I kept coming back to a simple question: if a model can use a computer reasonably well, why can’t I just give it my broker account, a strategy, and let it trade? My conclusion is that the blocker is not model capability in the abstract. It is the system around the model. A raw LLM breaks on a few practical things almost immediately: • no persistent operating memory across sessions • no trustworthy record of what it did and why • no hard approval boundary before money moves • no cheap always-on monitoring if…
Mar 2026 · github.com
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Practice trading with real historical market data by setting entry, stop-loss, and take-profit levels. The goal is to help traders practice without taking any financial risk. It's completely free, and no sign up is required to jump right in. I'd love for you to try it out: https://dare2trade.com/ It's best experienced on desktop devices for now.
2025 · dare2trade.com
- 8IB
Hi HN, I'm a solo dev and for the last few months I've been building Hikaro, a tool to find statistically significant trading signals for [e.g., US equities, crypto, forex]. I built this to solve my own problem: I was tired of backtests that looked great on paper but failed in practice. Simple metrics like "win rate" can be misleading, so I wanted a way to quickly tell if a signal's performance was genuine or just noise. Hikaro ingests daily market data and runs statistical analysis on various trading signals. The goal is to surface signals with strong properties, like: Low p-value: Evidence…
Sep 2025 · hikaro.app
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I built TradeSight (https://tradesight.live) as a lightweight market risk indicator that combines real-time data with AI insights. The backend is written in Rust, with a vanilla JS frontend for maximum performance. It aggregates data from multiple sources (FRED API, Yahoo Finance) and uses Claude's API to provide detailed market analysis. Technical stack: - No login required - static page with hourly updates - Rust backend for efficient data aggregation - Vanilla JavaScript frontend for minimal overhead - Claude API integration for real-time market analysis - Data sources: FRED…
2024 · tradesight.live
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Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
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AI trading analysis built for investors seeking clarity.
Apr 2026 · app.tradecompass.ca
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I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
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Hey HN, I'm Steve, co-founder of Factor.fyi, a new data platform for querying and visualizing financial datasets using SQL. During the pandemic, I took much more of an active role in managing my portfolio. I wanted to be able to make informed decisions about the investments I was making, and explore financial data in new ways. Market and Econ data are some of the most talked-about and widely-available datasets out there, but I was frustrated by the lack of options to answer questions I had, like, "What would have happened if I had started dollar-cost averaging VTI back in 2013?"[1] Or, "How…
2022 · factor.fyi
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How it works (tech stack): -Built entirely with Lovabl.dev (no-code front-end + logic) -ChatGPT / Claude for research and inspiration -Powered by GPT-4 Vision to interpret charts visually -Hosted on Supabase for performance & caching It’s not meant to replace analysts — just to speed up how traders interpret data. I’m a designer exploring AI tools, and this is my first attempt to turn an idea into a functional product. Would love to know what you think.
Oct 2025 · quantify-ai.co
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