Screen equities against dozens of technical indicators, backtest algorithmic trading strategies, and spot intraday market anomalies using Tick Stock Panel, a self-hosted quantitative analysis workbench. Traders can filter entire exchanges across technical indicators including moving averages, relative strength index, and Bollinger bands with near-instantaneous execution. The platform provides a full backtesting environment where users test customized entry and exit rules, account for simulated slippage and commission fees, and review streamed performance metrics. Dedicated monitoring modules track intraday volume spikes, price breakouts, and multi-day limit streaks with automated alert dispatching to messaging channels and voice announcements. Users can explore individual stock profiles featuring multi-dimensional technical breakdowns, financial balance sheets, and automated event post-mortems generated via integrated language models. Visual factor mining tools allow analysts to discover uncorrelated signals and assemble composite portfolio screens without external database overhead. An interactive dashboard aggregates sector rotations, hot concept heatmaps, and customizable watchlists into modular operational views. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

OpenStock delivers a production-ready financial market terminal that unifies real-time equity pricing, technical analysis, and multi-asset watchlists into a personal self-hosted dashboard. Investors can monitor equities across thirty international exchanges, inspect live candlestick charts powered by TradingView, and evaluate technical momentum oscillators without paying recurring platform subscriptions. The global command palette accessible via keyboard shortcuts enables instantaneous ticker discovery across global exchange symbols and economic sectors. Users can organize individual stock watchlists in MongoDB, configure automated price threshold alerts triggered every fifteen seconds, and review cross-platform sentiment scores synthesized from Reddit, X, and financial news feeds. The built-in automation engine schedules weekly digest reports and event-driven notifications dispatched directly to your inbox through Nodemailer transports. Responsive market heatmaps and top-mover widgets surface daily sector performance before the opening bell rings. Deployable via Docker Compose with dedicated MongoDB persistence, the platform scales across multi-key Finnhub rate limits effortlessly. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

OpenBB stands as the world's most popular open-source finance repository — an Open Data Platform that evolved from a pandemic-era Reddit post into a full-blown infrastructure layer challenging Bloomberg's $25 billion empire. The "connect once, consume everywhere" architecture consolidates proprietary, licensed, and public financial data sources into multiple consumption surfaces simultaneously: Python environments for quants building models, OpenBB Workspace and Excel for analysts creating dashboards, MCP servers for AI agents performing automated research, and REST APIs for custom applications. The modular extension system supports dozens of data providers including Yahoo Finance, Alpha Vantage, FRED, Intrinio, Polygon, and Tradier with standardized schemas that normalize responses across vendors. The CLI offers a terminal-style interactive interface with autocomplete, parameter hints, and chart rendering for rapid data exploration. Provider routing handles authentication, rate limiting, and response normalization transparently so switching between free and premium data sources requires changing a single parameter. The platform covers equities, options, fixed income, crypto, forex, ETFs, mutual funds, economics, technical analysis, quantitative analysis, and alternative data across global markets. AI agent integration exposes every data endpoint as tool-callable functions with schema discovery enabling LLMs to query financial data programmatically. Install via pip with Python 3.9+ and deploy the REST API server for team access. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Good European market data is either expensive or wrong, so Fonrex runs it all on your server: a self-hosted API serving per-listing prices, cross-checked fundamentals, DCF valuations, and factor models for European and US shares, with no subscription or per-call meter. Every price is stored per listing in its own currency and dated by trading session, so AIR.PA resolves to Airbus rather than a same-ticker US namesake, and one ISIN can carry many listings cleanly. Fundamentals are cross-checked between sources first; figures that disagree with the consensus are rejected, and every answer names the sources it came from. Value any company three ways with FCF, EPS, and dividend DCF models, compare them side by side, and stress the result with a WACC by growth sensitivity matrix. Factor tools return Kenneth French returns for the US, Europe, and developed markets, compute listing factor exposure, and price equity with the risk-free rate of the right currency, alongside FRED and ECB rates, Treasury curves, and Eurostat indicators. Daily history spans ten years, split-adjusted with a dividend-adjusted close; live ticks stream over WebSocket, indicators and a screener run on your stored prices, and deduplicated news arrives per ticker or as a global feed. Results plug into OpenBB Workspace, Google Sheets, Python notebooks, and Zipline backtests, so spreadsheets, dashboards, and research pipelines all read the same numbers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

PanWatch's three scheduled AI agents plan the trading day before the bell, watch the session, and review it after the close for your China A-share, Hong Kong, and U.S. holdings. Day one begins with the portfolio: several brokerage accounts, holdings and profit and loss, and search for stocks or listed ETFs by code or name. The pre-market agent folds overnight moves, news, and technical structure into that plan and skips exchange holidays. Through the session, the intraday monitor watches for unusual moves and technical signals. Price alerts combine price, percentage change, turnover, and volume ratio with AND/OR logic, cooldowns, and expiry times. Each rule picks its own channel from Telegram, WeCom, DingTalk, Feishu, Bark, or a webhook. Spot something odd? The brain icon next to a holding starts TradingAgents, where four analyst roles feed a bull and bear debate, a risk review, and a portfolio-manager decision, with the reasoning trail in the app and your notifications. The opportunities screen ranks AI-scored ideas with entry levels and targets, and paper trading simulates signal-based entries and exits and tracks equity and performance. At day's end, the daily report reviews the session and prepares the next trading day's plan. OpenAI-compatible providers or local Ollama models power the analysis, and the PWA installs on a phone in English or Simplified Chinese. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With 1,450+ GitHub stars and a live demo on Vercel, this Bloomberg Terminal clone delivers a professional-grade financial dashboard without the $24,000 annual seat license. The Next.js 15 App Router with React 19 and TypeScript serves a single-page terminal interface optimized for constantly mutating financial data, with partial pre-rendering enabling sub-500ms initial loads even on data-heavy views. Upstash Redis caches AlphaVantage market data to minimize API calls while maintaining sub-second update latency through React Query polling with configurable refresh rates. OpenAI integration provides AI-powered market insights, sentiment analysis, and trend interpretation directly within the terminal interface. Multiple specialized views cover market data tables with bid/ask spreads, financial news aggregation with category filtering, market movers highlighting top gainers and losers, and volatility analysis with historical comparison charts. Jotai atoms manage local state for watchlists, layout preferences, and terminal sessions while React Query handles server-state synchronization with aggressive stale-while-revalidate caching. The shadcn/ui component library with Tailwind CSS delivers accessible, keyboard-navigable interface elements styled after Bloomberg's iconic dark terminal aesthetic. Security features include origin restriction, rate limiting via Redis, and Zod-based input validation on all API routes. Motion (formerly Framer Motion) animates transitions between views and data updates without layout shift. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Built atop the TauricResearch TradingAgents framework with nearly 100,000 GitHub stars, TradingAgents GUI transforms a CLI-only multi-agent LLM stock analysis pipeline into a polished web application accessible at localhost:5000. The system deploys twelve specialized AI agents — fundamental analysts, sentiment experts, technical analysts, bull and bear researchers, a trader, risk management team, and portfolio manager — who collaboratively debate market conditions through structured LangGraph workflows before producing a final BUY, SELL, or HOLD recommendation. The interface supports ten LLM providers including OpenAI, Anthropic, Google, OpenRouter, DeepSeek, Ollama, xAI, Qwen, GLM, and MiniMax, with a first-run wizard that auto-detects configured API keys and tests connections. A live pipeline visualization shows each agent's status with real-time progress bars, while the tabbed output area separates Live Feed, Reports preview, and Tool calls into dedicated panes. The three-pane Reports tab provides searchable indexing, table-of-contents navigation, and export to Markdown, HTML, or PDF formats. Report length control across Concise, Standard, and Comprehensive modes saves up to 50% on token costs. Multi-session chat allows pinning past reports as grounding context with live token counting and context-window warnings. Three built-in themes — Terminal, Modern, and Bloomberg — persist per browser. Docker Compose deployment maps port 5000 with persistent report storage. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

A trading strategy that works on your laptop still has to survive restarts, remember its positions, and tell you what it is doing at 3 a.m.; the0 is the self-hosted runtime that handles that last mile for algorithmic trading bots. Write your bot in Python, TypeScript, Rust, C++, C#, Scala, or Haskell with the matching SDK, package it as a reusable custom bot, and instantiate it as many times as you like with different symbols and parameters. Every instance runs in its own isolated container, either continuously for realtime strategies or on a cron schedule for periodic ones, with key-value state that survives between runs and restarts. Structured logs and metrics stream into the dashboard in real time, and you can ship a custom React frontend with your bot so its prices, signals, and positions render exactly the way you want. Deploy from the CLI in one command, drive everything from the REST API, or let an AI assistant list, deploy, and debug bots through the built-in MCP server. Scale from a single Docker Compose host to Kubernetes with the Helm chart, where bots become pods and CronJobs, and keep backtesting and market data in your own research stack, because the0 deliberately runs production strategies rather than simulating them. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Trading alerts from TradingView, Amibroker, ChartInk, Excel, or a Python script turn into orders at your own broker through OpenAlgo, a self-hosted trading desk for Indian markets. One REST API handles orders, positions, holdings, funds, quotes, and market depth across more than 35 brokers, including Zerodha, Upstox, Angel One, Fyers, and Dhan, while a WebSocket feed streams live prices. Strategies can be wired together without code in Flow, a drag-and-drop canvas of data, indicator, condition, and order nodes with webhook triggers, or written in Python and scheduled with start and stop times in the built-in editor, each in an isolated process with live logs. The charting terminal places orders straight from the chart, with layouts of up to eight charts, over 100 indicators, drawing tools, and bar replay. Options traders get an option chain with live Greeks, OI tracker, max pain, straddle charts, a 3D volatility surface, a GEX dashboard, and a strategy builder with payoff diagrams. Analyzer mode runs any strategy against real market data with 1 crore rupees of sandbox capital. Semi-auto mode in the Action Center holds each order for your approval, and the AI agent charts, analyzes, and drafts strategies but pauses for sign-off on every order. Telegram alerts, a latency monitor, a P&L tracker, and Historify downloads with CSV and Parquet export cover daily operations. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

A trading journal you host yourself, Trade Journal rebuilds broker fills and statement exports into round-trip trades, a profit and loss calendar, and daily notes that show what actually works. Read-only sync covers more than twenty brokers and exchanges, including Alpaca, Binance, Coinbase, Kraken, and IBKR Flex. Statement import auto-detects TradingView, MetaTrader, NinjaTrader, Tradovate, and thinkorswim files, handles TradeZella and Tradervue CSV migrations, and maps columns for anything else. Trades can be matched first-in-first-out, last-in-first-out, or by weighted average, with partial fills, scale-ins, and futures multipliers handled. The dashboard offers gauges, cumulative and daily P&L, an Edge Score radar, and cards you can rearrange into named layouts, while Reports break results down by symbol, tag, mistake, playbook, weekday, and time of day. Each trade page charts entries and exits and can replay candles you load, with estimated MAE and MFE. Daily journal pages hold Markdown notes, templates, attachments, and voice dictation, and optional AI recaps use your own Anthropic or OpenAI key or a local Ollama model. Playbook checklists score rule adherence, a prop firm ledger tracks costs and payouts, and privacy mode masks every amount. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.