Open Source ChromeOS Algorithmic Trading Platforms

Algorithmic Trading Platforms for ChromeOS

Browse free open source Algorithmic Trading platforms and projects for ChromeOS below. Use the toggles on the left to filter open source Algorithmic Trading platforms by OS, license, language, programming language, and project status.

  • PageDNA: Web-to-Print eCommerce Software Icon
    PageDNA: Web-to-Print eCommerce Software

    eCommerce for Print, Signs and Fulfillment Trusted by In‑Plants and Commercial Print Leaders

    PageDNA enables successful eCommerce strategies for commercial print sales organizations, internal print shops, and brand owners. PageDNA’s online ordering platform increases print volume while decreasing touch costs for all stakeholders: clientele, print operations, and the organizations they support.
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  • Free Website Monitoring Service | UptimeRobot Icon
    Free Website Monitoring Service | UptimeRobot

    The free online uptime monitoring service with an App is available for iOS and Android.

    With the Free Plan, you can monitor up to 50 URLs, check for a website's content (using the keyword monitor), ping your server or monitor your ports in 5-minute intervals. You can create a status page to showcase your uptime. SMS or Call alerts can be bought anytime.
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  • 1
    AnyTrading

    AnyTrading

    The most simple, flexible, and comprehensive OpenAI Gym trading

    gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    Optopsy

    Optopsy

    A nimble options backtesting library for Python

    Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. As such, we just need to call the long_calls() function to have Optopsy generate all combinations of a simple long call strategy for the specified time period and return a DataFrame. Here we also use Panda's round() function afterwards to return statistics within two decimal places.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 3
    Kalshi Trading Bot CLI

    Kalshi Trading Bot CLI

    AI-native CLI for trading Kalshi prediction markets

    Kalshi Trading Bot CLI is an AI-driven command-line tool designed to automate trading strategies on Kalshi prediction markets by combining quantitative modeling with real-time market data. It operates by conducting deep research on events, generating independent probability estimates, and comparing those estimates against current market prices to identify trading opportunities. The system incorporates advanced decision-making logic, including Kelly criterion-based position sizing and a structured multi-step risk evaluation process before executing trades. Built as a CLI application, it allows traders to interact programmatically with markets, making it suitable for automation and integration into larger trading pipelines. The tool emphasizes disciplined trading through its risk engine, ensuring that decisions are filtered through multiple validation layers before capital is committed.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 4
    EliteQuant

    EliteQuant

    A list of online resources for quantitative modeling, trading, etc.

    EliteQuant is a curated directory of online resources for quantitative finance: trading, portfolio management, quantitative modeling, data sources, libraries, platforms, and communities. It is not a software library per se, but a “list of things” - i.e., an aggregator of open source projects, blogs, tools etc., intended to help practitioners find useful resources. It is licensed under Apache-2.0, and maintained by volunteers. A list of online resources for quantitative modeling, trading, and portfolio management. Has criteria for recommending projects/resources to help keep quality up.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Enterprise AI Agents for Every Customer Moment Icon
    Enterprise AI Agents for Every Customer Moment

    For enterprise companies looking for AI Agents

    From chat to voice to SMS, every conversation gets a smart, personalized response powered by your policies, tone, and data.
    Learn More
  • 5
    QuantComponents

    QuantComponents

    Free Java components for Quantitative Finance and Algorithmic Trading

    An open-source framework for financial time-series analysis and algorithmic trading, based on Java and OSGi, with an Eclipse front-end. * Highly modular: usable as plain java API, OSGi components, or integrated into Eclipse * Standalone or client-server architecture, depending on performance and reliability needs * Integrated with Interactive Brokers through IB Java API * Generic broker API, it can easily be extended to work with other brokers * It works with historical and/or realtime market data * Backtesting facility * Extensible SWT charting library
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    TradingGoose Studio

    TradingGoose Studio

    Technical analysis + LLM powered trading workflows

    TradingGoose Studio is an open-source AI workflow platform designed to enable advanced financial trading analysis and automation through a visual, modular interface powered by large language models. It combines traditional technical analysis with modern AI-driven decision-making by allowing users to build workflows where multiple specialized agents collaborate to interpret market signals and execute actions. The platform supports end-to-end trading pipelines, starting from ingesting real-time market data and applying custom indicators, to generating insights and triggering automated trades or alerts. Users can connect their own data providers and define personalized strategies using programmable indicators, making the system highly flexible for different trading styles. A key aspect of the platform is its visual workspace, where charts, widgets, and workflow blocks can be arranged and customized to create an interactive trading environment.
    Downloads: 0 This Week
    Last Update:
    See Project
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