Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"

Showing 26 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"

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  • 1
    GoCryptoTrader

    GoCryptoTrader

    Trading bot and framework supporting multiple exchanges

    GoCryptoTrader is a full framework / bot for cryptocurrency trading, written in Go (Golang). It supports multiple exchanges, real-time and historic data, backtesting, handling order books, portfolio management, scripting, and many exchange integration features. It is a trading engine that can be run by users to automate strategies across many exchanges. Licensed under MIT. Support for all exchange fiat and digital currencies, with the ability to individually toggle them on/off. Customisation of HTTP client features including setting a proxy, user agent and adjusting transport settings. ...
    Downloads: 2 This Week
    Last Update:
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  • 2
    PyBroker

    PyBroker

    Algorithmic Trading in Python with Machine Learning

    Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance.
    Downloads: 4 This Week
    Last Update:
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  • 3
    NautilusTrader

    NautilusTrader

    A high-performance algorithmic trading platform

    NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the parity challenge of keeping the Python research/backtest environment, consistent with the production live trading environment. ...
    Downloads: 19 This Week
    Last Update:
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  • 4
    Awesome-Quant

    Awesome-Quant

    A curated list of insanely awesome libraries, packages and resources

    awesome-quant is a curated list (“awesome list”) of libraries, packages, articles, and resources for quantitative finance (“quants”). It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards.
    Downloads: 1 This Week
    Last Update:
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  • 5
    Flowsurface

    Flowsurface

    A native desktop charting platform for crypto markets

    ...The platform connects directly to public exchange APIs and WebSocket streams from venues such as Binance, Bybit, and OKX, allowing low-latency real-time data ingestion without relying on third-party servers. Users can customize layouts across multiple panes, adjust aggregation intervals, and tailor the visual presentation to suit different trading strategies.
    Downloads: 8 This Week
    Last Update:
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  • 6
    Optopsy

    Optopsy

    A nimble options backtesting library for Python

    ...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. ...
    Downloads: 4 This Week
    Last Update:
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  • 7
    Qbot

    Qbot

    AI-powered Quantitative Investment Research Platform

    Qbot is an open source quantitative research and trading platform that provides a full pipeline from data ingestion and strategy development to backtesting, simulation, and (optionally) live trading. It bundles a lightweight GUI client (built with wxPython) and a modular backend so researchers can iterate on strategies, run batch backtests, and validate ideas in a near-real simulated environment that models latency and slippage. The project places special emphasis on AI-driven strategies — including supervised learning, reinforcement learning and multi-factor models — and offers a “model zoo” and example strategies to help users get started. ...
    Downloads: 31 This Week
    Last Update:
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  • 8
    Superalgos

    Superalgos

    Free, open-source crypto trading bot, automated bitcoin trading

    ...Once you install and launch the app, a series of interactive tutorials take you by the hand and walk you all around the system while you learn the basic skills required to use the interface, mine data, backtest strategies, and even run a live trading session.
    Downloads: 4 This Week
    Last Update:
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  • 9
    Barter

    Barter

    Open-source Rust framework for building event-driven systems

    ...Use mock MarketStream or Execution components to enable back-testing on a near-identical trading system as live-trading. Centralised cache-friendly state management system with O(1) constant lookups using indexed data structures. Robust Order management system - use stand-alone or with Barter. Turn on/off algorithmic trading from an external process (eg/ UI, Telegram, etc.) whilst still processing market/account data.
    Downloads: 0 This Week
    Last Update:
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  • 10
    TradingGoose Studio

    TradingGoose Studio

    Technical analysis + LLM powered trading workflows

    ...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: 1 This Week
    Last Update:
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  • 11
    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. ...
    Downloads: 5 This Week
    Last Update:
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  • 12
    Roboquant

    Roboquant

    User-friendly and completely free algorithmic trading platform

    ...So whether you are a beginning retail trader or an established trading firm, Roboquant can help you to quickly develop robust and fully automated trading strategies. But perhaps most important of all, it is blazingly fast. Roboquant is orders of magnitude faster than most other algo-trading platforms. With historic data sets becoming more widely available and growing in size, it is important that a strategy can still be quickly developed, back-tested and optimized. If this cycle takes too long, it is nearly impossible to create high-performing and robust strategies. A lot of effort and attention went into making sure Roboquant is easy to use, especially for less experienced developers.
    Downloads: 1 This Week
    Last Update:
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  • 13
    AutoTrader

    AutoTrader

    A Python-based development platform for automated trading systems

    AutoTrader is a Python-based platform—now archived—designed to facilitate the full lifecycle of automated trading systems. It provides tools for backtesting, strategy optimization, visualization, and live trading integration. A feature-rich trading simulator, supporting backtesting and paper trading. The 'virtual broker' allows you to test your strategies in a risk-free, simulated environment before going live. Capable of simulating multiple order types, stop-losse,s and take-profits,...
    Downloads: 3 This Week
    Last Update:
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  • 14

    Kalshi-Quant-TeleBot

    Kalshi Advanced Quantitative Trading Bot is an enterprise-grade

    ...Built with cutting-edge quantitative algorithms and professional risk management, it provides institutional-quality trading capabilities with user-friendly control The Kalshi Advanced Quantitative Trading Bot is a professional-grade automated trading system designed specifically for event-based markets on the Kalshi platform. This bot leverages advanced quantitative strategies, machine learning techniques, and real-time data analysis to identify profitable trading opportunities while maintaining robust risk management protocols. Built with a modular architecture, the system combines Python-based trading algorithms with a JavaScript Telegram bot interface for dynamic monitoring and interaction. The bot is designed to operate continuously, making data-driven decisions based on news sentiment analysis, statistical arbitrage opportunities
    Downloads: 11 This Week
    Last Update:
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  • 15
    roboquant

    roboquant

    roboquant is a very fast algo-trading platform

    Roboquant is an open source algorithmic trading platform written in Kotlin. It is very fast, flexible, user-friendly and completely free to use. It is designed for anyone serious about algo-trading. So whether you are a beginning retail trader or an established trading firm, roboquant can help you to quickly develop fully automated trading strategies. No false promises of making lots of profit without doing the hard work, just a great foundation for building your own strategies.
    Downloads: 3 This Week
    Last Update:
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  • 16
    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: 5 This Week
    Last Update:
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  • 17
    TradingGym

    TradingGym

    Trading backtesting environment for training reinforcement learning

    TradingGym is a toolkit (in Python) for creating trading and backtesting environments, especially for reinforcement learning agents, but also for simpler rule-based algorithms. It follows a design inspired by OpenAI Gym, offering various environments, data formats (tick data and OHLC), and tools to simulate trading with costs, position limits, observation windows etc. Licensed under MIT. This training environment was originally designed for tickdata, but also supports OHLC data format. WIP. The list contains the feature columns to use in the trading status.
    Downloads: 2 This Week
    Last Update:
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  • 18
    MarketStore

    MarketStore

    DataFrame server for financial timeseries data

    ...If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem. The batteries are included with the basic install, you can start pulling crypto price data from GDAX and writing it to the db with a simple plugin configuration. MarketStore enables you to query DataFrame content over the network at as low latency as your local HDF5 files from disk.
    Downloads: 0 This Week
    Last Update:
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  • 19
    ML for Trading

    ML for Trading

    Code for machine learning for algorithmic trading, 2nd edition

    ...Using deep learning models like CNN and RNN with financial and alternative data, and how to generate synthetic data with Generative Adversarial Networks, as well as training a trading agent using deep reinforcement learning.
    Downloads: 9 This Week
    Last Update:
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  • 20
    Zipline

    Zipline

    Zipline, a Pythonic algorithmic trading library

    ...Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python package. For a development installation (used to develop Zipline itself), create and activate a virtualenv, then run the etc/dev-install script. Please note that Zipline is not a community-led project. Zipline is maintained by the Quantopian engineering team, and we are quite small and often busy.
    Downloads: 0 This Week
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  • 21
    AlphaPy

    AlphaPy

    Python AutoML for Trading Systems and Sports Betting

    AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow. Develop trading systems and analyze portfolios using MarketFlow and Quantopian's pyfolio.
    Downloads: 0 This Week
    Last Update:
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  • 22
    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. ...
    Downloads: 0 This Week
    Last Update:
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  • 23
    PandoraTrader

    PandoraTrader

    C++ Trade Platform for quant developer

    PandoraTrader is a high-frequency quantitative trading platform implemented in C++. It interfaces with real-world futures trading desks using Trade APIs and MarketData APIs and includes support for backtesting via simulated market components. We design such a trading platform with various skills given by the designer, but we do not carry wisdom; this wisdom belongs to the strategy designer. We hope that the strategy designer will design excellent strategies to give the trading software...
    Downloads: 0 This Week
    Last Update:
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  • 24
    Gekko-Strategies

    Gekko-Strategies

    Strategies to Gekko trading bot with backtests results

    Gekko-Strategies is a community repository of strategies (JavaScript files plus configuration) for the Gekko trading bot. It contains a variety of trading strategy scripts, backtest results, and tools or helpers for strategy evaluation. It is not itself a standalone trading engine but contains strategy modules to use with Gekko. Results are sorted by amount of best profit/day on unique DATASETS. Includes an install script (install.sh) to facilitate installing strategies into the user’s Gekko setup under Unix-like systems. ...
    Downloads: 0 This Week
    Last Update:
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  • 25
    LEAN

    LEAN

    Lean algorithmic trading engine by QuantConnect

    ...Use combinations of margin, fill, and slippage models to simulate a liquidity endpoint. 100+ popular technical indicators built, tested, and ready for use. Applicable to any data source.
    Downloads: 0 This Week
    Last Update:
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