Showing 4 open source projects for "algorithmic trading software"

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    Interviews

    Interviews

    Comprehensive computer science and interview preparation guide

    Interviews is an open source repository designed as a comprehensive guide to preparing for technical interviews, with a strong focus on computer science fundamentals and algorithmic problem solving. Created by Kevin Naughton Jr., the project compiles detailed notes, explanations, and code implementations that cover core areas tested in software engineering interviews. The repository emphasizes topics such as data structures, algorithms, system design, operating systems, databases, and networking. It also includes practical coding examples and solutions that demonstrate how to approach and solve common problems asked at companies like Google, Amazon, Facebook, and Microsoft. ...
    Downloads: 2 This Week
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  • 2
    ML for Trading

    ML for Trading

    Code for machine learning for algorithmic trading, 2nd edition

    On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms, how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news. ...
    Downloads: 9 This Week
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  • 3
    Quantitative-Notebooks

    Quantitative-Notebooks

    Educational notebooks on quantitative finance, algorithmic trading

    Quantitative-Notebooks is a curated set of Jupyter notebooks focused on quantitative finance, algorithmic investing, and data-driven portfolio analysis. While each individual notebook is aimed at practical finance workflows, the overall repository helps practitioners and learners use Python, pandas, and numerical libraries to build, test, and evaluate financial strategies using historical market data. The notebooks typically showcase how to perform backtesting, factor analysis, risk...
    Downloads: 0 This Week
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  • 4
    GAVS+

    GAVS+

    An open platform for the research of algorithmic game solving

    GAVS+ (Game Arena Visualization and Synthesis, Plus!) is an open-source tool which enables to visualize a broad spectrum of algorithmic games used in verification and synthesis, and offers a standard interface with utility functions to establish connection with engineering practice. It is developed by Department of Informatics (Unit 6), TU München. The tool is mainly is served for research and educational purposes. The software is released under the GNU General Public License (v3). ...
    Downloads: 0 This Week
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