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cryptoquantAn Quantatitive trading library for crypto-assets 数字货币量化交易框架
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GOAiNo description or website provided.
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TaiA composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine
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QlibQlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.
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FintaCommon financial technical indicators implemented in Pandas.
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Qlib ServerQlib-Server is the data server system for Qlib. It enable Qlib to run in online mode. Under online mode, the data will be deployed as a shared data service. The data and their cache will be shared by all the clients. The data retrieval performance is expected to be improved due to a higher rate of cache hits. It will consume less disk space, too.
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TuringtraderThe Open-Source Backtesting Engine/ Market Simulator by Bertram Solutions.
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py-investmentExtensible Algo-Trading Python Package.
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ciraCira algorithmic trading made easy. A Façade library for simpler interaction with alpaca-trade-API from Alpaca Markets.
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Pipeline LivePipeline Extension for Live Trading
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Riskfolio LibPortfolio Optimization and Quantitative Strategic Asset Allocation in Python
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howtraderHowtrader is a crypto currency quant framework, you can easily develop, backtest and run your own strategy in real market. It also supports tradingview or other 3rd party signals, just simply send a post request and it will help trade automatically. Now it only support binance spot, futures and inverse futures exchange. It will support okex, ftx…
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RqalphaA extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
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ResearchNotebooks based on financial machine learning.
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QuantstatsPortfolio analytics for quants, written in Python
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Quant NotesQuantitative Interview Preparation Guide, updated version here ==>
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