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mlfinlab

hudson-and-thames / mlfinlab

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quant-trading

je-suis-tm / quant-trading

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Python quantitative trading strategies including Pattern Recognition, CTA, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
trading-bot quant trading-strategies trading-algorithms quantitative-finance algorithmic-trading quantitative-trading trading-systems statistical-arbitrage macd options-trading bollinger-bands options-strategies momentum-strategy quantitative-trading-strategies trading-strategy pair-trading momentum-trading-strategy commodity-trading quantimental-analysis
  • Updated Aug 19, 2020
  • Python
backtesting.py

kernc / backtesting.py

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Suggestion for Faster way to optimize vs GridSearch

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mitrymoe
mitrymoe commented May 13, 2020

Hey,

First of all thank you for the hard work put into this, it's a really awesome project that I still learn how to use.
I'm not that proficient in using python so that is why I'll put my suggestion here. I have used python more for machine learning stuff and there the option of searching hyperparameters was also between grid and random search. However, I found that using bayesian optimizati

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enhancement good first issue

rorysroes / SGX-Full-OrderBook-Tick-Data-Trading-Strategy

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Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
python machine-learning trading feature-selection model-selection quant trading-strategies investment market-maker feature-engineering algorithmic-trading backtesting-trading-strategies limit-order-book quantitative-trading orderbook market-microstructure high-frequency-trading market-making orderbook-tick-data
  • Updated Feb 14, 2017
  • Jupyter Notebook

AlgoTraders / stock-analysis-engine

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Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
docker kubernetes redis deep-neural-networks options deep-learning jupyter tensorflow helm s3 keras minio iex helm-charts stocks algorithmic-trading deep-learning-tutorial tradier backtesting iexcloud
  • Updated Aug 8, 2019
  • Jupyter Notebook

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