Repositories list

• quickstart

  Public
  QuickStart notebooks for QuantRocket

  Jupyter Notebook

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  Apache License 2.0

  •1•2•0•0•Updated Sep 16, 2024Sep 16, 2024

• brain-sentiment

  Public
  Overview of 3 sentiment datasets from data provider Brain: Brain Sentiment Indicator (news sentiment), Brain Language Metrics on Company Filings, and Brain Language Metrics on Earnings Call Transcripts.

  Jupyter Notebook

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  Apache License 2.0

  •0•0•0•0•Updated Jun 24, 2024Jun 24, 2024

• borrow-fees-alpha

  Public
  Introduction to QuantRocket's borrow fees dataset. Uses Alphalens to analyze borrow fees as an alpha source and uses Moonshot to backtest a strategy that shorts stocks with high borrow fees while modeling borrowing costs.

  Jupyter Notebook

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  Apache License 2.0

  •0•1•0•0•Updated May 13, 2024May 13, 2024

• moonshotml-intro

  Public
  Introductory tutorial for MoonshotML demonstrating walk-forward optimization of a simple machine learning strategy. Uses free sample data.

  Jupyter Notebook

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  Apache License 2.0

  •0•1•0•0•Updated May 3, 2024May 3, 2024

• moonshot-intro

  Public
  Introductory tutorial for Moonshot demonstrating data collection, universe selection, and backtesting of an end-of-day momentum strategy.

  Jupyter Notebook

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  Apache License 2.0

  •2•8•0•0•Updated Apr 25, 2024Apr 25, 2024

• zipline-intro

  Public
  Introductory tutorial for Zipline demonstrating data collection, interactive research, and backtesting of a momentum strategy for equities. Uses free sample data.

  Jupyter Notebook

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  Apache License 2.0

  •5•11•0•0•Updated Apr 25, 2024Apr 25, 2024

• sell-gap

  Public
  Intraday Zipline strategy for US stocks that sells stocks which gap below their moving average after previously trading above it. Demonstrates live trading.

  Jupyter Notebook

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  Apache License 2.0

  •2•2•0•0•Updated Apr 24, 2024Apr 24, 2024

• quant-finance-lectures

  Public
  Learn quantitative finance with this comprehensive lecture series. Adapted from the Quantopian Lecture Series. Uses free sample data.

  Jupyter Notebook

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  Other

  •172•383•0•0•Updated Apr 23, 2024Apr 23, 2024

• fundamental-factors

  Public
  Learn how to research fundamental factors using Pipeline, Alphalens, and Sharadar price and fundamental data.

  Jupyter Notebook

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  Apache License 2.0

  •9•10•0•0•Updated Apr 23, 2024Apr 23, 2024

• trend-day

  Public
  Intraday momentum strategy that buys (sells) leveraged ETFs late in the trading session following a significant intraday gain (loss) and holds until the close. From Ernie Chan's book Algorithmic Trading. Runs in Moonshot.

  Jupyter Notebook

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  Apache License 2.0

  •8•24•0•0•Updated Apr 23, 2024Apr 23, 2024

• pipeline-tutorial

  Public
  In-depth walkthrough of Pipeline, an API for filtering and performing computations on large universes of securities. The Pipeline API is part of Zipline but can also be used on a standalone basis.

  Jupyter Notebook

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  Apache License 2.0

  •6•9•0•0•Updated Apr 23, 2024Apr 23, 2024

• pairs-pipeline

  Public
  Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for cointegration using the Johansen test, then runs in-sample backtests on all cointegrating pairs, then runs an out-of-sample backtest on the 5 best performing pairs.

  Jupyter Notebook

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  Apache License 2.0

  •15•35•0•0•Updated Apr 23, 2024Apr 23, 2024

• kitchensink-ml

  Public
  Machine learning strategy that trains the model using "everything and the kitchen sink": fundamentals, technical indicators, returns, price levels, volume and volatility spikes, liquidity, market breadth, and more. Runs in Moonshot. Utilizes data from Sharadar and IB.

  Jupyter Notebook

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  Apache License 2.0

  •9•14•0•0•Updated Apr 23, 2024Apr 23, 2024

• fx-bizday

  Public
  Intraday forex strategy that exploits the tendency of currencies to depreciate during local business hours and appreciate during foreign business hours.

  Jupyter Notebook

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  Apache License 2.0

  •4•6•0•0•Updated Apr 23, 2024Apr 23, 2024

• calspread

  Public
  Intraday trading strategy for futures calendar spreads. Uses crude oil futures and 1-minute bid/ask bars from Interactive Brokers with a Bollinger Band mean reversion strategy. Runs in Moonshot. Demonstrates using exchange native spreads for live/paper trading, and non-native spreads for backtesting.

  Jupyter Notebook

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  Apache License 2.0

  •8•11•0•0•Updated Apr 23, 2024Apr 23, 2024

• futures-import

  Public
  Tutorial for importing historical futures data from a third-party data provider and combining it with recent data from Interactive Brokers in a Zipline bundle.

  Jupyter Notebook

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  Apache License 2.0

  •0•0•0•0•Updated Dec 14, 2023Dec 14, 2023

• market-cap-vs-dollar-volume

  Public
  Jupyter Notebook

  •2•1•0•0•Updated Oct 18, 2023Oct 18, 2023

• backtest-speed-comparison

  Public
  Trading strategies used to test the speed of Moonshot, Zipline, and Lean. See https://www.quantrocket.com/blog/backtest-speed-comparison/ for the results.

  Python

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  Apache License 2.0

  •2•3•0•0•Updated Aug 8, 2023Aug 8, 2023

• global-market-profiles

  Public
  Comparative analysis of stock market characteristics for 17 countries, including number of listings, short sale availability, volatility, distribution of sectors, etc.

  Jupyter Notebook

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  Apache License 2.0

  •4•2•0•0•Updated Jun 1, 2023Jun 1, 2023

• vmot

  Public
  Value/Momentum/Trend strategy modeled on Alpha Architect's VMOT ETF.

  Jupyter Notebook

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  Apache License 2.0

  •3•7•0•0•Updated Jun 1, 2023Jun 1, 2023

• qval

  Public
  Value strategy for US stocks modeled on Alpha Architect's QVAL ETF, using enterprise multiple and Piotroski F-Score to target cheap, high-quality stocks. Utilizes Sharadar fundamental and price data. Runs in Moonshot.

  quantrocket-codeloadquantrocket-codeload-moonshot

  Jupyter Notebook

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  Apache License 2.0

  •8•7•0•0•Updated Jun 1, 2023Jun 1, 2023

• qmom

  Public
  Long-only momentum strategy modeled on Alpha Architect's QMOM ETF, selecting stocks with the smoothest momentum and rebalancing the portfolio before quarter end to capture a window-dressing seasonality effect.

  Jupyter Notebook

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  Apache License 2.0

  •5•8•0•0•Updated Jun 1, 2023Jun 1, 2023

• first-last

  Public
  Intraday momentum strategy that buys (sells) the S&P 500 when the first half hour return and penultimate half hour return are both positive (negative). Uses VIX filter to restrict strategy to high volatility regimes. Uses 30-minute data from Interactive Brokers. Runs in Moonshot.

  Jupyter Notebook

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  Apache License 2.0

  •1•7•0•0•Updated Jun 1, 2023Jun 1, 2023

• dead-cat-drop

  Public
  Moonshot strategy that shorts stocks that fell 10% or more the previous day. Demonstrates running a multi-country backtest to find where an anomaly works best. Uses global equities data from EDI.

  Jupyter Notebook

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  Apache License 2.0

  •2•0•0•0•Updated Jun 1, 2023Jun 1, 2023

• backtrader-dma

  Public
  dual moving average crossover strategy for backtrader

  Jupyter Notebook

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  Apache License 2.0

  •3•4•0•0•Updated Jun 1, 2023Jun 1, 2023

• benchmark

  Public
  Equal-weighted and dollar-volume-weighted benchmark strategies for Moonshot

  Python

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  Apache License 2.0

  •1•1•0•0•Updated Jun 1, 2023Jun 1, 2023

• hello-jupyter

  Public
  A simple introduction to Jupyter notebooks, to demonstrate how cloning works.

  Jupyter Notebook

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  Apache License 2.0

  •1•1•0•0•Updated Nov 15, 2022Nov 15, 2022

• zipline-futures-pairs

  Public
  futures pairs trading Zipline strategy

  Jupyter Notebook

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  Apache License 2.0

  •4•2•1•0•Updated Nov 3, 2018Nov 3, 2018

• hml

  Public
  HML (High Minus Low) strategy for Moonshot and Zipline, using Reuters Fundamentals

  Python

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  Apache License 2.0

  •2•1•0•0•Updated Oct 27, 2018Oct 27, 2018