quantrocket-codeload Goto Github PK
Name: QuantRocket Codeload Library
Type: Organization
Bio: Sample code and notebooks for QuantRocket. For main GitHub organization see link:
Name: QuantRocket Codeload Library
Type: Organization
Bio: Sample code and notebooks for QuantRocket. For main GitHub organization see link:
Trading strategies used to test the speed of Moonshot, Zipline, and Lean. See https://www.quantrocket.com/blog/backtest-speed-comparison/ for the results.
dual moving average crossover strategy for backtrader
Equal-weighted and dollar-volume-weighted benchmark strategies for Moonshot
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.
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.
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.
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.
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.
Learn how to research fundamental factors using Pipeline, Alphalens, and Sharadar price and fundamental data.
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.
Intraday forex strategy that exploits the tendency of currencies to depreciate during local business hours and appreciate during foreign business hours.
Comparative analysis of stock market characteristics for 17 countries, including number of listings, short sale availability, volatility, distribution of sectors, etc.
A simple introduction to Jupyter notebooks, to demonstrate how cloning works.
HML (High Minus Low) strategy for Moonshot and Zipline, using Reuters Fundamentals
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.
Introductory tutorial for Moonshot demonstrating data collection, universe selection, and backtesting of an end-of-day momentum strategy.
Introductory tutorial for MoonshotML demonstrating walk-forward optimization of a simple machine learning strategy. Uses free sample data.
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.
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.
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.
Learn quantitative finance with this comprehensive lecture series. Adapted from the Quantopian Lecture Series. Uses free sample data.
QuickStart notebooks for QuantRocket
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.
Intraday Zipline strategy for US stocks that sells stocks which gap below their moving average after previously trading above it. Demonstrates live trading.
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.
Value/Momentum/Trend strategy modeled on Alpha Architect's VMOT ETF.
futures pairs trading Zipline strategy
Introductory tutorial for Zipline demonstrating data collection, interactive research, and backtesting of a momentum strategy for equities. Uses free sample data.
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