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awesome-quant

github.com/eric-erki/awesome-quant ↗

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

1
GitHub Stars
203
Curated Resources
12
Categories
17 hours ago
Last Refreshed
PythonRMatlabJuliaJavaJavaScriptHaskellScalaRubyFrameworksCSharpReproducing Works

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What's inside

Python

  • aatTrading & Backtesting

    Async Algorithmic Trading Engine

  • after-hoursData Sources

    Obtain pre market and after hours stock prices for a given symbol.

  • algobrokerTrading & Backtesting

    This is an execution engine for algo trading.

  • alpaca-trade-apiData Sources

    Python interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.

  • alphalensFactor Analysis

    Performance analysis of predictive alpha factors.

  • analyzerTrading & Backtesting

    Python framework for real-time financial and backtesting trading strategies.

R

  • AmericanCallOptFinancial Instruments and Pricing

    This package includes pricing function for selected American call options with underlying assets that generate payouts.

  • backtestTrading

    Exploring Portfolio-Based Conjectures About Financial Instruments.

  • bizdaysCalendars

    Business days calculations and utilities

  • covFactorModelFinancial Instruments and Pricing

    Covariance matrix estimation via factor models.

  • creduleFinancial Instruments and Pricing

    Credit Default Swap Functions.

  • data.tableNumerical Libraries & Data Structures

    Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.

Reproducing Works

  • Derman Papers

    Notebooks that replicate original quantitative finance papers from Emanuel Derman.

  • fecon235Risk Analysis

    Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.

  • quant

    Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.

  • volatility-trading

    A complete set of volatility estimators based on Euan Sinclair's Volatility Trading.

Java

  • DRIP

    Fixed Income, Asset Allocation, Transaction Cost Analysis, XVA Metrics Libraries.

  • finmath.net

    Java library with algorithms and methodologies related to mathematical finance.

  • quantcomponents

    Free Java components for Quantitative Finance and Algorithmic Trading.

  • Strata

    Modern open-source analytics and market risk library designed and written in Java.

Julia

  • FinancialMarkets.jl

    Describe and model financial markets objects using Julia.

  • Indicators.jl

    Financial market technical analysis & indicators on top of Temporal.

  • Ito.jl

    A Julia package for quantitative finance.

  • MarketData.jl

    Time series market data.

  • MarketTechnicals.jl

    Technical analysis of financial time series on top of TimeSeries.

  • Miletus.jl

    A financial contract definition, modeling language, and valuation framework.

Haskell

  • hqfl

    Haskell Quantitative Finance Library.

  • quantfin

    quant finance in pure haskell.

Ruby

  • Jiji

    Open Source Forex algorithmic trading framework using OANDA REST API.

Frameworks

Showing a sample of 203 resources. View the full list on GitHub →