1482 lines
73 KiB
HTML
1482 lines
73 KiB
HTML
<h1 id="awesome-quant">Awesome Quant</h1>
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<p>A curated list of insanely awesome libraries, packages and resources
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for Quants (Quantitative Finance).</p>
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<p><a href="https://awesome.re"><img
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src="https://awesome.re/badge.svg" /></a></p>
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<h2 id="languages">Languages</h2>
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<ul>
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<li><a href="#python">Python</a></li>
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<li><a href="#r">R</a></li>
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<li><a href="#matlab">Matlab</a></li>
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<li><a href="#julia">Julia</a></li>
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<li><a href="#java">Java</a></li>
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<li><a href="#javascript">JavaScript</a></li>
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<li><a href="#haskell">Haskell</a></li>
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<li><a href="#scala">Scala</a></li>
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<li><a href="#ruby">Ruby</a></li>
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<li><a href="#elixirerlang">Elixir/Erlang</a></li>
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<li><a href="#golang">Golang</a></li>
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<li><a href="#cpp">CPP</a></li>
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<li><a href="#csharp">CSharp</a></li>
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<li><a href="#rust">Rust</a></li>
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<li><a href="#frameworks">Frameworks</a></li>
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<li><a href="#reproducing-works-training--books">Reproducing Works,
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Training & Books</a></li>
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</ul>
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<h2 id="python">Python</h2>
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<h3 id="numerical-libraries-data-structures">Numerical Libraries &
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Data Structures</h3>
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<ul>
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<li><a href="https://www.numpy.org">numpy</a> - NumPy is the fundamental
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package for scientific computing with Python.</li>
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<li><a href="https://www.scipy.org">scipy</a> - SciPy (pronounced “Sigh
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Pie”) is a Python-based ecosystem of open-source software for
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mathematics, science, and engineering.</li>
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<li><a href="https://pandas.pydata.org">pandas</a> - pandas is an open
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source, BSD-licensed library providing high-performance, easy-to-use
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data structures and data analysis tools for the Python programming
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language.</li>
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<li><a href="https://docs.pola.rs/">polars</a> - Polars is a blazingly
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fast DataFrame library for manipulating structured data.</li>
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<li><a href="https://github.com/johnbywater/quantdsl">quantdsl</a> -
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Domain specific language for quantitative analytics in finance and
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trading.</li>
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<li><a
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href="https://docs.python.org/3/library/statistics.html">statistics</a>
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- Builtin Python library for all basic statistical calculations.</li>
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<li><a href="https://www.sympy.org/">sympy</a> - SymPy is a Python
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library for symbolic mathematics.</li>
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<li><a href="https://docs.pymc.io/">pymc3</a> - Probabilistic
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Programming in Python: Bayesian Modeling and Probabilistic Machine
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Learning with Theano.</li>
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<li><a href="https://docs.modelx.io/">modelx</a> - Python reimagination
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of spreadsheets as formula-centric objects that are interoperable with
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pandas.</li>
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<li><a href="https://github.com/man-group/ArcticDB">ArcticDB</a> - High
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performance datastore for time series and tick data.</li>
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</ul>
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<h3 id="financial-instruments-and-pricing">Financial Instruments and
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Pricing</h3>
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<ul>
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<li><a href="https://github.com/OpenBB-finance/OpenBBTerminal">OpenBB
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Terminal</a> - Terminal for investment research for everyone.</li>
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<li><a
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href="https://github.com/Fincept-Corporation/FinceptTerminal">Fincept
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Terminal</a> - Advance Data Based A.I Terminal for all Types of
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Financial Asset Research.</li>
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<li><a href="https://github.com/enthought/pyql">PyQL</a> - QuantLib’s
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Python port.</li>
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<li><a href="https://github.com/opendoor-labs/pyfin">pyfin</a> - Basic
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options pricing in Python. <em>ARCHIVED</em></li>
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<li><a href="https://github.com/vollib/vollib">vollib</a> - vollib is a
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python library for calculating option prices, implied volatility and
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greeks.</li>
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<li><a href="https://github.com/jsmidt/QuantPy">QuantPy</a> - A
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framework for quantitative finance In python.</li>
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<li><a
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href="https://github.com/alpha-miner/Finance-Python">Finance-Python</a>
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- Python tools for Finance.</li>
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<li><a href="https://github.com/pmorissette/ffn">ffn</a> - A financial
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function library for Python.</li>
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<li><a href="https://github.com/GriffinAustin/pynance">pynance</a> -
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Lightweight Python library for assembling and analyzing financial
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data.</li>
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<li><a href="https://github.com/bpsmith/tia">tia</a> - Toolkit for
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integration and analysis.</li>
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<li><a
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href="https://platform.hasura.io/hub/projects/hasura/base-python-dash">hasura/base-python-dash</a>
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- Hasura quick start to deploy Dash framework. Written on top of Flask,
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Plotly.js, and React.js, Dash is ideal for building data visualization
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apps with highly custom user interfaces in pure Python.</li>
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<li><a
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href="https://platform.hasura.io/hub/projects/hasura/base-python-bokeh">hasura/base-python-bokeh</a>
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- Hasura quick start to visualize data with bokeh library.</li>
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<li><a href="https://github.com/ynouri/pysabr">pysabr</a> - SABR model
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Python implementation.</li>
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<li><a href="https://github.com/domokane/FinancePy">FinancePy</a> - A
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Python Finance Library that focuses on the pricing and risk-management
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of Financial Derivatives, including fixed-income, equity, FX and credit
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derivatives.</li>
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<li><a href="https://github.com/goldmansachs/gs-quant">gs-quant</a> -
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Python toolkit for quantitative finance</li>
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<li><a
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href="https://github.com/federicomariamassari/willowtree">willowtree</a>
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- Robust and flexible Python implementation of the willow tree lattice
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for derivatives pricing.</li>
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<li><a
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href="https://github.com/federicomariamassari/financial-engineering">financial-engineering</a>
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- Applications of Monte Carlo methods to financial engineering projects,
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in Python.</li>
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<li><a href="https://github.com/dbrojas/optlib">optlib</a> - A library
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for financial options pricing written in Python.</li>
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<li><a
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href="https://github.com/google/tf-quant-finance">tf-quant-finance</a> -
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High-performance TensorFlow library for quantitative finance.</li>
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<li><a href="https://github.com/RomanMichaelPaolucci/Q-Fin">Q-Fin</a> -
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A Python library for mathematical finance.</li>
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<li><a href="https://github.com/quantsbin/Quantsbin">Quantsbin</a> -
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Tools for pricing and plotting of vanilla option prices, greeks and
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various other analysis around them.</li>
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<li><a href="https://github.com/bbcho/finoptions-dev">finoptions</a> -
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Complete python implementation of R package fOptions with partial
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implementation of fExoticOptions for pricing various options.</li>
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<li><a href="https://github.com/ymyke/pypme">pypme</a> - PME (Public
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Market Equivalent) calculation.</li>
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<li><a href="https://github.com/yellowbean/AbsBox">AbsBox</a> - A Python
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based library to model cashflow for structured product like Asset-backed
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securities (ABS) and Mortgage-backed securities (MBS).</li>
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<li><a
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href="https://github.com/akashaero/Intrinsic-Value-Calculator">Intrinsic-Value-Calculator</a>
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- A Python tool for quick calculations of a stock’s fair value using
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Discounted Cash Flow analysis.</li>
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<li><a
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href="https://github.com/deltaray-io/kelly-criterion">Kelly-Criterion</a>
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- Kelly Criterion implemented in Python to size portfolios based on J.
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L. Kelly Jr’s formula.</li>
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<li><a href="https://github.com/attack68/rateslib">rateslib</a> - A
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fixed income library for pricing bonds and bond futures, and derivatives
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such as IRS, cross-currency and FX swaps.</li>
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<li><a href="https://github.com/jkirkby3/fypy">fypy</a> - Vanilla and
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exotic option pricing library to support quantitative R&D. Focus on
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pricing interesting/useful models and contracts (including and beyond
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Black-Scholes), as well as calibration of financial models to market
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data.</li>
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</ul>
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<h3 id="indicators">Indicators</h3>
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<ul>
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<li><a
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href="https://github.com/femtotrader/pandas_talib">pandas_talib</a> - A
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Python Pandas implementation of technical analysis indicators.</li>
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<li><a href="https://github.com/peerchemist/finta">finta</a> - Common
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financial technical analysis indicators implemented in Pandas.</li>
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<li><a href="https://github.com/cirla/tulipy">Tulipy</a> - Financial
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Technical Analysis Indicator Library (Python bindings for <a
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href="https://github.com/TulipCharts/tulipindicators">tulipindicators</a>)</li>
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<li><a
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href="https://github.com/Boulder-Investment-Technologies/lppls">lppls</a>
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- A Python module for fitting the <a
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href="https://en.wikipedia.org/wiki/Didier_Sornette#The_JLS_and_LPPLS_models">Log-Periodic
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Power Law Singularity (LPPLS)</a> model.</li>
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<li><a href="https://github.com/nardew/talipp">talipp</a> - Incremental
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technical analysis library for Python.</li>
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<li><a
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href="https://github.com/mr-easy/streaming_indicators">streaming_indicators</a>
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- A python library for computing technical analysis indicators on
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streaming data.</li>
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</ul>
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<h3 id="trading-backtesting">Trading & Backtesting</h3>
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<ul>
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<li><a href="https://github.com/skfolio/skfolio">skfolio</a> - Python
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library for portfolio optimization built on top of scikit-learn. It
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provides a unified interface and sklearn compatible tools to build, tune
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and cross-validate portfolio models.</li>
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<li><a
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href="https://github.com/coding-kitties/investing-algorithm-framework">Investing
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algorithm framework</a> - Framework for developing, backtesting, and
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deploying automated trading algorithms.</li>
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<li><a href="https://github.com/mhallsmoore/qstrader">QSTrader</a> -
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QSTrader backtesting simulation engine.</li>
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<li><a href="https://github.com/Blankly-Finance/Blankly">Blankly</a> -
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Fully integrated backtesting, paper trading, and live deployment.</li>
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<li><a href="https://github.com/mrjbq7/ta-lib">TA-Lib</a> - Python
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wrapper for TA-Lib (<a href="http://ta-lib.org/"
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class="uri">http://ta-lib.org/</a>).</li>
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<li><a href="https://github.com/quantopian/zipline">zipline</a> -
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Pythonic algorithmic trading library.</li>
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<li><a
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href="https://github.com/stefan-jansen/zipline-reloaded">zipline-reloaded</a>
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- Zipline, a Pythonic Algorithmic Trading Library.</li>
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<li><a
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href="https://github.com/QuantSoftware/QuantSoftwareToolkit">QuantSoftware
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Toolkit</a> - Python-based open source software framework designed to
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support portfolio construction and management.</li>
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<li><a
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href="https://github.com/jeffrey-liang/quantitative">quantitative</a> -
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Quantitative finance, and backtesting library.</li>
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<li><a href="https://github.com/llazzaro/analyzer">analyzer</a> - Python
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framework for real-time financial and backtesting trading
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strategies.</li>
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<li><a href="https://github.com/pmorissette/bt">bt</a> - Flexible
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Backtesting for Python.</li>
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<li><a href="https://github.com/backtrader/backtrader">backtrader</a> -
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Python Backtesting library for trading strategies.</li>
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<li><a
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href="https://github.com/thalesians/pythalesians">pythalesians</a> -
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Python library to backtest trading strategies, plot charts, seamlessly
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download market data, analyze market patterns etc.</li>
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<li><a href="https://github.com/ematvey/pybacktest">pybacktest</a> -
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Vectorized backtesting framework in Python / pandas, designed to make
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your backtesting easier.</li>
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<li><a href="https://github.com/gbeced/pyalgotrade">pyalgotrade</a> -
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Python Algorithmic Trading Library.</li>
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<li><a href="https://github.com/gbeced/basana">basana</a> - A Python
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async and event driven framework for algorithmic trading, with a focus
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on crypto currencies.</li>
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<li><a
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href="https://pypi.org/project/tradingWithPython/">tradingWithPython</a>
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- A collection of functions and classes for Quantitative trading.</li>
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<li><a href="https://github.com/twopirllc/pandas-ta">Pandas TA</a> -
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Pandas TA is an easy to use Python 3 Pandas Extension with 115+
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Indicators. Easily build Custom Strategies.</li>
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<li><a href="https://github.com/bukosabino/ta">ta</a> - Technical
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Analysis Library using Pandas (Python)</li>
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<li><a href="https://github.com/joequant/algobroker">algobroker</a> -
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This is an execution engine for algo trading.</li>
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<li><a href="https://pypi.org/project/pysentosa/">pysentosa</a> - Python
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API for sentosa trading system.</li>
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<li><a href="https://github.com/cuemacro/finmarketpy">finmarketpy</a> -
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Python library for backtesting trading strategies and analyzing
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financial markets.</li>
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<li><a
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href="https://github.com/metaperl/binary-martingale">binary-martingale</a>
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- Computer program to automatically trade binary options martingale
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style.</li>
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<li><a href="https://github.com/foolcage/fooltrader">fooltrader</a> -
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the project using big-data technology to provide an uniform way to
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analyze the whole market.</li>
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<li><a href="https://github.com/zvtvz/zvt">zvt</a> - the project using
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sql, pandas to provide an uniform and extendable way to record data,
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computing factors, select securities, backtesting, realtime trading and
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it could show all of them in clearly charts in realtime.</li>
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<li><a href="https://github.com/alpacahq/pylivetrader">pylivetrader</a>
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- zipline-compatible live trading library.</li>
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<li><a
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href="https://github.com/alpacahq/pipeline-live">pipeline-live</a> -
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zipline’s pipeline capability with IEX for live trading.</li>
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<li><a
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href="https://github.com/quantrocket-llc/zipline-extensions">zipline-extensions</a>
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- Zipline extensions and adapters for QuantRocket.</li>
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<li><a href="https://github.com/quantrocket-llc/moonshot">moonshot</a> -
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Vectorized backtester and trading engine for QuantRocket based on
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Pandas.</li>
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<li><a
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href="https://github.com/robertmartin8/PyPortfolioOpt">PyPortfolioOpt</a>
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- Financial portfolio optimization in python, including classical
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efficient frontier and advanced methods.</li>
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<li><a href="https://github.com/tradytics/eiten">Eiten</a> - Eiten is an
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open source toolkit by Tradytics that implements various statistical and
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algorithmic investing strategies such as Eigen Portfolios, Minimum
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Variance Portfolios, Maximum Sharpe Ratio Portfolios, and Genetic
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Algorithms based Portfolios.</li>
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<li><a
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href="https://github.com/dppalomar/riskparity.py">riskparity.py</a> -
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fast and scalable design of risk parity portfolios with TensorFlow
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2.0</li>
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<li><a href="https://github.com/hudson-and-thames/mlfinlab">mlfinlab</a>
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- Implementations regarding “Advances in Financial Machine Learning” by
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Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures,
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Meta-Labeling)</li>
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<li><a href="https://github.com/abbass2/pyqstrat">pyqstrat</a> - A fast,
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extensible, transparent python library for backtesting quantitative
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strategies.</li>
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<li><a href="https://github.com/edouardpoitras/NowTrade">NowTrade</a> -
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Python library for backtesting technical/mechanical strategies in the
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stock and currency markets.</li>
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<li><a href="https://github.com/fja05680/pinkfish">pinkfish</a> - A
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backtester and spreadsheet library for security analysis.</li>
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<li><a href="https://github.com/timkpaine/aat">aat</a> - Async
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Algorithmic Trading Engine</li>
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<li><a href="https://kernc.github.io/backtesting.py/">Backtesting.py</a>
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- Backtest trading strategies in Python</li>
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<li><a href="https://github.com/enigmampc/catalyst">catalyst</a> - An
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Algorithmic Trading Library for Crypto-Assets in Python</li>
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<li><a href="https://github.com/ranaroussi/quantstats">quantstats</a> -
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Portfolio analytics for quants, written in Python</li>
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<li><a href="https://github.com/ranaroussi/qtpylib">qtpylib</a> -
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QTPyLib, Pythonic Algorithmic Trading <a href="http://qtpylib.io"
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class="uri">http://qtpylib.io</a></li>
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<li><a href="https://github.com/constverum/Quantdom">Quantdom</a> -
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Python-based framework for backtesting trading strategies &
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analyzing financial markets [GUI :neckbeard:]</li>
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<li><a href="https://github.com/freqtrade/freqtrade">freqtrade</a> -
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Free, open source crypto trading bot</li>
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<li><a
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href="https://github.com/chrisconlan/algorithmic-trading-with-python">algorithmic-trading-with-python</a>
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- Free <code>pandas</code> and <code>scikit-learn</code> resources for
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trading simulation, backtesting, and machine learning on financial
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data.</li>
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<li><a href="https://github.com/jankrepl/deepdow">DeepDow</a> -
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Portfolio optimization with deep learning</li>
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<li><a href="https://github.com/microsoft/qlib">Qlib</a> - An
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AI-oriented Quantitative Investment Platform by Microsoft. Full ML
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pipeline of data processing, model training, back-testing; and covers
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the entire chain of quantitative investment: alpha seeking, risk
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modeling, portfolio optimization, and order execution.</li>
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<li><a
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href="https://github.com/stefan-jansen/machine-learning-for-trading">machine-learning-for-trading</a>
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- Code and resources for Machine Learning for Algorithmic Trading</li>
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<li><a href="https://github.com/ScottfreeLLC/AlphaPy">AlphaPy</a> -
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Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,
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XGBoost, LightGBM, and CatBoost</li>
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<li><a href="https://github.com/jesse-ai/jesse">jesse</a> - An advanced
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crypto trading bot written in Python</li>
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<li><a href="https://github.com/ricequant/rqalpha">rqalpha</a> - A
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extendable, replaceable Python algorithmic backtest && trading
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framework supporting multiple securities.</li>
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<li><a
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href="https://github.com/AI4Finance-LLC/FinRL-Library">FinRL-Library</a>
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- A Deep Reinforcement Learning Library for Automated Trading in
|
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Quantitative Finance. NeurIPS 2020.</li>
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<li><a href="https://github.com/achillesrasquinha/bulbea">bulbea</a> -
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Deep Learning based Python Library for Stock Market Prediction and
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Modelling.</li>
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<li><a href="https://github.com/ajhpark/ib_nope">ib_nope</a> - Automated
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trading system for NOPE strategy over IBKR TWS.</li>
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<li><a href="https://github.com/Drakkar-Software/OctoBot">OctoBot</a> -
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Open source cryptocurrency trading bot for high frequency, arbitrage, TA
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and social trading with an advanced web interface.</li>
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<li><a href="https://github.com/mementum/bta-lib">bta-lib</a> -
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Technical Analysis library in pandas for backtesting algotrading and
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quantitative analysis.</li>
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<li><a
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href="https://github.com/huseinzol05/Stock-Prediction-Models">Stock-Prediction-Models</a>
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- Gathers machine learning and deep learning models for Stock
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forecasting including trading bots and simulations.</li>
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<li><a href="https://github.com/jmrichardson/tuneta">TuneTA</a> - TuneTA
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optimizes technical indicators using a distance correlation measure to a
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user defined target feature such as next day return.</li>
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<li><a href="https://github.com/kieran-mackle/AutoTrader">AutoTrader</a>
|
||
- A Python-based development platform for automated trading systems -
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from backtesting to optimization to livetrading.</li>
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||
<li><a href="https://github.com/jrmeier/fast-trade">fast-trade</a> - A
|
||
library built with backtest portability and performance in mind for
|
||
backtest trading strategies.</li>
|
||
<li><a href="https://github.com/quarkfin/qf-lib">qf-lib</a> - QF-Lib is
|
||
a Python library that provides high quality tools for quantitative
|
||
finance.</li>
|
||
<li><a href="https://github.com/alexgolec/tda-api">tda-api</a> - Gather
|
||
data and trade equities, options, and ETFs via TDAmeritrade.</li>
|
||
<li><a href="https://github.com/polakowo/vectorbt">vectorbt</a> - Find
|
||
your trading edge, using a powerful toolkit for backtesting, algorithmic
|
||
trading, and research.</li>
|
||
<li><a href="https://github.com/QuantConnect/Lean">Lean</a> - Lean
|
||
Algorithmic Trading Engine by QuantConnect (Python, C#).</li>
|
||
<li><a href="https://github.com/jrmeier/fast-trade">fast-trade</a> - Low
|
||
code backtesting library utilizing pandas and technical analysis
|
||
indicators.</li>
|
||
<li><a
|
||
href="https://github.com/robcarver17/pysystemtrade">pysystemtrade</a> -
|
||
pysystemtrade is the open source version of Robert Carver’s backtesting
|
||
and trading engine that implements systems according to the framework
|
||
outlined in his book “Systematic Trading”, which is further developed on
|
||
his <a href="https://qoppac.blogspot.com/">blog</a>.</li>
|
||
<li><a
|
||
href="https://github.com/rafa-rod/pytrendseries">pytrendseries</a> -
|
||
Detect trend in time series, drawdown, drawdown within a constant
|
||
look-back window , maximum drawdown, time underwater.</li>
|
||
<li><a href="https://github.com/DrAshBooth/PyLOB">PyLOB</a> - Fully
|
||
functioning fast Limit Order Book written in Python.</li>
|
||
<li><a href="https://github.com/edtechre/pybroker">PyBroker</a> -
|
||
Algorithmic Trading with Machine Learning.</li>
|
||
<li><a href="https://github.com/Drakkar-Software/OctoBot-Script">OctoBot
|
||
Script</a> - A quant framework to create cryptocurrencies strategies -
|
||
from backtesting to optimization to livetrading.</li>
|
||
<li><a href="https://github.com/nkaz001/hftbacktest">hftbacktest</a> - A
|
||
high-frequency trading and market-making backtesting tool accounts for
|
||
limit orders, queue positions, and latencies, utilizing full tick data
|
||
for trades and order books.</li>
|
||
<li><a href="https://github.com/vnpy/vnpy">vnpy</a> - VeighNa is a
|
||
Python-based open source quantitative trading system development
|
||
framework.</li>
|
||
<li><a
|
||
href="https://github.com/asavinov/intelligent-trading-bot">Intelligent
|
||
Trading Bot</a> - Automatically generating signals and trading based on
|
||
machine learning and feature engineering</li>
|
||
<li><a href="https://github.com/enzoampil/fastquant">fastquant</a> -
|
||
fastquant allows you to easily backtest investment strategies with as
|
||
few as 3 lines of python code.</li>
|
||
<li><a
|
||
href="https://github.com/nautechsystems/nautilus_trader">nautilus_trader</a>
|
||
- A high-performance algorithmic trading platform and event-driven
|
||
backtester.</li>
|
||
<li><a href="https://github.com/bsdz/yabte">YABTE</a> - Yet Another
|
||
(Python) BackTesting Engine.</li>
|
||
<li><a
|
||
href="https://github.com/tradingstrategy-ai/getting-started">Trading
|
||
Strategy</a> - TradingStrategy.ai is a market data, backtesting, live
|
||
trading and investor management framework for decentralised finance</li>
|
||
<li><a href="https://github.com/fasiondog/hikyuu">Hikyuu</a> - A base on
|
||
Python/C++ open source high-performance quant framework for faster
|
||
analysis and backtesting, contains the complete trading system
|
||
components for reuse and combination.</li>
|
||
<li><a href="https://github.com/jensnesten/rust_bt">rust_bt</a> - A high
|
||
performance, low-latency backtesting engine for testing quantitative
|
||
trading strategies on historical and live data in Rust.</li>
|
||
</ul>
|
||
<h3 id="risk-analysis">Risk Analysis</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/auto-differentiation/QuantLib-Risks-Py">QuantLibRisks</a>
|
||
- Fast risks with QuantLib</li>
|
||
<li><a href="https://github.com/auto-differentiation/xad-py">XAD</a> -
|
||
Automatic Differentation (AAD) Library</li>
|
||
<li><a href="https://github.com/quantopian/pyfolio">pyfolio</a> -
|
||
Portfolio and risk analytics in Python.</li>
|
||
<li><a href="https://github.com/quantopian/empyrical">empyrical</a> -
|
||
Common financial risk and performance metrics.</li>
|
||
<li><a href="https://github.com/rsvp/fecon235">fecon235</a> -
|
||
Computational tools for financial economics include: Gaussian Mixture
|
||
model of leptokurtotic risk, adaptive Boltzmann portfolios.</li>
|
||
<li><a href="https://pypi.org/project/finance/">finance</a> - Financial
|
||
Risk Calculations. Optimized for ease of use through class construction
|
||
and operator overload.</li>
|
||
<li><a href="https://pypi.org/project/qfrm/">qfrm</a> - Quantitative
|
||
Financial Risk Management: awesome OOP tools for measuring, managing and
|
||
visualizing risk of financial instruments and portfolios.</li>
|
||
<li><a
|
||
href="https://github.com/benjaminmgross/visualize-wealth">visualize-wealth</a>
|
||
- Portfolio construction and quantitative analysis.</li>
|
||
<li><a
|
||
href="https://github.com/wegamekinglc/VisualPortfolio">VisualPortfolio</a>
|
||
- This tool is used to visualize the performance of a portfolio.</li>
|
||
<li><a
|
||
href="https://github.com/Marigold/universal-portfolios">universal-portfolios</a>
|
||
- Collection of algorithms for online portfolio selection.</li>
|
||
<li><a href="https://github.com/fmilthaler/FinQuant">FinQuant</a> - A
|
||
program for financial portfolio management, analysis and
|
||
optimization.</li>
|
||
<li><a href="https://github.com/ssantoshp/Empyrial">Empyrial</a> -
|
||
Portfolio’s risk and performance analytics and returns predictions.</li>
|
||
<li><a href="https://github.com/bbcho/risktools-dev">risktools</a> -
|
||
Risk tools for use within the crude and crude products trading space
|
||
with partial implementation of R’s PerformanceAnalytics.</li>
|
||
<li><a href="https://github.com/dcajasn/Riskfolio-Lib">Riskfolio-Lib</a>
|
||
- Portfolio Optimization and Quantitative Strategic Asset Allocation in
|
||
Python.</li>
|
||
<li><a
|
||
href="https://github.com/stefan-jansen/empyrical-reloaded">empyrical-reloaded</a>
|
||
- Common financial risk and performance metrics. <a
|
||
href="https://github.com/quantopian/empyrical">empyrical</a> fork.</li>
|
||
<li><a
|
||
href="https://github.com/stefan-jansen/pyfolio-reloaded">pyfolio-reloaded</a>
|
||
- Portfolio and risk analytics in Python. <a
|
||
href="https://github.com/quantopian/pyfolio">pyfolio</a> fork.</li>
|
||
<li><a
|
||
href="https://github.com/fortitudo-tech/fortitudo.tech">fortitudo.tech</a>
|
||
- Conditional Value-at-Risk (CVaR) portfolio optimization and Entropy
|
||
Pooling views / stress-testing in Python.</li>
|
||
</ul>
|
||
<h3 id="factor-analysis">Factor Analysis</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/quantopian/alphalens">alphalens</a> -
|
||
Performance analysis of predictive alpha factors.</li>
|
||
<li><a
|
||
href="https://github.com/stefan-jansen/alphalens-reloaded">alphalens-reloaded</a>
|
||
- Performance analysis of predictive (alpha) stock factors.</li>
|
||
<li><a href="https://github.com/Heerozh/spectre">Spectre</a> -
|
||
GPU-accelerated Factors analysis library and Backtester</li>
|
||
</ul>
|
||
<h3 id="sentiment-analysis">Sentiment Analysis</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/KVignesh122/AssetNewsSentimentAnalyzer">Asset
|
||
News Sentiment Analyzer</a> - Sentiment analysis and report generation
|
||
package for financial assets and securities utilizing GPT models.</li>
|
||
</ul>
|
||
<h3 id="quant-research-environment">Quant Research Environment</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/gnzsnz/jupyter-quant">Jupyter Quant</a>
|
||
- A dockerized Jupyter quant research environment with preloaded tools
|
||
for quant analysis, statsmodels, pymc, arch, py_vollib,
|
||
zipline-reloaded, PyPortfolioOpt, etc.</li>
|
||
</ul>
|
||
<h3 id="time-series">Time Series</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/bashtage/arch">ARCH</a> - ARCH models in
|
||
Python.</li>
|
||
<li><a href="http://statsmodels.sourceforge.net">statsmodels</a> -
|
||
Python module that allows users to explore data, estimate statistical
|
||
models, and perform statistical tests.</li>
|
||
<li><a href="https://github.com/quantmind/dynts">dynts</a> - Python
|
||
package for timeseries analysis and manipulation.</li>
|
||
<li><a href="https://github.com/RJT1990/pyflux">PyFlux</a> - Python
|
||
library for timeseries modelling and inference (frequentist and
|
||
Bayesian) on models.</li>
|
||
<li><a href="https://github.com/blue-yonder/tsfresh">tsfresh</a> -
|
||
Automatic extraction of relevant features from time series.</li>
|
||
<li><a
|
||
href="https://platform.hasura.io/hub/projects/anirudhm/quandl-metabase-time-series">hasura/quandl-metabase</a>
|
||
- Hasura quickstart to visualize Quandl’s timeseries datasets with
|
||
Metabase.</li>
|
||
<li><a href="https://github.com/facebook/prophet">Facebook Prophet</a> -
|
||
Tool for producing high quality forecasts for time series data that has
|
||
multiple seasonality with linear or non-linear growth.</li>
|
||
<li><a href="https://github.com/cerlymarco/tsmoothie">tsmoothie</a> - A
|
||
python library for time-series smoothing and outlier detection in a
|
||
vectorized way.</li>
|
||
<li><a href="https://github.com/alkaline-ml/pmdarima">pmdarima</a> - A
|
||
statistical library designed to fill the void in Python’s time series
|
||
analysis capabilities, including the equivalent of R’s auto.arima
|
||
function.</li>
|
||
<li><a href="https://github.com/awslabs/gluon-ts">gluon-ts</a> -
|
||
vProbabilistic time series modeling in Python.</li>
|
||
<li><a href="https://github.com/functime-org/functime">functime</a> -
|
||
Time-series machine learning at scale. Built with Polars for
|
||
embarrassingly parallel feature extraction and forecasts on panel
|
||
data.</li>
|
||
</ul>
|
||
<h3 id="calendars">Calendars</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/gerrymanoim/exchange_calendars">exchange_calendars</a>
|
||
- Stock Exchange Trading Calendars.</li>
|
||
<li><a
|
||
href="https://github.com/wilsonfreitas/python-bizdays">bizdays</a> -
|
||
Business days calculations and utilities.</li>
|
||
<li><a
|
||
href="https://github.com/rsheftel/pandas_market_calendars">pandas_market_calendars</a>
|
||
- Exchange calendars to use with pandas for trading applications.</li>
|
||
</ul>
|
||
<h3 id="data-sources">Data Sources</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/ranaroussi/yfinance">yfinance</a> -
|
||
Yahoo! Finance market data downloader (+faster Pandas Datareader)</li>
|
||
<li><a href="https://github.com/cuemacro/findatapy">findatapy</a> -
|
||
Python library to download market data via Bloomberg, Quandl, Yahoo
|
||
etc.</li>
|
||
<li><a
|
||
href="https://github.com/hongtaocai/googlefinance">googlefinance</a> -
|
||
Python module to get real-time stock data from Google Finance API.</li>
|
||
<li><a
|
||
href="https://github.com/lukaszbanasiak/yahoo-finance">yahoo-finance</a>
|
||
- Python module to get stock data from Yahoo! Finance.</li>
|
||
<li><a
|
||
href="https://github.com/pydata/pandas-datareader">pandas-datareader</a>
|
||
- Python module to get data from various sources (Google Finance, Yahoo
|
||
Finance, FRED, OECD, Fama/French, World Bank, Eurostat…) into Pandas
|
||
datastructures such as DataFrame, Panel with a caching mechanism.</li>
|
||
<li><a
|
||
href="https://github.com/davidastephens/pandas-finance">pandas-finance</a>
|
||
- High level API for access to and analysis of financial data.</li>
|
||
<li><a href="https://github.com/innes213/pyhoofinance">pyhoofinance</a>
|
||
- Rapidly queries Yahoo Finance for multiple tickers and returns typed
|
||
data for analysis.</li>
|
||
<li><a href="https://github.com/Karthik005/yfinanceapi">yfinanceapi</a>
|
||
- Finance API for Python.</li>
|
||
<li><a href="https://github.com/slawek87/yql-finance">yql-finance</a> -
|
||
yql-finance is simple and fast. API returns stock closing prices for
|
||
current period of time and current stock ticker (i.e. APPL, GOOGL).</li>
|
||
<li><a href="https://github.com/cgoldberg/ystockquote">ystockquote</a> -
|
||
Retrieve stock quote data from Yahoo Finance.</li>
|
||
<li><a href="https://github.com/mcdallas/wallstreet">wallstreet</a> -
|
||
Real time stock and option data.</li>
|
||
<li><a
|
||
href="https://github.com/ZachLiuGIS/stock_extractor">stock_extractor</a>
|
||
- General Purpose Stock Extractors from Online Resources.</li>
|
||
<li><a href="https://github.com/cttn/Stockex">Stockex</a> - Python
|
||
wrapper for Yahoo! Finance API.</li>
|
||
<li><a href="https://github.com/skillachie/finsymbols">finsymbols</a> -
|
||
Obtains stock symbols and relating information for SP500, AMEX, NYSE,
|
||
and NASDAQ.</li>
|
||
<li><a href="https://github.com/avelkoski/FRB">FRB</a> - Python Client
|
||
for FRED® API.</li>
|
||
<li><a href="https://github.com/econdb/inquisitor">inquisitor</a> -
|
||
Python Interface to Econdb.com API.</li>
|
||
<li><a href="https://github.com/nickelkr/yfi">yfi</a> - Yahoo! YQL
|
||
library.</li>
|
||
<li><a
|
||
href="https://pypi.org/project/chinesestockapi/">chinesestockapi</a> -
|
||
Python API to get Chinese stock price.</li>
|
||
<li><a href="https://github.com/akarat/exchange">exchange</a> - Get
|
||
current exchange rate.</li>
|
||
<li><a href="https://github.com/jamescnowell/ticks">ticks</a> - Simple
|
||
command line tool to get stock ticker data.</li>
|
||
<li><a href="https://github.com/bpsmith/pybbg">pybbg</a> - Python
|
||
interface to Bloomberg COM APIs.</li>
|
||
<li><a href="https://github.com/lsbardel/ccy">ccy</a> - Python module
|
||
for currencies.</li>
|
||
<li><a href="https://pypi.org/project/tushare/">tushare</a> - A utility
|
||
for crawling historical and Real-time Quotes data of China stocks.</li>
|
||
<li><a href="https://pypi.org/project/jsm/">jsm</a> - Get the japanese
|
||
stock market data.</li>
|
||
<li><a href="https://github.com/jealous/cn_stock_src">cn_stock_src</a> -
|
||
Utility for retrieving basic China stock data from different
|
||
sources.</li>
|
||
<li><a
|
||
href="https://github.com/barnumbirr/coinmarketcap">coinmarketcap</a> -
|
||
Python API for coinmarketcap.</li>
|
||
<li><a
|
||
href="https://github.com/datawrestler/after-hours">after-hours</a> -
|
||
Obtain pre market and after hours stock prices for a given symbol.</li>
|
||
<li><a href="https://pypi.org/project/bronto-python/">bronto-python</a>
|
||
- Bronto API Integration for Python.</li>
|
||
<li><a href="https://github.com/rainx/pytdx">pytdx</a> - Python
|
||
Interface for retrieving chinese stock realtime quote data from
|
||
TongDaXin Nodes.</li>
|
||
<li><a href="https://github.com/matthewgilbert/pdblp">pdblp</a> - A
|
||
simple interface to integrate pandas and the Bloomberg Open API.</li>
|
||
<li><a href="https://github.com/hydrosquall/tiingo-python">tiingo</a> -
|
||
Python interface for daily composite prices/OHLC/Volume + Real-time News
|
||
Feeds, powered by the Tiingo Data Platform.</li>
|
||
<li><a href="https://github.com/addisonlynch/iexfinance">iexfinance</a>
|
||
- Python Interface for retrieving real-time and historical prices and
|
||
equities data from The Investor’s Exchange.</li>
|
||
<li><a href="https://github.com/timkpaine/pyEX">pyEX</a> - Python
|
||
interface to IEX with emphasis on pandas, support for streaming data,
|
||
premium data, points data (economic, rates, commodities), and technical
|
||
indicators.</li>
|
||
<li><a
|
||
href="https://github.com/alpacahq/alpaca-trade-api-python">alpaca-trade-api</a>
|
||
- Python interface for retrieving real-time and historical prices from
|
||
Alpaca API as well as trade execution.</li>
|
||
<li><a href="https://pypi.org/project/MetaTrader5/">metatrader5</a> -
|
||
API Connector to MetaTrader 5 Terminal</li>
|
||
<li><a href="https://github.com/jindaxiang/akshare">akshare</a> -
|
||
AkShare is an elegant and simple financial data interface library for
|
||
Python, built for human beings! <a href="https://akshare.readthedocs.io"
|
||
class="uri">https://akshare.readthedocs.io</a></li>
|
||
<li><a href="https://github.com/dpguthrie/yahooquery">yahooquery</a> -
|
||
Python interface for retrieving data through unofficial Yahoo Finance
|
||
API.</li>
|
||
<li><a href="https://github.com/alvarobartt/investpy">investpy</a> -
|
||
Financial Data Extraction from Investing.com with Python! <a
|
||
href="https://investpy.readthedocs.io/"
|
||
class="uri">https://investpy.readthedocs.io/</a></li>
|
||
<li><a
|
||
href="https://github.com/yahoofinancelive/yliveticker">yliveticker</a> -
|
||
Live stream of market data from Yahoo Finance websocket.</li>
|
||
<li><a href="https://github.com/ran404/bbgbridge">bbgbridge</a> - Easy
|
||
to use Bloomberg Desktop API wrapper for Python.</li>
|
||
<li><a href="https://github.com/polygon-io/client-python">polygon.io</a>
|
||
- A python library for Polygon.io financial data APIs.</li>
|
||
<li><a
|
||
href="https://github.com/RomelTorres/alpha_vantage">alpha_vantage</a> -
|
||
A python wrapper for Alpha Vantage API for financial data.</li>
|
||
<li><a
|
||
href="https://github.com/FinanceData/FinanceDataReader">FinanceDataReader</a>
|
||
- Open Source Financial data reader for U.S, Korean, Japanese, Chinese,
|
||
Vietnamese Stocks</li>
|
||
<li><a
|
||
href="https://github.com/TomasKoutek/pystlouisfed">pystlouisfed</a> -
|
||
Python client for Federal Reserve Bank of St. Louis API - FRED, ALFRED,
|
||
GeoFRED and FRASER.</li>
|
||
<li><a href="https://github.com/wilsonfreitas/python-bcb">python-bcb</a>
|
||
- Python interface to Brazilian Central Bank web services.</li>
|
||
<li><a
|
||
href="https://github.com/maread99/market_prices">market-prices</a> -
|
||
Create meaningful OHLCV datasets from knowledge of <a
|
||
href="https://github.com/gerrymanoim/exchange_calendars">exchange-calendars</a>
|
||
(works out-the-box with data from Yahoo Finance).</li>
|
||
<li><a
|
||
href="https://github.com/tardis-dev/tardis-python">tardis-python</a> -
|
||
Python interface for Tardis.dev high frequency crypto market data</li>
|
||
<li><a href="https://github.com/crypto-lake/lake-api">lake-api</a> -
|
||
Python interface for Crypto Lake high frequency crypto market data</li>
|
||
<li><a href="https://github.com/ymyke/tessa">tessa</a> - simple,
|
||
hassle-free access to price information of financial assets (currently
|
||
based on yfinance and pycoingecko), including search and a symbol
|
||
class.</li>
|
||
<li><a href="https://github.com/dr-leo/pandaSDMX">pandaSDMX</a> - Python
|
||
package that implements SDMX 2.1 (ISO 17369:2013), a format for exchange
|
||
of statistical data and metadata used by national statistical agencies,
|
||
central banks, and international organisations.</li>
|
||
<li><a href="https://github.com/LenkaV/CIF">cif</a> - Python package
|
||
that include few composite indicators, which summarize multidimensional
|
||
relationships between individual economic indicators.</li>
|
||
<li><a href="https://github.com/theOGognf/finagg">finagg</a> - finagg is
|
||
a Python package that provides implementations of popular and free
|
||
financial APIs, tools for aggregating historical data from those APIs
|
||
into SQL databases, and tools for transforming aggregated data into
|
||
features useful for analysis and AI/ML.</li>
|
||
<li><a
|
||
href="https://github.com/JerBouma/FinanceDatabase">FinanceDatabase</a> -
|
||
This is a database of 300.000+ symbols containing Equities, ETFs, Funds,
|
||
Indices, Currencies, Cryptocurrencies and Money Markets.</li>
|
||
<li><a
|
||
href="https://github.com/tradingstrategy-ai/trading-strategy/">Trading
|
||
Strategy</a> - download price data for decentralised exchanges and
|
||
lending protocols (DeFi)</li>
|
||
<li><a
|
||
href="https://github.com/john-friedman/datamule-python">datamule-python</a>
|
||
- A package to work with SEC data. Incorporates datamule endpoints.</li>
|
||
<li><a href="https://financialdata.net/">Financial Data</a> - Stock
|
||
Market and Financial Data API.</li>
|
||
<li><a href="https://www.developer.saxo/">SaxoOpenAPI</a> - Saxo Bank
|
||
financial data API.</li>
|
||
</ul>
|
||
<h3 id="excel-integration">Excel Integration</h3>
|
||
<ul>
|
||
<li><a href="https://www.xlwings.org/">xlwings</a> - Make Excel fly with
|
||
Python.</li>
|
||
<li><a href="https://openpyxl.readthedocs.io/en/latest/">openpyxl</a> -
|
||
Read/Write Excel 2007 xlsx/xlsm files.</li>
|
||
<li><a href="https://github.com/python-excel/xlrd">xlrd</a> - Library
|
||
for developers to extract data from Microsoft Excel spreadsheet
|
||
files.</li>
|
||
<li><a href="https://xlsxwriter.readthedocs.io/">xlsxwriter</a> - Write
|
||
files in the Excel 2007+ XLSX file format.</li>
|
||
<li><a href="https://github.com/python-excel/xlwt">xlwt</a> - Library to
|
||
create spreadsheet files compatible with MS Excel 97/2000/XP/2003 XLS
|
||
files, on any platform.</li>
|
||
<li><a href="https://datanitro.com/">DataNitro</a> - DataNitro also
|
||
offers full-featured Python-Excel integration, including UDFs. Trial
|
||
downloads are available, but users must purchase a license.</li>
|
||
<li><a href="http://xlloop.sourceforge.net">xlloop</a> - XLLoop is an
|
||
open source framework for implementing Excel user-defined functions
|
||
(UDFs) on a centralised server (a function server).</li>
|
||
<li><a href="http://www.bnikolic.co.uk/expy/expy.html">expy</a> - The
|
||
ExPy add-in allows easy use of Python directly from within an Microsoft
|
||
Excel spreadsheet, both to execute arbitrary code and to define new
|
||
Excel functions.</li>
|
||
<li><a href="https://www.pyxll.com">pyxll</a> - PyXLL is an Excel add-in
|
||
that enables you to extend Excel using nothing but Python code.</li>
|
||
</ul>
|
||
<h3 id="visualization">Visualization</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/man-group/dtale">D-Tale</a> - Visualizer
|
||
for pandas dataframes and xarray datasets.</li>
|
||
<li><a href="https://github.com/matplotlib/mplfinance">mplfinance</a> -
|
||
matplotlib utilities for the visualization, and visual analysis, of
|
||
financial data.</li>
|
||
<li><a href="https://github.com/highfestiva/finplot">finplot</a> -
|
||
Performant and effortless finance plotting for Python.</li>
|
||
<li><a href="https://github.com/lit26/finvizfinance">finvizfinance</a> -
|
||
Finviz analysis python library.</li>
|
||
<li><a href="https://github.com/maread99/market_analy">market-analy</a>
|
||
- Analysis and interactive charting using <a
|
||
href="https://github.com/maread99/market_prices">market-prices</a> and
|
||
bqplot.</li>
|
||
<li><a
|
||
href="https://github.com/ArturSepp/QuantInvestStrats">QuantInvestStrats</a>
|
||
- Quantitative Investment Strategies (QIS) package implements Python
|
||
analytics for visualisation of financial data, performance reporting,
|
||
analysis of quantitative strategies.</li>
|
||
</ul>
|
||
<h2 id="r">R</h2>
|
||
<h3 id="numerical-libraries-data-structures-1">Numerical Libraries &
|
||
Data Structures</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/joshuaulrich/xts">xts</a> - eXtensible
|
||
Time Series: Provide for uniform handling of R’s different time-based
|
||
data classes by extending zoo, maximizing native format information
|
||
preservation and allowing for user level customization and extension,
|
||
while simplifying cross-class interoperability.</li>
|
||
<li><a href="https://github.com/Rdatatable/data.table">data.table</a> -
|
||
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.</li>
|
||
<li><a href="https://github.com/dppalomar/sparseEigen">sparseEigen</a> -
|
||
Sparse principal component analysis.</li>
|
||
<li><a href="http://tsdbi.r-forge.r-project.org/">TSdbi</a> - Provides a
|
||
common interface to time series databases.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/tseries/index.html">tseries</a>
|
||
- Time Series Analysis and Computational Finance.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/zoo/index.html">zoo</a> -
|
||
S3 Infrastructure for Regular and Irregular Time Series (Z’s Ordered
|
||
Observations).</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/tis/index.html">tis</a> -
|
||
Functions and S3 classes for time indexes and time indexed series, which
|
||
are compatible with FAME frequencies.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/tfplot/index.html">tfplot</a>
|
||
- Utilities for simple manipulation and quick plotting of time series
|
||
data.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/tframe/index.html">tframe</a>
|
||
- A kernel of functions for programming time series methods in a way
|
||
that is relatively independently of the representation of time.</li>
|
||
</ul>
|
||
<h3 id="data-sources-1">Data Sources</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/IBrokers/index.html">IBrokers</a>
|
||
- Provides native R access to Interactive Brokers Trader Workstation
|
||
API.</li>
|
||
<li><a href="https://github.com/Rblp/Rblpapi">Rblpapi</a> - An R
|
||
Interface to ‘Bloomberg’ is provided via the ‘Blp API’.</li>
|
||
<li><a href="https://www.quandl.com/tools/r">Quandl</a> - Get Financial
|
||
Data Directly Into R.</li>
|
||
<li><a href="https://github.com/jangorecki/Rbitcoin">Rbitcoin</a> -
|
||
Unified markets API interface (bitstamp, kraken, btce, bitmarket).</li>
|
||
<li><a href="https://github.com/msperlin/GetTDData">GetTDData</a> -
|
||
Downloads and aggregates data for Brazilian government issued bonds
|
||
directly from the website of Tesouro Direto.</li>
|
||
<li><a href="https://github.com/msperlin/GetHFData">GetHFData</a> -
|
||
Downloads and aggregates high frequency trading data for Brazilian
|
||
instruments directly from Bovespa ftp site.</li>
|
||
<li><a href="https://dashboard.nbshare.io/apps/reddit/api/">Reddit
|
||
WallstreetBets API</a> - Provides daily top 50 stocks from reddit
|
||
(subreddit) Wallstreetbets and their sentiments via the API.</li>
|
||
<li><a href="https://github.com/eddelbuettel/td">td</a> - Interfaces the
|
||
‘twelvedata’ API for stocks and (digital and standard) currencies.</li>
|
||
<li><a href="https://github.com/wilsonfreitas/rbcb">rbcb</a> - R
|
||
interface to Brazilian Central Bank web services.</li>
|
||
<li><a href="https://github.com/ropensci/rb3">rb3</a> - A bunch of
|
||
downloaders and parsers for data delivered from B3.</li>
|
||
<li><a href="https://github.com/matthiasgomolka/simfinapi">simfinapi</a>
|
||
- Makes ‘SimFin’ data (<a href="https://simfin.com/"
|
||
class="uri">https://simfin.com/</a>) easily accessible in R.</li>
|
||
<li><a
|
||
href="https://github.com/tidy-finance/r-tidyfinance">tidyfinance</a> -
|
||
Tidy Finance helper functions to download financial data and process the
|
||
raw data into a structured Format (tidy data), including date
|
||
conversion, scaling factor values, and filtering by the specified
|
||
date.</li>
|
||
</ul>
|
||
<h3 id="financial-instruments-and-pricing-1">Financial Instruments and
|
||
Pricing</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/eddelbuettel/rquantlib">RQuantLib</a> -
|
||
RQuantLib connects GNU R with QuantLib.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/quantmod/index.html">quantmod</a>
|
||
- Quantitative Financial Modelling Framework.</li>
|
||
<li><a href="https://www.rmetrics.org">Rmetrics</a> - The premier open
|
||
source software solution for teaching and training quantitative finance.
|
||
<ul>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fAsianOptions/index.html">fAsianOptions</a>
|
||
- EBM and Asian Option Valuation.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fAssets/index.html">fAssets</a>
|
||
- Analysing and Modelling Financial Assets.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fBasics/index.html">fBasics</a>
|
||
- Markets and Basic Statistics.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fBonds/index.html">fBonds</a>
|
||
- Bonds and Interest Rate Models.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fExoticOptions/index.html">fExoticOptions</a>
|
||
- Exotic Option Valuation.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fOptions/index.html">fOptions</a>
|
||
- Pricing and Evaluating Basic Options.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fPortfolio/index.html">fPortfolio</a>
|
||
- Portfolio Selection and Optimization.</li>
|
||
</ul></li>
|
||
<li><a href="https://github.com/dgerlanc/portfolio">portfolio</a> -
|
||
Analysing equity portfolios.</li>
|
||
<li><a
|
||
href="https://github.com/dppalomar/sparseIndexTracking">sparseIndexTracking</a>
|
||
- Portfolio design to track an index.</li>
|
||
<li><a
|
||
href="https://github.com/dppalomar/covFactorModel">covFactorModel</a> -
|
||
Covariance matrix estimation via factor models.</li>
|
||
<li><a
|
||
href="https://github.com/dppalomar/riskParityPortfolio">riskParityPortfolio</a>
|
||
- Blazingly fast design of risk parity portfolios.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/sde/index.html">sde</a> -
|
||
Simulation and Inference for Stochastic Differential Equations.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/YieldCurve/index.html">YieldCurve</a>
|
||
- Modelling and estimation of the yield curve.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/SmithWilsonYieldCurve/index.html">SmithWilsonYieldCurve</a>
|
||
- Constructs a yield curve by the Smith-Wilson method from a table of
|
||
LIBOR and SWAP rates.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/ycinterextra/index.html">ycinterextra</a>
|
||
- Yield curve or zero-coupon prices interpolation and
|
||
extrapolation.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/AmericanCallOpt/index.html">AmericanCallOpt</a>
|
||
- This package includes pricing function for selected American call
|
||
options with underlying assets that generate payouts.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/VarSwapPrice/index.html">VarSwapPrice</a>
|
||
- Pricing a variance swap on an equity index.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/RND/index.html">RND</a> -
|
||
Risk Neutral Density Extraction Package.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/LSMonteCarlo/index.html">LSMonteCarlo</a>
|
||
- American options pricing with Least Squares Monte Carlo method.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/OptHedging/index.html">OptHedging</a>
|
||
- Estimation of value and hedging strategy of call and put options.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/tvm/index.html">tvm</a> -
|
||
Time Value of Money Functions.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/OptionPricing/index.html">OptionPricing</a>
|
||
- Option Pricing with Efficient Simulation Algorithms.</li>
|
||
<li><a href="https://github.com/blenezet/credule">credule</a> - Credit
|
||
Default Swap Functions.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/derivmkts/index.html">derivmkts</a>
|
||
- Functions and R Code to Accompany Derivatives Markets.</li>
|
||
<li><a href="https://github.com/felixfan/FinCal">FinCal</a> - Package
|
||
for time value of money calculation, time series analysis and
|
||
computational finance.</li>
|
||
<li><a href="https://github.com/artyyouth/r-quant">r-quant</a> - R code
|
||
for quantitative analysis in finance.</li>
|
||
<li><a
|
||
href="https://github.com/taylorizing/options.studies">options.studies</a>
|
||
- options trading studies functions for use with options.data package
|
||
and shiny.</li>
|
||
<li><a
|
||
href="https://github.com/braverock/PortfolioAnalytics">PortfolioAnalytics</a>
|
||
- Portfolio Analysis, Including Numerical Methods for Optimizationof
|
||
Portfolios.</li>
|
||
<li><a href="https://github.com/imanuelcostigan/fmbasics">fmbasics</a> -
|
||
Financial Market Building Blocks.</li>
|
||
<li><a
|
||
href="https://github.com/wilsonfreitas/R-fixedincome">R-fixedincome</a>
|
||
- Fixed income tools for R.</li>
|
||
</ul>
|
||
<h3 id="trading">Trading</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/backtest/index.html">backtest</a>
|
||
- Exploring Portfolio-Based Conjectures About Financial
|
||
Instruments.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/pa/index.html">pa</a> -
|
||
Performance Attribution for Equity Portfolios.</li>
|
||
<li><a href="https://github.com/joshuaulrich/TTR">TTR</a> - Technical
|
||
Trading Rules.</li>
|
||
<li><a
|
||
href="https://quanttools.bitbucket.io/_site/index.html">QuantTools</a> -
|
||
Enhanced Quantitative Trading Modelling.</li>
|
||
<li><a href="https://github.com/braverock/blotter">blotter</a> -
|
||
Transaction infrastructure for defining instruments, transactions,
|
||
portfolios and accounts for trading systems and simulation. Provides
|
||
portfolio support for multi-asset class and multi-currency portfolios.
|
||
Actively maintained and developed.</li>
|
||
</ul>
|
||
<h3 id="backtesting">Backtesting</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/braverock/quantstrat">quantstrat</a> -
|
||
Transaction-oriented infrastructure for constructing trading systems and
|
||
simulation. Provides support for multi-asset class and multi-currency
|
||
portfolios for backtesting and other financial research.</li>
|
||
</ul>
|
||
<h3 id="risk-analysis-1">Risk Analysis</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/braverock/PerformanceAnalytics">PerformanceAnalytics</a>
|
||
- Econometric tools for performance and risk analysis.</li>
|
||
</ul>
|
||
<h3 id="factor-analysis-1">Factor Analysis</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/braverock/FactorAnalytics">FactorAnalytics</a>
|
||
- The FactorAnalytics package contains fitting and analysis methods for
|
||
the three main types of factor models used in conjunction with portfolio
|
||
construction, optimization and risk management, namely fundamental
|
||
factor models, time series factor models and statistical factor
|
||
models.</li>
|
||
<li><a href="https://github.com/JustinMShea/ExpectedReturns">Expected
|
||
Returns</a> - Solutions for enhancing portfolio diversification and
|
||
replications of seminal papers with R, most of which are discussed in
|
||
one of the best investment references of the recent decade, Expected
|
||
Returns: An Investors Guide to Harvesting Market Rewards by Antti
|
||
Ilmanen.</li>
|
||
</ul>
|
||
<h3 id="time-series-1">Time Series</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/tseries/index.html">tseries</a>
|
||
- Time Series Analysis and Computational Finance.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/fGarch/index.html">fGarch</a>
|
||
- Rmetrics - Autoregressive Conditional Heteroskedastic Modelling.</li>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/timeSeries/index.html">timeSeries</a>
|
||
- Rmetrics - Financial Time Series Objects.</li>
|
||
<li><a href="https://github.com/alexiosg/rugarch">rugarch</a> -
|
||
Univariate GARCH Models.</li>
|
||
<li><a href="https://github.com/alexiosg/rmgarch">rmgarch</a> -
|
||
Multivariate GARCH Models.</li>
|
||
<li><a href="https://github.com/edgararuiz/tidypredict">tidypredict</a>
|
||
- Run predictions inside the database <a
|
||
href="https://tidypredict.netlify.com/"
|
||
class="uri">https://tidypredict.netlify.com/</a>.</li>
|
||
<li><a
|
||
href="https://github.com/business-science/tidyquant">tidyquant</a> -
|
||
Bringing financial analysis to the tidyverse.</li>
|
||
<li><a href="https://github.com/business-science/timetk">timetk</a> - A
|
||
toolkit for working with time series in R.</li>
|
||
<li><a
|
||
href="https://github.com/business-science/tibbletime">tibbletime</a> -
|
||
Built on top of the tidyverse, tibbletime is an extension that allows
|
||
for the creation of time aware tibbles through the setting of a time
|
||
index.</li>
|
||
<li><a
|
||
href="https://github.com/matrix-profile-foundation/matrixprofile">matrixprofile</a>
|
||
- Time series data mining library built on top of the novel Matrix
|
||
Profile data structure and algorithms.</li>
|
||
<li><a
|
||
href="https://github.com/AlbertoAlmuinha/garchmodels">garchmodels</a> -
|
||
A parsnip backend for GARCH models.</li>
|
||
</ul>
|
||
<h3 id="calendars-1">Calendars</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://cran.r-project.org/web/packages/timeDate/index.html">timeDate</a>
|
||
- Chronological and Calendar Objects</li>
|
||
<li><a href="https://github.com/wilsonfreitas/R-bizdays">bizdays</a> -
|
||
Business days calculations and utilities</li>
|
||
</ul>
|
||
<h2 id="matlab">Matlab</h2>
|
||
<h3 id="frameworks">FrameWorks</h3>
|
||
<ul>
|
||
<li><a href="https://github.com/yutiansut/quantaxis">QUANTAXIS</a> -
|
||
Integrated Quantitative Toolbox with Matlab.</li>
|
||
<li><a
|
||
href="https://github.com/jkirkby3/PROJ_Option_Pricing_Matlab">PROJ_Option_Pricing_Matlab</a>
|
||
- Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European,
|
||
American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward
|
||
Starting, Step, Fader</li>
|
||
</ul>
|
||
<h2 id="julia">Julia</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/oliviermilla/Lucky.jl">Lucky.jl</a> -
|
||
Modular, asynchronous trading engine in pure Julia.</li>
|
||
<li><a href="https://github.com/pazzo83/QuantLib.jl">QuantLib.jl</a> -
|
||
Quantlib implementation in pure Julia.</li>
|
||
<li><a href="https://github.com/aviks/Ito.jl">Ito.jl</a> - A Julia
|
||
package for quantitative finance.</li>
|
||
<li><a href="https://github.com/femtotrader/TALib.jl">TALib.jl</a> - A
|
||
Julia wrapper for TA-Lib.</li>
|
||
<li><a href="https://github.com/femtotrader/IncTA.jl">IncTA.jl</a> -
|
||
Julia Incremental Technical Analysis Indicators</li>
|
||
<li><a
|
||
href="https://github.com/JuliaComputing/Miletus.jl">Miletus.jl</a> - A
|
||
financial contract definition, modeling language, and valuation
|
||
framework.</li>
|
||
<li><a href="https://github.com/dysonance/Temporal.jl">Temporal.jl</a> -
|
||
Flexible and efficient time series class & methods.</li>
|
||
<li><a
|
||
href="https://github.com/dysonance/Indicators.jl">Indicators.jl</a> -
|
||
Financial market technical analysis & indicators on top of
|
||
Temporal.</li>
|
||
<li><a
|
||
href="https://github.com/dysonance/Strategems.jl">Strategems.jl</a> -
|
||
Quantitative systematic trading strategy development and
|
||
backtesting.</li>
|
||
<li><a
|
||
href="https://github.com/JuliaStats/TimeSeries.jl">TimeSeries.jl</a> -
|
||
Time series toolkit for Julia.</li>
|
||
<li><a
|
||
href="https://github.com/JuliaQuant/MarketTechnicals.jl">MarketTechnicals.jl</a>
|
||
- Technical analysis of financial time series on top of TimeSeries.</li>
|
||
<li><a
|
||
href="https://github.com/JuliaQuant/MarketData.jl">MarketData.jl</a> -
|
||
Time series market data.</li>
|
||
<li><a
|
||
href="https://github.com/femtotrader/TimeFrames.jl">TimeFrames.jl</a> -
|
||
A Julia library that defines TimeFrame (essentially for resampling
|
||
TimeSeries).</li>
|
||
<li><a
|
||
href="https://github.com/JuliaData/DataFrames.jl">DataFrames.jl</a> -
|
||
In-memory tabular data in Julia</li>
|
||
<li><a href="https://github.com/xKDR/TSFrames.jl">TSFrames.jl</a> -
|
||
Handle timeseries data on top of the powerful and mature
|
||
DataFrames.jl</li>
|
||
</ul>
|
||
<h2 id="java">Java</h2>
|
||
<ul>
|
||
<li><a href="http://strata.opengamma.io/">Strata</a> - Modern
|
||
open-source analytics and market risk library designed and written in
|
||
Java.</li>
|
||
<li><a href="https://github.com/frgomes/jquantlib">JQuantLib</a> -
|
||
JQuantLib is a free, open-source, comprehensive framework for
|
||
quantitative finance, written in 100% Java.</li>
|
||
<li><a href="http://finmath.net">finmath.net</a> - Java library with
|
||
algorithms and methodologies related to mathematical finance.</li>
|
||
<li><a
|
||
href="https://github.com/lsgro/quantcomponents">quantcomponents</a> -
|
||
Free Java components for Quantitative Finance and Algorithmic
|
||
Trading.</li>
|
||
<li><a href="https://lakshmidrip.github.io/DRIP">DRIP</a> - Fixed
|
||
Income, Asset Allocation, Transaction Cost Analysis, XVA Metrics
|
||
Libraries.</li>
|
||
<li><a href="https://github.com/ta4j/ta4j">ta4j</a> - A Java library for
|
||
technical analysis.</li>
|
||
</ul>
|
||
<h2 id="javascript">JavaScript</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/ebradyjobory/finance.js">finance.js</a>
|
||
- A JavaScript library for common financial calculations.</li>
|
||
<li><a
|
||
href="https://github.com/lequant40/portfolio_allocation_js">portfolio-allocation</a>
|
||
- PortfolioAllocation is a JavaScript library designed to help
|
||
constructing financial portfolios made of several assets: bonds,
|
||
commodities, cryptocurrencies, currencies, exchange traded funds (ETFs),
|
||
mutual funds, stocks…</li>
|
||
<li><a href="https://github.com/ghostfolio/ghostfolio">Ghostfolio</a> -
|
||
Wealth management software to keep track of financial assets like
|
||
stocks, ETFs or cryptocurrencies and make solid, data-driven investment
|
||
decisions.</li>
|
||
<li><a href="https://github.com/cinar/indicatorts">IndicatorTS</a> -
|
||
Indicator is a TypeScript module providing various stock technical
|
||
analysis indicators, strategies, and a backtest framework for
|
||
trading.</li>
|
||
<li><a
|
||
href="https://github.com/focus1691/chart-patterns">chart-patterns</a> -
|
||
Technical analysis library for Market Profile, Volume Profile, Stacked
|
||
Imbalances and High Volume Node indicators.</li>
|
||
<li><a href="https://github.com/focus1691/orderflow">orderflow</a> -
|
||
Orderflow trade aggregator for building Footprint Candles from exchange
|
||
websocket data.</li>
|
||
<li><a href="https://github.com/ccxt/ccxt">ccxt</a> - A JavaScript /
|
||
Python / PHP cryptocurrency trading API with support for more than 100
|
||
bitcoin/altcoin exchanges.</li>
|
||
<li><a href="https://github.com/CompendiumFi/PENDAX-SDK">PENDAX</a> -
|
||
Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX,
|
||
Bybit, & More.</li>
|
||
</ul>
|
||
<h3 id="data-visualization">Data Visualization</h3>
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/yutiansut/QUANTAXIS_Webkit">QUANTAXIS_Webkit</a>
|
||
- An awesome visualization center based on quantaxis.</li>
|
||
</ul>
|
||
<h2 id="haskell">Haskell</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/boundedvariation/quantfin">quantfin</a>
|
||
- quant finance in pure haskell.</li>
|
||
<li><a href="https://github.com/MarcusRainbow/Haxcel">Haxcel</a> - Excel
|
||
Addin for Haskell.</li>
|
||
<li><a href="https://github.com/MarcusRainbow/Ffinar">Ffinar</a> - A
|
||
financial maths library in Haskell.</li>
|
||
</ul>
|
||
<h2 id="scala">Scala</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/choucrifahed/quantscale">QuantScale</a>
|
||
- Scala Quantitative Finance Library.</li>
|
||
<li><a href="https://github.com/frankcash/Scala-Quant">Scala Quant</a> -
|
||
Scala library for working with stock data from IFTTT recipes or Google
|
||
Finance.</li>
|
||
</ul>
|
||
<h2 id="ruby">Ruby</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/unageanu/jiji2">Jiji</a> - Open Source
|
||
Forex algorithmic trading framework using OANDA REST API.</li>
|
||
</ul>
|
||
<h2 id="elixirerlang">Elixir/Erlang</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/fremantle-capital/tai">Tai</a> - Open
|
||
Source composable, real time, market data and trade execution
|
||
toolkit.</li>
|
||
<li><a
|
||
href="https://github.com/fremantle-industries/workbench">Workbench</a> -
|
||
From Idea to Execution - Manage your trading operation across a globally
|
||
distributed cluster</li>
|
||
<li><a href="https://github.com/fremantle-industries/prop">Prop</a> - An
|
||
open and opinionated trading platform using productive & familiar
|
||
open source libraries and tools for strategy research, execution and
|
||
operation.</li>
|
||
</ul>
|
||
<h2 id="golang">Golang</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/stellar/kelp">Kelp</a> - Kelp is an
|
||
open-source Golang algorithmic cryptocurrency trading bot that runs on
|
||
centralized exchanges and Stellar DEX (command-line usage and desktop
|
||
GUI).</li>
|
||
<li><a href="https://github.com/alpacahq/marketstore">marketstore</a> -
|
||
DataFrame Server for Financial Timeseries Data.</li>
|
||
<li><a href="https://github.com/cinar/indicator">IndicatorGo</a> -
|
||
IndicatorGo is a Golang module providing various stock technical
|
||
analysis indicators, strategies, and a backtest framework for
|
||
trading.</li>
|
||
</ul>
|
||
<h2 id="cpp">CPP</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/lballabio/QuantLib">QuantLib</a> - The
|
||
QuantLib project is aimed at providing a comprehensive software
|
||
framework for quantitative finance.</li>
|
||
<li><a
|
||
href="https://github.com/auto-differentiation/QuantLib-Risks-Cpp">QuantLibRisks</a>
|
||
- Fast risks with QuantLib in C++</li>
|
||
<li><a href="https://github.com/auto-differentiation/xad">XAD</a> -
|
||
Automatic Differentation (AAD) Library</li>
|
||
<li><a href="https://github.com/rburkholder/trade-frame">TradeFrame</a>
|
||
- C++ 17 based framework/library (with sample applications) for testing
|
||
options based automated trading ideas using DTN IQ real time data feed
|
||
and Interactive Brokers (TWS API) for trade execution. Comes with
|
||
built-in <a
|
||
href="https://github.com/rburkholder/trade-frame/tree/master/lib/TFOptions">Option
|
||
Greeks/IV</a> calculation library.</li>
|
||
<li><a href="https://github.com/fasiondog/hikyuu">Hikyuu</a> - A base on
|
||
Python/C++ open source high-performance quant framework for faster
|
||
analysis and backtesting, contains the complete trading system
|
||
components for reuse and combination. You can use python or c++
|
||
freely.</li>
|
||
</ul>
|
||
<h2 id="frameworks-1">Frameworks</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/lballabio/QuantLib">QuantLib</a> - The
|
||
QuantLib project is aimed at providing a comprehensive software
|
||
framework for quantitative finance.
|
||
<ul>
|
||
<li>QuantLibRisks - Fast risks with QuantLib in <a
|
||
href="https://pypi.org/project/QuantLib-Risks/">Python</a> and <a
|
||
href="https://github.com/auto-differentiation/QuantLib-Risks-Cpp">C++</a></li>
|
||
<li>XAD - Automatic Differentiation (AAD) Library in <a
|
||
href="https://pypi.org/project/xad/">Python</a> and <a
|
||
href="https://github.com/auto-differentiation/xad/">C++</a></li>
|
||
<li><a href="https://github.com/frgomes/jquantlib">JQuantLib</a> - Java
|
||
port.</li>
|
||
<li><a href="https://github.com/eddelbuettel/rquantlib">RQuantLib</a> -
|
||
R port.</li>
|
||
<li><a href="https://www.quantlib.org/quantlibaddin/">QuantLibAddin</a>
|
||
- Excel support.</li>
|
||
<li><a href="https://www.quantlib.org/quantlibxl/">QuantLibXL</a> -
|
||
Excel support.</li>
|
||
<li><a href="https://github.com/amaggiulli/qlnet">QLNet</a> - .Net
|
||
port.</li>
|
||
<li><a href="https://github.com/enthought/pyql">PyQL</a> - Python
|
||
port.</li>
|
||
<li><a href="https://github.com/pazzo83/QuantLib.jl">QuantLib.jl</a> -
|
||
Julia port.</li>
|
||
<li><a
|
||
href="https://quantlib-python-docs.readthedocs.io/">QuantLib-Python
|
||
Documentation</a> - Documentation for the Python bindings for the
|
||
QuantLib library</li>
|
||
</ul></li>
|
||
<li><a href="https://ta-lib.org">TA-Lib</a> - perform technical analysis
|
||
of financial market data.
|
||
<ul>
|
||
<li><a
|
||
href="https://github.com/TA-Lib/ta-lib-python">ta-lib-python</a></li>
|
||
<li><a href="https://github.com/TA-Lib/ta-lib">ta-lib</a></li>
|
||
</ul></li>
|
||
<li><a href="https://portfoliooptimizer.io/">Portfolio Optimizer</a> -
|
||
Portfolio Optimizer is a Web API for portfolio analysis and
|
||
optimization.</li>
|
||
<li>XAD: Automatic Differentation (AAD) Library for <a
|
||
href="https://pypi.org/project/xad/">Python</a> and <a
|
||
href="https://github.com/auto-differentiation/xad">C++</a></li>
|
||
</ul>
|
||
<h2 id="csharp">CSharp</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/QuantConnect/Lean">QuantConnect</a> -
|
||
Lean Engine is an open-source fully managed C# algorithmic trading
|
||
engine built for desktop and cloud usage.</li>
|
||
<li><a href="https://github.com/StockSharp/StockSharp">StockSharp</a> -
|
||
Algorithmic trading and quantitative trading open source platform to
|
||
develop trading robots (stock markets, forex, crypto, bitcoins, and
|
||
options).</li>
|
||
<li><a
|
||
href="https://github.com/NVentimiglia/TDAmeritrade.DotNetCore">TDAmeritrade.DotNetCore</a>
|
||
- Free, open-source .NET Client for the TD Ameritrade Trading Platform.
|
||
Helps developers integrate TD Ameritrade API into custom trading
|
||
solutions.</li>
|
||
</ul>
|
||
<h2 id="rust">Rust</h2>
|
||
<ul>
|
||
<li><a href="https://github.com/MarcusRainbow/QuantMath">QuantMath</a> -
|
||
Financial maths library for risk-neutral pricing and risk</li>
|
||
<li><a href="https://github.com/barter-rs/barter-rs">Barter</a> -
|
||
Open-source Rust framework for building event-driven live-trading &
|
||
backtesting systems</li>
|
||
<li><a href="https://github.com/MathisWellmann/lfest-rs">LFEST</a> -
|
||
Simulated perpetual futures exchange to trade your strategy
|
||
against.</li>
|
||
<li><a
|
||
href="https://github.com/MathisWellmann/trade_aggregation-rs">TradeAggregation</a>
|
||
- Aggregate trades into user-defined candles using information driven
|
||
rules.</li>
|
||
<li><a
|
||
href="https://github.com/MathisWellmann/sliding_features-rs">SlidingFeatures</a>
|
||
- Chainable tree-like sliding windows for signal processing and
|
||
technical analysis.</li>
|
||
<li><a href="https://github.com/avhz/RustQuant">RustQuant</a> -
|
||
Quantitative finance library written in Rust.</li>
|
||
<li><a href="https://github.com/Nnamdi-sys/finalytics">finalytics</a> -
|
||
A rust library for financial data analysis.</li>
|
||
</ul>
|
||
<h2 id="reproducing-works-training-books">Reproducing Works, Training
|
||
& Books</h2>
|
||
<ul>
|
||
<li><a
|
||
href="https://auto-differentiation.github.io/">Auto-Differentiation
|
||
Website</a> - Background and resources on Automatic Differentiation (AD)
|
||
/ Adjoint Algorithmic Differentitation (AAD).</li>
|
||
<li><a href="https://github.com/MarcosCarreira/DermanPapers">Derman
|
||
Papers</a> - Notebooks that replicate original quantitative finance
|
||
papers from Emanuel Derman.</li>
|
||
<li><a href="https://www.ml-quant.com/">ML-Quant</a> - Top Quant
|
||
resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos,
|
||
and Blogs.</li>
|
||
<li><a
|
||
href="https://github.com/jasonstrimpel/volatility-trading">volatility-trading</a>
|
||
- A complete set of volatility estimators based on Euan Sinclair’s
|
||
Volatility Trading.</li>
|
||
<li><a href="https://github.com/paulperry/quant">quant</a> -
|
||
Quantitative Finance and Algorithmic Trading exhaust; mostly ipython
|
||
notebooks based on Quantopian, Zipline, or Pandas.</li>
|
||
<li><a href="https://github.com/rsvp/fecon235">fecon235</a> - Open
|
||
source project for software tools in financial economics. Many jupyter
|
||
notebook to verify theoretical ideas and practical methods
|
||
interactively.</li>
|
||
<li><a
|
||
href="https://github.com/LongOnly/Quantitative-Notebooks">Quantitative-Notebooks</a>
|
||
- Educational notebooks on quantitative finance, algorithmic trading,
|
||
financial modelling and investment strategy</li>
|
||
<li><a href="https://quantecon.org/">QuantEcon</a> - Lecture series on
|
||
economics, finance, econometrics and data science; QuantEcon.py,
|
||
QuantEcon.jl, notebooks</li>
|
||
<li><a href="https://github.com/Finance-Hub/FinanceHub">FinanceHub</a> -
|
||
Resources for Quantitative Finance</li>
|
||
<li><a
|
||
href="https://github.com/dedwards25/Python_Option_Pricing">Python_Option_Pricing</a>
|
||
- An library to price financial options written in Python. Includes:
|
||
Black Scholes, Black 76, Implied Volatility, American, European, Asian,
|
||
Spread Options.</li>
|
||
<li><a
|
||
href="https://github.com/jpmorganchase/python-training">python-training</a>
|
||
- J.P. Morgan’s Python training for business analysts and traders.</li>
|
||
<li><a
|
||
href="https://github.com/LastAncientOne/Stock_Analysis_For_Quant">Stock_Analysis_For_Quant</a>
|
||
- Different Types of Stock Analysis in Excel, Matlab, Power BI, Python,
|
||
R, and Tableau.</li>
|
||
<li><a
|
||
href="https://github.com/chrisconlan/algorithmic-trading-with-python">algorithmic-trading-with-python</a>
|
||
- Source code for Algorithmic Trading with Python (2020) by Chris
|
||
Conlan.</li>
|
||
<li><a
|
||
href="https://github.com/cerlymarco/MEDIUM_NoteBook">MEDIUM_NoteBook</a>
|
||
- Repository containing notebooks of <a
|
||
href="https://github.com/cerlymarco">cerlymarco</a>’s posts on
|
||
Medium.</li>
|
||
<li><a
|
||
href="https://github.com/PythonCharmers/QuantFinance">QuantFinance</a> -
|
||
Training materials in quantitative finance.</li>
|
||
<li><a
|
||
href="https://github.com/mgroncki/IPythonScripts">IPythonScripts</a> -
|
||
Tutorials about Quantitative Finance in Python and QuantLib: Pricing,
|
||
xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep
|
||
Learning.</li>
|
||
<li><a
|
||
href="https://github.com/LechGrzelak/Computational-Finance-Course">Computational-Finance-Course</a>
|
||
- Materials for the course of Computational Finance.</li>
|
||
<li><a
|
||
href="https://github.com/emoen/Machine-Learning-for-Asset-Managers">Machine-Learning-for-Asset-Managers</a>
|
||
- Implementation of code snippets, exercises and application to live
|
||
data from Machine Learning for Asset Managers (Elements in Quantitative
|
||
Finance) written by Prof. Marcos López de Prado.</li>
|
||
<li><a
|
||
href="https://github.com/PacktPublishing/Python-for-Finance-Cookbook">Python-for-Finance-Cookbook</a>
|
||
- Python for Finance Cookbook, published by Packt.</li>
|
||
<li><a
|
||
href="https://github.com/ysaporito/modelos_vol_derivativos">modelos_vol_derivativos</a>
|
||
- “Modelos de Volatilidade para Derivativos” book’s Jupyter
|
||
notebooks</li>
|
||
<li><a href="https://github.com/enricoschumann/NMOF">NMOF</a> -
|
||
Functions, examples and data from the first and the second edition of
|
||
“Numerical Methods and Optimization in Finance” by M. Gilli, D. Maringer
|
||
and E. Schumann (2019, ISBN:978-0128150658).</li>
|
||
<li><a href="https://github.com/yhilpisch/py4fi2nd">py4fi2nd</a> -
|
||
Jupyter Notebooks and code for Python for Finance (2nd ed., O’Reilly) by
|
||
Yves Hilpisch.</li>
|
||
<li><a href="https://github.com/yhilpisch/aiif">aiif</a> - Jupyter
|
||
Notebooks and code for the book Artificial Intelligence in Finance
|
||
(O’Reilly) by Yves Hilpisch.</li>
|
||
<li><a href="https://github.com/yhilpisch/py4at">py4at</a> - Jupyter
|
||
Notebooks and code for the book Python for Algorithmic Trading
|
||
(O’Reilly) by Yves Hilpisch.</li>
|
||
<li><a href="https://github.com/yhilpisch/dawp">dawp</a> - Jupyter
|
||
Notebooks and code for Derivatives Analytics with Python (Wiley Finance)
|
||
by Yves Hilpisch.</li>
|
||
<li><a href="https://github.com/yhilpisch/dx">dx</a> - DX Analytics |
|
||
Financial and Derivatives Analytics with Python.</li>
|
||
<li><a
|
||
href="https://github.com/LechGrzelak/QuantFinanceBook">QuantFinanceBook</a>
|
||
- Quantitative Finance book.</li>
|
||
<li><a
|
||
href="https://github.com/ryanmccrickerd/rough_bergomi">rough_bergomi</a>
|
||
- A Python implementation of the rough Bergomi model.</li>
|
||
<li><a href="https://github.com/ryanmccrickerd/frh-fx">frh-fx</a> - A
|
||
python implementation of the fast-reversion Heston model of Mechkov for
|
||
FX purposes.</li>
|
||
<li><a href="https://github.com/euclidjda/value-investing-studies">Value
|
||
Investing Studies</a> - A collection of data analysis studies that
|
||
examine the performance and characteristics of value investing over long
|
||
periods of time.</li>
|
||
<li><a
|
||
href="https://github.com/firmai/machine-learning-asset-management">Machine
|
||
Learning Asset Management</a> - Machine Learning in Asset Management (by
|
||
<span class="citation" data-cites="firmai">@firmai</span>).</li>
|
||
<li><a
|
||
href="https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock">Deep
|
||
Learning Machine Learning Stock</a> - Deep Learning and Machine Learning
|
||
stocks represent a promising long-term or short-term opportunity for
|
||
investors and traders.</li>
|
||
<li><a
|
||
href="https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering">Technical
|
||
Analysis and Feature Engineering</a> - Feature Engineering and Feature
|
||
Importance of Machine Learning in Financial Market.</li>
|
||
<li><a
|
||
href="https://github.com/differential-machine-learning/notebooks">Differential
|
||
Machine Learning and Axes that matter by Brian Huge and Antoine
|
||
Savine</a> - Implement, demonstrate, reproduce and extend the results of
|
||
the Risk articles ‘Differential Machine Learning’ (2020) and ‘PCA with a
|
||
Difference’ (2021) by Huge and Savine, and cover implementation details
|
||
left out from the papers.</li>
|
||
<li><a
|
||
href="https://github.com/robcarver17/systematictradingexamples">systematictradingexamples</a>
|
||
- Examples of code related to book <a
|
||
href="www.systematictrading.org">Systematic Trading</a> and <a
|
||
href="http://qoppac.blogspot.com">blog</a></li>
|
||
<li><a
|
||
href="https://github.com/robcarver17/pysystemtrade_examples">pysystemtrade_examples</a>
|
||
- Examples using pysystemtrade for Robert Carver’s <a
|
||
href="http://qoppac.blogspot.com">blog</a>.</li>
|
||
<li><a
|
||
href="https://github.com/mfrdixon/ML_Finance_Codes">ML_Finance_Codes</a>
|
||
- Machine Learning in Finance: From Theory to Practice Book</li>
|
||
<li><a
|
||
href="https://github.com/packtpublishing/hands-on-machine-learning-for-algorithmic-trading">Hands-On
|
||
Machine Learning for Algorithmic Trading</a> - Hands-On Machine Learning
|
||
for Algorithmic Trading, published by Packt</li>
|
||
<li><a
|
||
href="https://github.com/financialnoob/misc">financialnoob-misc</a> -
|
||
Codes from <span class="citation"
|
||
data-cites="financialnoob">@financialnoob</span>’s posts</li>
|
||
<li><a href="https://github.com/deltaray-io/strategy-library">MesoSim
|
||
Options Trading Strategy Library</a> - Free and public Options Trading
|
||
strategy library for MesoSim.</li>
|
||
<li><a
|
||
href="https://github.com/lingyixu/Quant-Finance-With-Python-Code">Quant-Finance-With-Python-Code</a>
|
||
- Repo for code examples in Quantitative Finance with Python by Chris
|
||
Kelliher</li>
|
||
<li><a
|
||
href="https://github.com/JoaoJungblut/QuantFinanceTraining">QuantFinanceTraining</a>
|
||
- This repository contains codes that were executed during my training
|
||
in the CQF (Certificate in Quantitative Finance). The codes are
|
||
organized by class, facilitating navigation and reference.</li>
|
||
<li><a
|
||
href="https://github.com/YannickKae/Statistical-Learning-based-Portfolio-Optimization">Statistical-Learning-based-Portfolio-Optimization</a>
|
||
- This R Shiny App utilizes the Hierarchical Equal Risk Contribution
|
||
(HERC) approach, a modern portfolio optimization method developed by
|
||
Raffinot (2018).</li>
|
||
<li><a href="https://github.com/attack68/book_irds3">book_irds3</a> -
|
||
Code repository for Pricing and Trading Interest Rate Derivatives.</li>
|
||
<li><a
|
||
href="https://github.com/RichardS0268/Autoencoder-Asset-Pricing-Models">Autoencoder-Asset-Pricing-Models</a>
|
||
- Reimplementation of Autoencoder Asset Pricing Models (<a
|
||
href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3335536">GKX,
|
||
2019</a>).</li>
|
||
<li><a href="https://github.com/shashankvemuri/Finance">Finance</a> -
|
||
150+ quantitative finance Python programs to help you gather,
|
||
manipulate, and analyze stock market data.</li>
|
||
<li><a
|
||
href="https://github.com/ram-ki/101_formulaic_alphas">101_formulaic_alphas</a>
|
||
- Implementation of <a
|
||
href="https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf">101
|
||
formulaic alphas</a> using qstrader.</li>
|
||
<li><a href="https://www.tidy-finance.org/">Tidy Finance</a> - An
|
||
opinionated approach to empirical research in financial economics - a
|
||
fully transparent, open-source code base in multiple programming
|
||
languages (Python and R) to enable the reproducible implementation of
|
||
financial research projects for students and practitioners.</li>
|
||
<li><a
|
||
href="https://github.com/jgatheral/RoughVolatilityWorkshop">RoughVolatilityWorkshop</a>
|
||
- 2024 QuantMind’s Rough Volatility Workshop lectures.</li>
|
||
<li><a href="https://github.com/boyboi86/AFML">AFML</a> - All the
|
||
answers for exercises from Advances in Financial Machine Learning by Dr
|
||
Marco Lopez de Parodo.</li>
|
||
</ul>
|
||
<p><a href="https://github.com/wilsonfreitas/awesome-quant">quant.md
|
||
Github</a></p>
|