diff --git a/.github/workflows/render-README.yaml b/.github/workflows/render-README.yaml new file mode 100644 index 0000000..5ad9d57 --- /dev/null +++ b/.github/workflows/render-README.yaml @@ -0,0 +1,48 @@ +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + schedule: + # * is a special character in YAML so you have to quote this string + # Trigger once a week, on a Sunday (0) + - cron: "0 0 * * 0" + +name: render-README + +jobs: + render-README: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + steps: + - uses: actions/checkout@v3 + + - uses: r-lib/actions/setup-pandoc@v2 + with: + pandoc-version: "3.1.3" + + - uses: quarto-dev/quarto-actions/setup@v2 + with: + version: pre-release + - run: | + quarto --version + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + pak-version: devel + extra-packages: | + quarto-dev/quarto-r + + - name: Render README + run: | + options(crayon.enabled = TRUE) + quarto::quarto_render("README.qmd", output_format = "html") + fs::file_copy("README.html", "index.html", overwrite = TRUE) + shell: Rscript {0} + + - uses: stefanzweifel/git-auto-commit-action@v4 diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..e4db06b --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,128 @@ +# Contributor Covenant Code of Conduct + +## Our Pledge + +We as members, contributors, and leaders pledge to make participation in our +community a harassment-free experience for everyone, regardless of age, body +size, visible or invisible disability, ethnicity, sex characteristics, gender +identity and expression, level of experience, education, socio-economic status, +nationality, personal appearance, race, religion, or sexual identity +and orientation. + +We pledge to act and interact in ways that contribute to an open, welcoming, +diverse, inclusive, and healthy community. + +## Our Standards + +Examples of behavior that contributes to a positive environment for our +community include: + +* Demonstrating empathy and kindness toward other people +* Being respectful of differing opinions, viewpoints, and experiences +* Giving and gracefully accepting constructive feedback +* Accepting responsibility and apologizing to those affected by our mistakes, + and learning from the experience +* Focusing on what is best not just for us as individuals, but for the + overall community + +Examples of unacceptable behavior include: + +* The use of sexualized language or imagery, and sexual attention or + advances of any kind +* Trolling, insulting or derogatory comments, and personal or political attacks +* Public or private harassment +* Publishing others' private information, such as a physical or email + address, without their explicit permission +* Other conduct which could reasonably be considered inappropriate in a + professional setting + +## Enforcement Responsibilities + +Community leaders are responsible for clarifying and enforcing our standards of +acceptable behavior and will take appropriate and fair corrective action in +response to any behavior that they deem inappropriate, threatening, offensive, +or harmful. + +Community leaders have the right and responsibility to remove, edit, or reject +comments, commits, code, wiki edits, issues, and other contributions that are +not aligned to this Code of Conduct, and will communicate reasons for moderation +decisions when appropriate. + +## Scope + +This Code of Conduct applies within all community spaces, and also applies when +an individual is officially representing the community in public spaces. +Examples of representing our community include using an official e-mail address, +posting via an official social media account, or acting as an appointed +representative at an online or offline event. + +## Enforcement + +Instances of abusive, harassing, or otherwise unacceptable behavior may be +reported to the community leaders responsible for enforcement at +awesom3quant@gmail.com. +All complaints will be reviewed and investigated promptly and fairly. + +All community leaders are obligated to respect the privacy and security of the +reporter of any incident. + +## Enforcement Guidelines + +Community leaders will follow these Community Impact Guidelines in determining +the consequences for any action they deem in violation of this Code of Conduct: + +### 1. Correction + +**Community Impact**: Use of inappropriate language or other behavior deemed +unprofessional or unwelcome in the community. + +**Consequence**: A private, written warning from community leaders, providing +clarity around the nature of the violation and an explanation of why the +behavior was inappropriate. A public apology may be requested. + +### 2. Warning + +**Community Impact**: A violation through a single incident or series +of actions. + +**Consequence**: A warning with consequences for continued behavior. No +interaction with the people involved, including unsolicited interaction with +those enforcing the Code of Conduct, for a specified period of time. This +includes avoiding interactions in community spaces as well as external channels +like social media. Violating these terms may lead to a temporary or +permanent ban. + +### 3. Temporary Ban + +**Community Impact**: A serious violation of community standards, including +sustained inappropriate behavior. + +**Consequence**: A temporary ban from any sort of interaction or public +communication with the community for a specified period of time. No public or +private interaction with the people involved, including unsolicited interaction +with those enforcing the Code of Conduct, is allowed during this period. +Violating these terms may lead to a permanent ban. + +### 4. Permanent Ban + +**Community Impact**: Demonstrating a pattern of violation of community +standards, including sustained inappropriate behavior, harassment of an +individual, or aggression toward or disparagement of classes of individuals. + +**Consequence**: A permanent ban from any sort of public interaction within +the community. + +## Attribution + +This Code of Conduct is adapted from the [Contributor Covenant][homepage], +version 2.0, available at +https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. + +Community Impact Guidelines were inspired by [Mozilla's code of conduct +enforcement ladder](https://github.com/mozilla/diversity). + +[homepage]: https://www.contributor-covenant.org + +For answers to common questions about this code of conduct, see the FAQ at +https://www.contributor-covenant.org/faq. Translations are available at +https://www.contributor-covenant.org/translations. diff --git a/README.md b/README.md index c3e31ba..9c6c247 100644 --- a/README.md +++ b/README.md @@ -34,9 +34,11 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [statistics](https://docs.python.org/3/library/statistics.html) - Builtin Python library for all basic statistical calculations. - [sympy](https://www.sympy.org/) - SymPy is a Python library for symbolic mathematics. - [pymc3](https://docs.pymc.io/) - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano. +- [modelx](https://docs.modelx.io/) - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas. ### Financial Instruments and Pricing +- [OpenBB Terminal](https://github.com/OpenBB-finance/OpenBBTerminal) - Terminal for investment research for everyone. - [PyQL](https://github.com/enthought/pyql) - QuantLib's Python port. - [pyfin](https://github.com/opendoor-labs/pyfin) - Basic options pricing in Python. [ARCHIVED] - [vollib](https://github.com/vollib/vollib) - vollib is a python library for calculating option prices, implied volatility and greeks. @@ -57,6 +59,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [Q-Fin](https://github.com/RomanMichaelPaolucci/Q-Fin) - A Python library for mathematical finance. - [Quantsbin](https://github.com/quantsbin/Quantsbin) - Tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them. - [finoptions](https://github.com/bbcho/finoptions-dev) - Complete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options. +- [pypme](https://github.com/ymyke/pypme) - PME (Public Market Equivalent) calculation. +- [AbsBox](https://github.com/yellowbean/AbsBox) - A Python based library to model cashflow for structured product like Asset-backed securities (ABS) and Mortgage-backed securities (MBS). ### Indicators @@ -68,16 +72,16 @@ A curated list of insanely awesome libraries, packages and resources for Quants ### Trading & Backtesting - [Blankly](https://github.com/Blankly-Finance/Blankly) - Fully integrated backtesting, paper trading, and live deployment. -- [TA-Lib](https://github.com/mrjbq7/ta-lib) - Python wrapper for TA-Lib (http://ta-lib.org/). +- [TA-Lib](https://github.com/mrjbq7/ta-lib) - Python wrapper for TA-Lib (). - [zipline](https://github.com/quantopian/zipline) - Pythonic algorithmic trading library. - [QuantSoftware Toolkit](https://github.com/QuantSoftware/QuantSoftwareToolkit) - Python-based open source software framework designed to support portfolio construction and management. - [quantitative](https://github.com/jeffrey-liang/quantitative) - Quantitative finance, and backtesting library. - [analyzer](https://github.com/llazzaro/analyzer) - Python framework for real-time financial and backtesting trading strategies. - [bt](https://github.com/pmorissette/bt) - Flexible Backtesting for Python. - [backtrader](https://github.com/backtrader/backtrader) - Python Backtesting library for trading strategies. -- [pythalesians](https://github.com/thalesians/pythalesians) - Python library to backtest trading strategies, plot charts, seamlessly download market data, analyse market patterns etc. - [pybacktest](https://github.com/ematvey/pybacktest) - Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier. - [pyalgotrade](https://github.com/gbeced/pyalgotrade) - Python Algorithmic Trading Library. +- [basana](https://github.com/gbeced/basana) - A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies. - [tradingWithPython](https://pypi.org/project/tradingWithPython/) - A collection of functions and classes for Quantitative trading. - [Pandas TA](https://github.com/twopirllc/pandas-ta) - Pandas TA is an easy to use Python 3 Pandas Extension with 115+ Indicators. Easily build Custom Strategies. - [ta](https://github.com/bukosabino/ta) - Technical Analysis Library using Pandas (Python) @@ -126,6 +130,10 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [vectorbt](https://github.com/polakowo/vectorbt) - Find your trading edge, using a powerful toolkit for backtesting, algorithmic trading, and research. - [Lean](https://github.com/QuantConnect/Lean) - Lean Algorithmic Trading Engine by QuantConnect (Python, C#). - [fast-trade](https://github.com/jrmeier/fast-trade) - Low code backtesting library utilizing pandas and technical analysis indicators. +- [pysystemtrade](https://github.com/robcarver17/pysystemtrade) - 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 [blog](https://qoppac.blogspot.com/). +- [pytrendseries](https://github.com/rafa-rod/pytrendseries) - Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater. +- [PyLOB](https://github.com/DrAshBooth/PyLOB) - Fully functioning fast Limit Order Book written in Python. +- [PyBroker](https://github.com/edtechre/pybroker) - Algorithmic Trading with Machine Learning. ### Risk Analysis @@ -212,6 +220,13 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [FinanceDataReader](https://github.com/FinanceData/FinanceDataReader) - Open Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks - [pystlouisfed](https://github.com/TomasKoutek/pystlouisfed) - Python client for Federal Reserve Bank of St. Louis API - FRED, ALFRED, GeoFRED and FRASER. - [python-bcb](https://github.com/wilsonfreitas/python-bcb) - Python interface to Brazilian Central Bank web services. +- [market-prices](https://github.com/maread99/market_prices) - Create meaningful OHLCV datasets from knowledge of [exchange-calendars](https://github.com/gerrymanoim/exchange_calendars) (works out-the-box with data from Yahoo Finance). +- [tardis-python](https://github.com/tardis-dev/tardis-python) - Python interface for Tardis.dev high frequency crypto market data +- [lake-api](https://github.com/crypto-lake/lakeapi) - Python interface for Crypto Lake high frequency crypto market data +- [tessa](https://github.com/ymyke/tessa) - simple, hassle-free access to price information of financial assets (currently based on yfinance and pycoingecko), including search and a symbol class. +- [pandaSDMX](https://github.com/dr-leo/pandaSDMX) - 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. +- [cif](https://github.com/LenkaV/CIF) - Python package that include few composite indicators, which summarize multidimensional relationships between individual economic indicators. +- [finagg](https://github.com/theOGognf/finagg) - 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. ### Excel Integration @@ -231,6 +246,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [mplfinance](https://github.com/matplotlib/mplfinance) - matplotlib utilities for the visualization, and visual analysis, of financial data. - [finplot](https://github.com/highfestiva/finplot) - Performant and effortless finance plotting for Python. - [finvizfinance](https://github.com/lit26/finvizfinance) - Finviz analysis python library. +- [market-analy](https://github.com/maread99/market_analy) - Analysis and interactive charting using [market-prices](https://github.com/maread99/market_prices) and bqplot. ## R @@ -257,6 +273,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [Reddit WallstreetBets API](https://dashboard.nbshare.io/apps/reddit/api/) - Provides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API. - [td](https://github.com/eddelbuettel/td) - Interfaces the 'twelvedata' API for stocks and (digital and standard) currencies. - [rbcb](https://github.com/wilsonfreitas/rbcb) - R interface to Brazilian Central Bank web services. +- [rb3](https://github.com/ropensci/rb3) - A bunch of downloaders and parsers for data delivered from B3. +- [simfinapi](https://github.com/matthiasgomolka/simfinapi) - Makes 'SimFin' data () easily accessible in R. ### Financial Instruments and Pricing @@ -353,6 +371,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [MarketTechnicals.jl](https://github.com/JuliaQuant/MarketTechnicals.jl) - Technical analysis of financial time series on top of TimeSeries. - [MarketData.jl](https://github.com/JuliaQuant/MarketData.jl) - Time series market data. - [TimeFrames.jl](https://github.com/femtotrader/TimeFrames.jl) - A Julia library that defines TimeFrame (essentially for resampling TimeSeries). +- [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) - In-memory tabular data in Julia +- [TSFrames.jl](https://github.com/xKDR/TSFrames.jl) - Handle timeseries data on top of the powerful and mature DataFrames.jl ## Java @@ -370,6 +390,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [Ghostfolio](https://github.com/ghostfolio/ghostfolio) - Wealth management software to keep track of financial assets like stocks, ETFs or cryptocurrencies and make solid, data-driven investment decisions. - [IndicatorTS](https://github.com/cinar/indicatorts) - Indicator is a TypeScript module providing various stock technical analysis indicators, strategies, and a backtest framework for trading. - [ccxt](https://github.com/ccxt/ccxt) - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges. +- [PENDAX](https://github.com/CompendiumFi/PENDAX-SDK) - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More. +- [Mida](https://github.com/Reiryoku-Technologies/Mida) - The open-source and cross-platform trading framework (https://www.mida.org/). ### Data Visualization @@ -416,6 +438,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [QuantLibXL](https://www.quantlib.org/quantlibxl/) - Excel support. - [QLNet](https://github.com/amaggiulli/qlnet) - .Net port. - [PyQL](https://github.com/enthought/pyql) - Python port. + - [QuantLib-Python Documentation](https://quantlib-python-docs.readthedocs.io/) - Documentation for the Python bindings for the QuantLib library - [QuantLib.jl](https://github.com/pazzo83/QuantLib.jl) - Julia port. - [TA-Lib](https://ta-lib.org) - perform technical analysis of financial market data. - [Portfolio Optimizer](https://portfoliooptimizer.io/) - Portfolio Optimizer is a Web API for portfolio analysis and optimization. @@ -429,6 +452,11 @@ A curated list of insanely awesome libraries, packages and resources for Quants ## Rust - [QuantMath](https://github.com/MarcusRainbow/QuantMath) - Financial maths library for risk-neutral pricing and risk +- [Barter](https://github.com/barter-rs/barter-rs) - Open-source Rust framework for building event-driven live-trading & backtesting systems +- [LFEST](https://github.com/MathisWellmann/lfest-rs) - Simulated perpetual futures exchange to trade your strategy against. +- [TradeAggregation](https://github.com/MathisWellmann/trade_aggregation-rs) - Aggregate trades into user-defined candles using information driven rules. +- [SlidingFeatures](https://github.com/MathisWellmann/sliding_features-rs) - Chainable tree-like sliding windows for signal processing and technical analysis. +- [RustQuant](https://github.com/avhz/RustQuant) - Quantitative finance library written in Rust. ## Reproducing Works, Training & Books @@ -461,7 +489,13 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [QuantFinanceBook](https://github.com/LechGrzelak/QuantFinanceBook) - Quantitative Finance book. - [rough_bergomi](https://github.com/ryanmccrickerd/rough_bergomi) - A Python implementation of the rough Bergomi model. - [frh-fx](https://github.com/ryanmccrickerd/frh-fx) - A python implementation of the fast-reversion Heston model of Mechkov for FX purposes. -- [value-investing-studies](https://github.com/euclidjda/value-investing-studies) - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time. -- [machine-learning-asset-management](https://github.com/firmai/machine-learning-asset-management) - Machine Learning in Asset Management (by @firmai). -- [Deep-Learning-Machine-Learning-Stock](https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock) - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders. -- [Technical_Analysis_and_Feature_Engineering](https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering) - Feature Engineering and Feature Importance of Machine Learning in Financial Market. +- [Value Investing Studies](https://github.com/euclidjda/value-investing-studies) - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time. +- [Machine Learning Asset Management](https://github.com/firmai/machine-learning-asset-management) - Machine Learning in Asset Management (by @firmai). +- [Deep Learning Machine Learning Stock](https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock) - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders. +- [Technical Analysis and Feature Engineering](https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering) - Feature Engineering and Feature Importance of Machine Learning in Financial Market. +- [Differential Machine Learning and Axes that matter by Brian Huge and Antoine Savine](https://github.com/differential-machine-learning/notebooks) - 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. +- [systematictradingexamples](https://github.com/robcarver17/systematictradingexamples) - Examples of code related to book [Systematic Trading](www.systematictrading.org) and [blog](http://qoppac.blogspot.com) +- [pysystemtrade_examples](https://github.com/robcarver17/pysystemtrade_examples) - Examples using pysystemtrade for Robert Carver's [blog](http://qoppac.blogspot.com). +- [ML_Finance_Codes](https://github.com/mfrdixon/ML_Finance_Codes) - Machine Learning in Finance: From Theory to Practice Book +- [Hands-On Machine Learning for Algorithmic Trading](https://github.com/packtpublishing/hands-on-machine-learning-for-algorithmic-trading) - Hands-On Machine Learning for Algorithmic Trading, published by Packt +- [financialnoob-misc](https://github.com/financialnoob/misc) - Codes from @financialnoob's posts diff --git a/projects.csv b/projects.csv index af3888b..4aba65c 100644 --- a/projects.csv +++ b/projects.csv @@ -331,3 +331,5 @@ value-investing-studies,"Reproducing Works, Training & Books",2021-10-26,https:/ machine-learning-asset-management,"Reproducing Works, Training & Books",2021-12-17,https://github.com/firmai/machine-learning-asset-management,Machine Learning in Asset Management (by @firmai).,True,False,firmai/machine-learning-asset-management Deep-Learning-Machine-Learning-Stock,"Reproducing Works, Training & Books",2022-06-01,https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock,Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.,True,False,LastAncientOne/Deep-Learning-Machine-Learning-Stock Technical_Analysis_and_Feature_Engineering,"Reproducing Works, Training & Books",2021-08-19,https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering,Feature Engineering and Feature Importance of Machine Learning in Financial Market.,True,False,jo-cho/Technical_Analysis_and_Feature_Engineering +Barter,Rust,2022-10-18,https://github.com/barter-rs/barter-rs,Open-source Rust framework for building event-driven live-trading & backtesting systems,True,False,barter-rs/barter-rs +RustQuant,Rust,2023-06-16,https://github.com/avhz/RustQuant,A Rust library for quantitative finance.,True,False,avhz/RustQuant diff --git a/projects.md b/projects.md index 189a022..a83ee1c 100644 --- a/projects.md +++ b/projects.md @@ -331,4 +331,5 @@ | value-investing-studies | Reproducing Works, Training & Books | 2021-10-26 | https://github.com/euclidjda/value-investing-studies | A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time. | True | False | euclidjda/value-investing-studies | | machine-learning-asset-management | Reproducing Works, Training & Books | 2021-12-17 | https://github.com/firmai/machine-learning-asset-management | Machine Learning in Asset Management (by @firmai). | True | False | firmai/machine-learning-asset-management | | Deep-Learning-Machine-Learning-Stock | Reproducing Works, Training & Books | 2022-06-01 | https://github.com/LastAncientOne/Deep-Learning-Machine-Learning-Stock | Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders. | True | False | LastAncientOne/Deep-Learning-Machine-Learning-Stock | -| Technical_Analysis_and_Feature_Engineering | Reproducing Works, Training & Books | 2021-08-19 | https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering | Feature Engineering and Feature Importance of Machine Learning in Financial Market. | True | False | jo-cho/Technical_Analysis_and_Feature_Engineering | \ No newline at end of file +| Technical_Analysis_and_Feature_Engineering | Reproducing Works, Training & Books | 2021-08-19 | https://github.com/jo-cho/Technical_Analysis_and_Feature_Engineering | Feature Engineering and Feature Importance of Machine Learning in Financial Market. | True | False | jo-cho/Technical_Analysis_and_Feature_Engineering | +| Barter | Rust | 2022-10-18 | https://github.com/barter-rs/barter-rs | Open-source Rust framework for building event-driven live-trading & backtesting systems | True | False | barter-rs/barter-rs |