Quant Trading

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

https://www.quantstart.com/

https://github.com/edtechre/pybroker

https://github.com/whittlem/pycryptobot

https://github.com/asavinov/intelligent-trading-bot

Forums & Discussions

ML-Quant

Quant Trading Libraries

General

RustQuant is a Rust library for quantitative finance.
zvt is a modular quant framework.

Technical Analysis

TA-Lib is an open-source technical analysis library for financial applications. It provides a wide range of technical indicators and functions for analyzing financial market data.
QuantLib is aimed at providing a comprehensive software framework for quantitative finance. QuantLib is a free/open-source library for modeling, trading, and risk management in real-life.
ffn is a library that contains many useful functions for those who work in quantitative finance. It stands on the shoulders of giants (Pandas, Numpy, Scipy, etc.) and provides a vast array of utilities, from performance measurement and evaluation to graphing and common data transformations.
riskparity.py riskparityportfolio provides solvers to design risk parity portfolios. In its simplest form, we consider the convex formulation with a unique solution proposed by Spinu (2013) and use cyclical methods inspired by Griveau-Billion et al. (2013) and Choi & Chen (2022). For more general formulations, which are usually nonconvex, we implement the successive convex approximation method proposed by Feng & Palomar (2015).

Indicators

TA-Lib is an open-source technical analysis library for financial applications. It provides a wide range of technical indicators and functions for analyzing financial market data.
indicator is a Golang module providing various stock technical analysis indicators for trading.
stock-indicators-python is a PyPI library package that produces financial market technical indicators. Send in historical price quotes and get back desired indicators such as moving averages, Relative Strength Index, Stochastic Oscillator, Parabolic SAR, etc. Nothing more. stock-indicators-python is based on Stock.Indicators which is implemented in C#.
Tulip Indicators is a library of functions for technical analysis of financial time series data. It is written in ANSI C for speed and portability. Bindings are available for many other programming languages too.
trade_aggregation-rs is a high performance, modular and flexible trade aggregation crate, producing Candle data, suitable for low-latency applications and incremental updates. It allows the user to choose the rule dictating how a new candle is created through the AggregationRule trait, e.g: Time, Volume based or some other information driven rule. It also allows the user to choose which type of candle will be created from the aggregation process through the ModularCandle trait. Combined with the Candle macro, it enables the user to flexibly create any type of Candle as long as each component implements the CandleComponent trait. The aggregation process is also generic over the type of input trade data as long as it implements the TakerTrade trait, allowing for greater flexibility for downstream projects.
sliding_features-rs provides modular, chainable sliding windows with various signal processing functions and technical indicators.

Calendar

[python-bizdays] (https://github.com/wilsonfreitas/python-bizdays) offers business days calculations and utilities.

Backtesting

bt is a flexible backtesting framework for Python used to test quantitative trading strategies. Backtesting is the process of testing a strategy over a given data set. This framework allows you to easily create strategies that mix and match different Algos. It aims to foster the creation of easily testable, re-usable and flexible blocks of strategy logic to facilitate the rapid development of complex trading strategies.
vectorbt is a powerful Python library that enables easy backtesting of trading strategies, financial data analysis, and visualization. It provides a fast and efficient engine for quantitative finance research and algorithmic trading.
qstrader is a free Python-based open-source modular schedule-driven backtesting framework for long-short equities and ETF based systematic trading strategies.

Deep Learning

FinRL is an open-source framework for financial reinforcement learning. It aims to revolutionize FinTech by providing a comprehensive ecosystem for developing and deploying reinforcement learning-based trading strategies.

Good Platfroms

API Algo Trading Landscape has a good summary.

Charles Schwab supports algo trading via the thinkorswim® platform (thinkScript). For more details, please refer to Coding for Traders: Building Your Own Indicator . Charles Schwab is currently developing Trade APIs (both for commercial and individual) .

Alpaca

9 Great Tools for Algo Trading has a good summary

In terms of cost to get started, Alpaca < QuantConnect < QuantRocket < IteractiveBrokers .

Open Source Trading Platforms/Projects

MIT Open Course Ware - Trading

quantos, kungfu, vnpy, RQAlpha2

https://zhuanlan.zhihu.com/p/34822731

Quantopian

Quantitative Economics

Data Source

polygon.io

polygon.io is great data source with free plans available.

Taxes

Short-term taxes

Wash Sale

Please refer to Tips on Wash Sale
for detailed discussions.

Order Types

Trailing Stop Orders

Misc

http://www.zhihu.com/question/28557233?from=profile_question_card

http://myquant.cn/

http://www.vnpy.org/quantlib-tutorial.html

http://www.vnpy.org/talib-tutorial.html

http://www.vnpy.org/basic-tutorial-4.html

http://www.zhihu.com/question/33555640/answer/56820093

https://www.zhihu.com/question/25074959/answer/31184123?from=profile_answer_card

https://www.zhihu.com/question/21789812/answer/22369809

https://zhuanlan.zhihu.com/p/20505282?refer=edwardfuna

https://zhuanlan.zhihu.com/p/20502027?refer=edwardfuna

https://www.zhihu.com/question/34868706/answer/106024559

https://www.zhihu.com/question/36532600/answer/68127964?from=profile_answer_card

https://www.zhihu.com/question/31817168/answer/53462153

Tow the Iceburg

Prediction of Hidden Liquidity in the Limit Order Book of GLOBEX Futures

Mclean, R. David and Jeffrey Pontiff, 2016, Does Academic Research Destroy Stock Return Predictability, The Journal of Finance 71(1), 5-32.

Ben Chuanlong Du's Blog

It is never too late to learn.