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README.md

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@@ -10,11 +10,12 @@ Backtesting.py
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Backtest trading strategies with Python.
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[**Project website**][website]
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[**Project website**](https://kernc.github.io/backtesting.py)
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[Documentation]
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[website]: https://kernc.github.io/backtesting.py/
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[![Star](https://i.imgur.com/LSI6p6O.png)](#top) the project if you use it.
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[Documentation]: https://kernc.github.io/backtesting.py/doc/backtesting/
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@@ -102,101 +103,9 @@ Features
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* Detailed results
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* Interactive visualizations
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-------------------------------------------------
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Alternatives
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------------
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The thing with backtesting is, unless you dug into the dirty details yourself,
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you can't rely on execution correctness, and you risk losing your house.
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In addition, everyone has their own preconveived ideas about how a mechanical
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trading strategy should be conducted, so everyone (and their brother)
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just rolls their own backtesting frameworks.
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If after reviewing the docs and exmples perchance you find
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[_Backtesting.py_][website] not your cup of tea,
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kindly have a look at some similar alternative Python backtesting frameworks:
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- [bt](http://pmorissette.github.io/bt/) -
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a framework based on reusable and flexible blocks of
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strategy logic that support multiple instruments and
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output detailed statistics and useful charts.
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- [vectorbt](https://polakowo.io/vectorbt/) -
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a pandas-based library for quickly analyzing trading strategies at scale.
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- [Backtrader](https://www.backtrader.com/) -
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a pure-python feature-rich framework for backtesting
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and live algotrading with a few brokers.
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- [PyAlgoTrade](https://gbeced.github.io/pyalgotrade/) -
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event-driven algorithmic trading library with focus on
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backtesting and support for live trading.
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- [Zipline](https://www.zipline.io/) -
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the backtesting and live-trading engine powering Quantopian — the
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community-centered, hosted platform for building and executing strategies.
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- [Pinkfish](http://fja05680.github.io/pinkfish/) -
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a lightweight backtester for intraday strategies on daily data.
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- [finmarketpy](https://github.com/cuemacro/finmarketpy) -
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a library for analyzing financial market data.
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- [QuantStart QSTrader](https://github.com/mhallsmoore/qstrader/) -
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a modular schedule-driven backtesting framework for long-short equities
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and ETF-based systematic trading strategies.
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- [pysystemtrade](https://github.com/robcarver17/pysystemtrade) -
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the open-source version of Robert Carver's backtesting engine that
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implements systems according to his book _Systematic Trading:
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A unique new method for designing trading and investing systems_.
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- [QTPyLib](https://github.com/ranaroussi/qtpylib) -
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a versatile, event-driven algorithmic trading library.
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- [Gemini](https://github.com/anfederico/Gemini) -
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a backtester namely focusing on cryptocurrency markets.
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- [Quantdom](https://github.com/constverum/Quantdom) -
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a Qt-based framework that lets you focus on modeling financial strategies,
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portfolio management, and analyzing backtests.
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- [Clairvoyant](https://github.com/anfederico/Clairvoyant) -
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software for identifying and monitoring social / historical cues
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for short-term stock movement.
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- [optopsy](https://github.com/michaelchu/optopsy) -
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a nimble backtesting library for options trading.
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- [RQalpha](https://github.com/ricequant/rqalpha) -
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a complete solution for programmatic traders from data acquisition,
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algorithmic trading, backtesting, real-time simulation, live trading
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to mere data analysis. Documentation in Chinese.
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- [zvt](https://github.com/zvtvz/zvt) -
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a quant trading platform which includes data recorder, factor calculation,
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stock picking, backtesting, and unified visualization. Documentation in Chinese.
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- [AwesomeQuant](https://github.com/wilsonfreitas/awesome-quant#trading--backtesting) -
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A somewhat curated list of libraries, packages, and resources for quants.
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#### Obsolete / Unmaintained
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The following projects are mainly old, stale, incomplete, incompatible,
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abandoned, and here for posterity reference only:
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- [AlephNull](https://github.com/CarterBain/AlephNull) -
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extends the features of Zipline, for use within an institutional environment.
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- [ProfitPy](https://code.google.com/p/profitpy/) -
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a set of libraries and tools for the development, testing, and execution of
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automated stock trading systems.
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- [prophet](https://github.com/Emsu/prophet) -
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a microframework for financial markets, focusing on modeling
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strategies and portfolio management.
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- [pybacktest](https://github.com/ematvey/pybacktest) -
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a vectorized pandas-based backtesting framework,
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designed to make backtesting compact, simple and fast.
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- [quant](https://github.com/maihde/quant) -
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a technical analysis tool for trading strategies with a particularily
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simplistic view of the market.
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- [QuantSoftware Toolkit](https://github.com/QuantSoftware/QuantSoftwareToolkit) -
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a toolkit by the guys that soon after went to form Lucena Research.
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- [QuantStart QSForex](https://github.com/mhallsmoore/qsforex) -
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an event-driven backtesting and live-trading platform for use in
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the foreign exchange markets,
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- [tia: Toolkit for integration and analysis](https://github.com/PaulMest/tia/) -
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a toolkit providing Bloomberg data access, PDF generation,
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technical analysis and backtesting functionality.
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- [TradingWithPython](https://github.com/sjev/trading-with-python) -
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boiler-plate code for the (no longer active) course _Trading With Python_.
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- [Ultra-Finance](https://github.com/panpanpandas/ultrafinance) -
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real-time financial data collection, analyzing and backtesting trading strategies.
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- [visualize-wealth](https://github.com/benjaminmgross/visualize-wealth) -
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a library to construct, backtest, analyze, and evaluate portfolios
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and their benchmarks, with comprehensive documentation illustrating
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all underlying methodologies and statistics.
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See [alternatives.md] for a list of alternative Python
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backtesting frameworks and related packages.
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[alternatives.md]: https://github.com/kernc/backtesting.py/blob/master/doc/alternatives.md

doc/alternatives.md

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Alternatives
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------------
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The thing with backtesting is, unless you dug into the dirty details yourself,
4+
you can't rely on execution correctness, and you risk losing your house.
5+
In addition, everyone has their own preconveived ideas about how a mechanical
6+
trading strategy should be conducted, so everyone (and their brother)
7+
just rolls their own backtesting frameworks.
8+
9+
If after reviewing the docs and exmples perchance you find
10+
[_Backtesting.py_](https://kernc.github.io/backtesting.py) not your cup of tea,
11+
kindly have a look at some similar alternative Python backtesting frameworks:
12+
13+
- [bt](http://pmorissette.github.io/bt/) -
14+
a framework based on reusable and flexible blocks of
15+
strategy logic that support multiple instruments and
16+
output detailed statistics and useful charts.
17+
- [vectorbt](https://polakowo.io/vectorbt/) -
18+
a pandas-based library for quickly analyzing trading strategies at scale.
19+
- [Backtrader](https://www.backtrader.com/) -
20+
a pure-python feature-rich framework for backtesting
21+
and live algotrading with a few brokers.
22+
- [PyAlgoTrade](https://gbeced.github.io/pyalgotrade/) -
23+
event-driven algorithmic trading library with focus on
24+
backtesting and support for live trading.
25+
- [Pinkfish](http://fja05680.github.io/pinkfish/) -
26+
a lightweight backtester for intraday strategies on daily data.
27+
- [finmarketpy](https://github.com/cuemacro/finmarketpy) -
28+
a library for analyzing financial market data.
29+
- [QuantStart QSTrader](https://github.com/mhallsmoore/qstrader/) -
30+
a modular schedule-driven backtesting framework for long-short equities
31+
and ETF-based systematic trading strategies.
32+
- [pysystemtrade](https://github.com/robcarver17/pysystemtrade) -
33+
the open-source version of Robert Carver's backtesting engine that
34+
implements systems according to his book _Systematic Trading:
35+
A unique new method for designing trading and investing systems_.
36+
- [QTPyLib](https://github.com/ranaroussi/qtpylib) -
37+
a versatile, event-driven algorithmic trading library.
38+
- [Gemini](https://github.com/anfederico/Gemini) -
39+
a backtester namely focusing on cryptocurrency markets.
40+
- [Quantdom](https://github.com/constverum/Quantdom) -
41+
a Qt-based framework that lets you focus on modeling financial strategies,
42+
portfolio management, and analyzing backtests.
43+
- [Clairvoyant](https://github.com/anfederico/Clairvoyant) -
44+
software for identifying and monitoring social / historical cues
45+
for short-term stock movement.
46+
- [optopsy](https://github.com/michaelchu/optopsy) -
47+
a nimble backtesting library for options trading.
48+
- [RQalpha](https://github.com/ricequant/rqalpha) -
49+
a complete solution for programmatic traders from data acquisition,
50+
algorithmic trading, backtesting, real-time simulation, live trading
51+
to mere data analysis. Documentation in Chinese.
52+
- [zvt](https://github.com/zvtvz/zvt) -
53+
a quant trading platform which includes data recorder, factor calculation,
54+
stock picking, backtesting, and unified visualization. Documentation in Chinese.
55+
- [AwesomeQuant](https://github.com/wilsonfreitas/awesome-quant#trading--backtesting) -
56+
A somewhat curated list of libraries, packages, and resources for quants.
57+
58+
#### Obsolete / Unmaintained
59+
60+
The following projects are mainly old, stale, incomplete, incompatible,
61+
abandoned, and here for posterity reference only:
62+
63+
- [Zipline](https://www.zipline.io/) -
64+
the backtesting and live-trading engine powering Quantopian — the
65+
community-centered, hosted platform for building and executing strategies.
66+
- [AlephNull](https://github.com/CarterBain/AlephNull) -
67+
extends the features of Zipline, for use within an institutional environment.
68+
- [ProfitPy](https://code.google.com/p/profitpy/) -
69+
a set of libraries and tools for the development, testing, and execution of
70+
automated stock trading systems.
71+
- [prophet](https://github.com/Emsu/prophet) -
72+
a microframework for financial markets, focusing on modeling
73+
strategies and portfolio management.
74+
- [pybacktest](https://github.com/ematvey/pybacktest) -
75+
a vectorized pandas-based backtesting framework,
76+
designed to make backtesting compact, simple and fast.
77+
- [quant](https://github.com/maihde/quant) -
78+
a technical analysis tool for trading strategies with a particularily
79+
simplistic view of the market.
80+
- [QuantSoftware Toolkit](https://github.com/QuantSoftware/QuantSoftwareToolkit) -
81+
a toolkit by the guys that soon after went to form Lucena Research.
82+
- [QuantStart QSForex](https://github.com/mhallsmoore/qsforex) -
83+
an event-driven backtesting and live-trading platform for use in
84+
the foreign exchange markets,
85+
- [tia: Toolkit for integration and analysis](https://github.com/PaulMest/tia/) -
86+
a toolkit providing Bloomberg data access, PDF generation,
87+
technical analysis and backtesting functionality.
88+
- [TradingWithPython](https://github.com/sjev/trading-with-python) -
89+
boiler-plate code for the (no longer active) course _Trading With Python_.
90+
- [Ultra-Finance](https://github.com/panpanpandas/ultrafinance) -
91+
real-time financial data collection, analyzing and backtesting trading strategies.
92+
- [visualize-wealth](https://github.com/benjaminmgross/visualize-wealth) -
93+
a library to construct, backtest, analyze, and evaluate portfolios
94+
and their benchmarks, with comprehensive documentation illustrating
95+
all underlying methodologies and statistics.

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