超全Python 量化金融库汇总，必看

本文汇总了定量金融的大量三方库，按功能进行分类，覆盖数值运算，衍生品定价，回溯检验，风险管理，数据爬取，可视化等多个子领域，供每个Python程序员参考。

不要重复造轮子，明确要解决的问题，然后寻找相应的工具。很多著名的包如Numpy，Pandas，Seaborn，backtrader等已经被证明高度有效，即便没有找到符合应用场景的包，类似的工具也能够为创建自己的解决方案提供参考。

科学运算和数据结构

numpy[2] - 进行数值运算的基础包，scipy和numpy令Python进行有效的矩阵运算成为可能
scipy[3] - 科学计算生态系统，广泛应用于数学，物理学和工程学等自然科学领域
pandas[4] - 提供了高性能的数据结构和数据分析工具
quantdsl[5] - 金融/交易领域进行定量分析的领域特定语言
statistics[6] - 进行基础统计运算
sympy[7] - 专门用于符号数学
pymc3[8] - 用Python实现概率编程，贝叶斯建模，用Theano实现概率机器学习

金融工具和定价

PyQL[9] - Quantlib的Python接口
pyfin[10] - 期权定价
vollib[11] - 计算期权价格，隐含波动率和希腊值
QuantPy[12] - 定量金融分析
Finance-Python[13] - 定量金融分析
ffn[14] - 拓展Pandas，提供一系列函数进行基础的量化分析
pynance[15] - 获取股票和衍生品市场的数据，分析和可视化
hasura/base-python-dash[16] - 快速入门部署Dash应用，Dash基于Flask，Plotly.js和React.js，允许用户用纯Python快速搭建强大的数据科学网页App
hasura/base-python-bokeh[17] - 如何用Bokeh实现数据可视化
pysabr[18] - 用Python实现SABR模型

技术指标

pandas_talib[19] - 整合Pandas和Talib，用pandas计算技术指标
finta[20] - 用Pandas计算常见的技术指标
Tulipy[21] - 技术指标库（tulipindicators的Python绑定）

量化交易/回溯检验

TA-Lib[22] - 计算技术指标，跟Numpy深度整合
trade[23] - 用于开发金融应用的基础包
zipline[24] - 强大的回溯检验框架，被很多量化交易平台作为底层技术，包括Qauntopian, 聚宽等
QuantSoftware Toolkit[25] - 创建和管理投资组合
quantitative[26] - 定量金融的基础工具，回溯检验
analyzer[27] - 接收实时报价并回溯检验
bt[28] - 回溯检验框架，比Zipline更灵活
backtrader[29] - 回溯检验框架，支持实盘交易，过去几年快速崛起，已成为最流行的量化工具之一
pythalesians[30] - 回溯检验框架
pybacktest[31] - 向量化回溯检验框架，向量化允许进行快速的回溯，但检验精度不高
pyalgotrade[32] - 回溯检验框架
tradingWithPython[33] - 提供一系列函数和自定义类来管理量化交易
Pandas TA[34] - 拓展Pandas，包含115种技术指标，快速创建交易策略
ta[35] - 用Pandas计算技术指标
algobroker[36] - 算法交易的部署引擎
pysentosa[37] - sentosa交易系统的Python接口
finmarketpy[38] - 分析市场数据，支持简单回溯检验
binary-martingale[39] - 自动化交易程序，用马丁格尔策略交易二元期权
fooltrader[40] - 利用大数据技术进行量化分析，包含回溯检验
zvt[41] - 提供统一和灵活的方式来获取数据，计算因子，选股，回溯检验和实盘交易
pylivetrader[42] - 兼容zipline的实时交易库
pipeline-live[43] - zipline扩展库，用于实盘交易
zipline-extensions[44] - Zipline扩展，适配QuantRocket
moonshot[45] - 向量化回溯检验和交易引擎
PyPortfolioOpt[46] - 金融投资组合优化，包括创建有效边界和其它高级算法
riskparity.py[47] - 用TensorFlow设计风险平价投资组合
mlfinlab[48] - 《金融机器学习应用》一书的实现
pyqstrat[49] - 快速地回测交易策略
pinkfish[50] - 证券分析
aat[51] - 异步算法交易引擎
Backtesting.py[52] - 回溯检验框架
catalyst[53] - 回溯检验框架，专门用于数字货币市场
quantstats[54] - 投资组合分析
qtpylib[55] - 回溯检验框架，支持实盘交易
freqtrade[56] - 开源数字货币交易机器人
algorithmic-trading-with-python[57] - 《Python算法交易》一书的源码和数据
DeepDow[58] - 用深度学习优化投资组合

风险分析

pyfolio[59] - 计算投资组合和交易策略的业绩指标
empyrical[60] - 计算常用的风险和业绩指标
fecon235[61] - 金融计量经济工具包，包括leptokurtotic风险高斯混合模型，自适应Boltzmann投资组合
finance[62] - 计算金融风险
qfrm[63] - 定量金融风险管理
visualize-wealth[64] - 构建投资组合和定量分析
VisualPortfolio[65] - 可视化投资组合表现

因子分析

alphalens[66] - 分析预测性因子的表现

时间序列

ARCH[67] - Python实现ARCH模型
statsmodels[68] - 计量经济模型库，用于创建回归模型，统计检验，时序模型
dynts[69] - 操纵和分析时间序列
PyFlux[70] - 时间序列模型和因果推断
tsfresh[71] - 从时间序列中提取有意义的特征
hasura/quandl-metabase[72] - 可视化Quandl的时间序列数据集

日历

trading_calendars[73] - 股票交易所财经日历
bizdays[74] - 工作日计算和效用工具
pandas_market_calendars[75] - 拓展Pandas，股票交易所财经日历

数据源

findatapy[76] - 获取彭博终端，Quandl和雅虎财经的数据
googlefinance[77] - 从谷歌财经获取实时股票价格
yahoo-finance[78] - 从雅虎财经下载股票报价，历史价格，产品信息和财务报表
pandas-datareader[79] - 从多个数据源获取经济/金融时间序列，包括谷歌财经，雅虎财经，圣路易斯联储(FRED)，OECD, Fama/French，世界银行，欧元区统计局等，是Pandas生态系统的重要组成
pandas-finance[80] - 提供高级接口下载和分析金融时间序列
pyhoofinance[81] - 从雅虎财经批量获取股票数据
yfinanceapi[82] - 从雅虎财经获取数据
yql-finance[83] - 从雅虎财经获取数据
ystockquote[84] - 从雅虎财经获取实时报价
wallstreet[85] - 实时股票和期权报价
stock_extractor[86] - 从网络上爬取股票信息
Stockex[87] - 从雅虎财经获取数据
finsymbols[88] - 获取全美证券交易所，纽约证券交易所和纳斯达克上市公司的详细数据
inquisitor[89] - 从Econdb获取经济数据，Econdb是全球经济指标聚合器
chinesestockapi[90] - 获取A股数据
exchange[91] - 获取最新的汇率报价
ticks[92] - 命令行程序，获取股票报价
pybbg[93] - 彭博终端COM的Python接口
ccy[94] - 获取外汇数据
tushare[95] - 获取中国股票，基金，债券和期货市场的历史数据
jsm[96] - 获取日本股票市场的历史数据
cn_stock_src[97] - 从不同数据源获取中国的股票数据
coinmarketcap[98] - 从coinmarketcap获取数字货币数据
after-hours[99] - 获取美股盘前和盘后的市场价格
bronto-python[100] - 整合Bronto API接
pytdx[101] - 获取中国国内股票的实时报价
pdblp[102] - 整合Pandas和彭博终端的公共接口
tiingo[103] - 从Tiingo平台获取股票日K线和实时报价/新闻流
IEX[104] - 从IEX交易所获取股票的实时报价和历史数据
alpaca-trade-api[105] - 从Alpaca平台获取股票实时报价和历史数据，并提供交易接口交易美股
metatrader5[106] - 集成Python和MQL5交易平台，适合外汇交易
akshare[107] - 获取中国股票，基金，债券和宏观经济数据
yahooquery[108] - 从雅虎财经获取数据
investpy[109] - 从英为财经(Investing.com)获取数据
yliveticker[110] - 从雅虎财经通过Websocket获取实时报价

Excel集成

xlwings[111] - 深度整合Python和Excel
openpyxl[112] - 读取/写入Excel 2007 xlsx/xlsm文件
xlrd[113] - 从Excel电子表格提取数据
xlsxwriter[114] - 将数据写入Excel电子表格
xlwt[115] - 创建跨平台和向后兼容的电子表格
DataNitro[116] - 深度整合Python和Excel，可免费试用，商业付费软件
xlloop[117] - 创建Excel用户自定义函数
expy[118] - Excel插件，允许用户从电子表格中执行Python代码和定义自定义函数
pyxll[119] - Excel插件，从Excel中执行Python代码

可视化

Matplotlib[120] - Python数据可视化的基础包，从二维图表到三维图表
Seaborn[121] - 基于Matplotlib，快速创建美观的统计图表
Plotly[122] - 创建动态和交互式的图表
Altair[123] - 统计可视化工具，同时支持静态和交互式图表
D-Tale[124] - 可视化Pandas数据结构。

python学习

如果你想学习Python，但是找不到学习路径和资源
欢迎加入新的交流【君羊】：905229245
一起探讨编程知识,成为大神,群里还有软件安装包，实战案例、学习资料

地址链接

[1] Awesome Quant: https//github.com/wilsonfreitas/awesome-quant

[2] numpy: https//www.numpy.org/

[3] scipy: https//www.scipy.org/

[4] pandas: https//pandas.pydata.org/

[5] quantdsl: https//github.com/johnbywater/quantdsl

[6] statistics: https//docs.python.org/3/library/statistics.html

[7] sympy: https//www.sympy.org/

[8] pymc3: https//docs.pymc.io/

[9] PyQL: https//github.com/enthought/pyql

[10]

pyfin: https//github.com/opendoor-labs/pyfin

[11] vollib: https//github.com/vollib/vollib

[12] QuantPy: https//github.com/jsmidt/QuantPy

[13] Finance-Python: https//github.com/alpha-miner/Finance-Python

[14] ffn: https//github.com/pmorissette/ffn

[15] pynance: https//pynance.net/

[16] hasura/base-python-dash: https//platform.hasura.io/hub/projects/hasura/base-python-dash

[17] hasura/base-python-bokeh: https//platform.hasura.io/hub/projects/hasura/base-python-bokeh

[18] pysabr: https//github.com/ynouri/pysabr

[19] pandas_talib: https//github.com/femtotrader/pandas_talib

[20] finta: https//github.com/peerchemist/finta

[21] Tulipy: https//github.com/cirla/tulipy

[22] TA-Lib: https//ta-lib.org/

[23] trade: https//github.com/rochars/trade

[24] zipline: https//www.zipline.io/

[25] QuantSoftware Toolkit: https//github.com/QuantSoftware/QuantSoftwareToolkit

[26] quantitative: https//github.com/jeffrey-liang/quantitative

[27] analyzer: https//github.com/llazzaro/analyzer

[28] bt: https//github.com/pmorissette/bt

[29] backtrader: https//github.com/backtrader/backtrader

[30] pythalesians: https//github.com/thalesians/pythalesians

[31] pybacktest: https//github.com/ematvey/pybacktest

[32] pyalgotrade: https//github.com/gbeced/pyalgotrade

[33] tradingWithPython: https//pypi.org/project/tradingWithPython/

[34] Pandas TA: https//github.com/twopirllc/pandas-ta

[35] ta: https//github.com/bukosabino/ta

[36] algobroker: https//github.com/joequant/algobroker

[37] pysentosa: https//pypi.org/project/pysentosa/

[38] finmarketpy: https//github.com/cuemacro/finmarketpy

[39] binary-martingale: https//github.com/metaperl/binary-martingale

[40] fooltrader: https//github.com/foolcage/fooltrader

[41] zvt: https//github.com/zvtvz/zvt

[42] pylivetrader: https//github.com/alpacahq/pylivetrader

[43] pipeline-live: https//github.com/alpacahq/pipeline-live

[44] zipline-extensions: https//github.com/quantrocket-llc/zipline-extensions

[45] moonshot: https//github.com/quantrocket-llc/moonshot

[46] PyPortfolioOpt: https//github.com/robertmartin8/PyPortfolioOpt

[47] riskparity.py: https//github.com/dppalomar/riskparity.py

[48] mlfinlab: https//github.com/hudson-and-thames/mlfinlab

[49] pyqstrat: https//github.com/abbass2/pyqstrat

[50] pinkfish: https//github.com/fja05680/pinkfish

[51] aat: https//github.com/timkpaine/aat

[52] Backtesting.py: https//kernc.github.io/backtesting.py/

[53] catalyst: https//github.com/enigmampc/catalyst

[54] quantstats: https//github.com/ranaroussi/quantstats

[55] qtpylib: https//github.com/ranaroussi/qtpylib

[56] freqtrade: https//github.com/freqtrade/freqtrade

[57] algorithmic-trading-with-python: https//github.com/chrisconlan/algorithmic-trading-with-python

[58] DeepDow: https//github.com/jankrepl/deepdow

[59] pyfolio: https//github.com/quantopian/pyfolio

[60] empyrical: https//github.com/quantopian/empyrical

[61] fecon235: https//github.com/rsvp/fecon235

[62] finance: https//pypi.org/project/finance/

[63] qfrm: https//pypi.org/project/qfrm/

[64] visualize-wealth: https//github.com/benjaminmgross/visualize-wealth

[65] VisualPortfolio: https//github.com/wegamekinglc/VisualPortfolio

[66] alphalens: https//github.com/quantopian/alphalens

[67]

ARCH: https//github.com/bashtage/arch

[68] statsmodels: https://link.zhihu.com/?target=http%3A//statsmodels.sourceforge.net/

[69] dynts: https//github.com/quantmind/dynts

[70] PyFlux: https//github.com/RJT1990/pyflux

[71] tsfresh: https//github.com/blue-yonder/tsfresh

[72] hasura/quandl-metabase: https//platform.hasura.io/hub/projects/anirudhm/quandl-metabase-time-series

[73] trading_calendars: https//github.com/quantopian/trading_calendars

[74] bizdays: https//github.com/wilsonfreitas/python-bizdays

[75] pandas_market_calendars: https//github.com/rsheftel/pandas_market_calendars

[76] findatapy: https//github.com/cuemacro/findatapy

[77] googlefinance: https//github.com/hongtaocai/googlefinance

[78] yahoo-finance: https//github.com/lukaszbanasiak/yahoo-finance

[79] pandas-datareader: https//github.com/pydata/pandas-datareader

[80] pandas-finance: https//github.com/davidastephens/pandas-finance

[81] pyhoofinance: https//github.com/innes213/pyhoofinance

[82] yfinanceapi: https//github.com/Karthik005/yfinanceapi

[83] yql-finance: https//github.com/slawek87/yql-finance

[84] ystockquote: https//github.com/cgoldberg/ystockquote

[85] wallstreet: https//github.com/mcdallas/wallstreet

[86] stock_extractor: https//github.com/ZachLiuGIS/stock_extractor

[87] Stockex: https//github.com/cttn/Stockex

[88] finsymbols: https//github.com/skillachie/finsymbols

[89] inquisitor: https//github.com/econdb/inquisitor

[90] chinesestockapi: https//pypi.org/project/chinesestockapi/

[91] exchange: https//github.com/akarat/exchange

[92] ticks: https//github.com/jamescnowell/ticks

[93] pybbg: https//github.com/bpsmith/pybbg

[94] ccy: https//github.com/lsbardel/ccy

[95] tushare: https//pypi.org/project/tushare/

[96] jsm: https//pypi.org/project/jsm/

[97] cn_stock_src: https//github.com/jealous/cn_stock_src

[98] coinmarketcap: https//github.com/barnumbirr/coinmarketcap

[99] after-hours: https//github.com/datawrestler/after-hours

[100] bronto-python: https//pypi.org/project/bronto-python/

[101] pytdx: https//github.com/rainx/pytdx

[102] pdblp: https//github.com/matthewgilbert/pdblp

[103] tiingo: https//github.com/hydrosquall/tiingo-python

[104] IEX: https//github.com/addisonlynch/iexfinance

[105] alpaca-trade-api: https//github.com/alpacahq/alpaca-trade-api-python

[106] metatrader5: https//pypi.org/project/MetaTrader5/

[107] akshare: https//github.com/jindaxiang/akshare

[108] yahooquery: https//github.com/dpguthrie/yahooquery

[109] investpy: https//github.com/alvarobartt/investpy

[110] yliveticker: https//github.com/yahoofinancelive/yliveticker

[111] xlwings: https//www.xlwings.org/

[112] openpyxl: https//openpyxl.readthedocs.io/en/latest/

[113]

xlrd: https//github.com/python-excel/xlrd

[114] xlsxwriter: https//xlsxwriter.readthedocs.io/

[115] xlwt: https//github.com/python-excel/xlwt

[116] DataNitro: https//datanitro.com/

[117] xlloop: https://link.zhihu.com/?target=http%3A//xlloop.sourceforge.net/

[118] expy: https://link.zhihu.com/?target=http%3A//www.bnikolic.co.uk/expy/expy.html

[119] pyxll: https//www.pyxll.com/

[120] Matplotlib: https//matplotlib.org/tutorials/index.html

[121] Seaborn: https//seaborn.pydata.org/

[122] Plotly: https//plotly.com/python/

[123] Altair: https//altair-viz.github.io/index.html

[124] D-Tale: https//github.com/man-group/dtale