pyqstrat - A fast, extensible, transparent python library for backtesting quantitative strategies. NowTrade - Python library for backtesting technical/mechanical strategies in the stock and currency markets. pin
BacktraderfintaPandas TATa-LibPerformanceUsabilityStock Indicator Libraries Match 核心维度 在对基础库进行架构对比时,我们可以使用C4架构图来逐层展示各个库的组成部分和功能模块。以下是对主要库的C4架构对比图: <<person>>User<<container>>TA-Lib[Technical Analysis Library]Offers over 150 indicators<<container>...
import baostock as bs import pandas as pd import numpy as np import cv2 import math import os #saveStockData是保存股票的数据的函数,code是股票代码,startDate,endDate是起始日期,rootPath是保存路径,flag是日d,周w,月m标识符 def saveStockData(code,startDate,endDate,rootPath,flag): rs = bs.query...
Stock Indicators for Pythonis 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. ...
Technical Indicators using Python Ta-Lib We will first import the Python Ta-Lib library since we are using it to work out different indicators. Along with that, we use the python matplotlib to draw their graphs for analysis. Since we are going to be working on the stock prices, we will ...
Add your technical indicators (example: moving average, relative strength index, neural network, random forest, etc) Add criteria based on your technical indicators (example: neural network prediction is higher than current price) Associate actions to those criteria (example: go long when a certain...
ffn - A financial function library for Python. pynance - PyNance is open-source software for retrieving, analysing and visualizing data from stock and derivatives markets. tia - Toolkit for integration and analysis. hasura/base-python-dash - Hasura quickstart to deploy Dash framework. Written on...
对于每天运行的sh /data/stock/jobs/cron.daily/run_daily 进行分析 找到主要是guess_indicators_daily_job.py文件来调用相应的股票选择,根据经验与相关参数,调整如下: 1、对于需要关注的股票参数调整如下: 下面是原先的代码 # K值在80以上,D值在70以上,J值大于90时为超买。
self.buy_comm = None # 添加移动均线指标 self.sma = bt.indicators.SimpleMovingAverage(...
sql_1 = """SELECT `date`,`code`,`name`,`latest_price`,`quote_change`,`ups_downs`,`volume`,`turnover`,`amplitude`,`high`,`low`,`open`,`closed`,`quantity_ratio`,`turnover_rate`,`pe_dynamic`,`pb`,`kdjj`,`rsi_6`,`cci`FROM stock_data.guess_indicators_daily WHERE `date` = ...