EZFintech

EZFintech

Pypi: ezfintech

1. Introduction

Shanghai and Shenzhen Stock Data

• Data sources include: Netease, Sohu, StockStar
• Data API (ezfintech.stockData)
  • Daily data (on the same day, 4-day data)
  • Yearly data (yearly data)
  • Periodic data (daily/weekly/monthly data)
  • Interval data (data within the start and end date)
  • Real-time data (undeveloped)
  • Multiple stocks combined data (undeveloped)
• Data visualization (ezfintech.stockVisualization)
  • K-line chart
  • Golden Fork Dead Fork
  • Bollinger belt
• Data Analysis (ezfintech.stockAnalysis)
  • Regression analysis
  • Correlation Analysis
• Stock Finance related knowledge (ezfintech.stockKnowledge)
• Stock Model (ezfintech.stockAlgorithms.EZLSTM)

2. Dependency package

numpy,pandas,matplotlib,requests,mplfinance,pandas_datareader

3. How to use

3.1 Installation

python pip install ezfintech

3.2 Import

import ezfintech.stockData as ezd
import ezfintech.stockAnalysis as eza
import ezfintech.stockVisualization as ezv
import ezfintech.stockKnowledge as ezk
import ezfintech.stockModels.EZLSTM as ezm

3.3 Use

(1) Obtain stock data

---

• Daily data

 ezd.getStockByDay(stockCode,day="today",source="126")  
stockCode:"XXXXXXX"
day: "today" / "4d"  
source: "126"  

• Yearly data

 ezd.getStockByYear(stockCode,year="2020",adjust="klinederc",source="126")  
stockCode:"XXXXXXX"
year: "YYYY"   
adjust: "kline" / "klinederc"    
source: "126"  

• Periodic data

 ezd.getStockByPeriod(stockCode,period="week",adjust="klinederc",source="126")  
stockCode:"XXXXXXX"
period: "day" / "week" / "month"  
adjust: "kline" / "klinederc"   
source: "126" / "stockstar"  

• Interval data

 ezd.getStockByTwoDate(stockCode,startDate="20210301",endDate="20210308",source="sohu")  
stockCode:"XXXXXX"
startDate: "YYYYMMDD"  
endDate: "YYYYMMDD"  
source: "sohu"  

• Get FamaFrench factor data

 ezd.getFamaFrenchFactors(ffType="3factors",startDate="",endDate="")  
ffType: 3factors/5factors  
startDate: "YYYY-MM-DD"  
endDate: "YYYY-MM-DD"  

(2) Stock data visualization

---

• K-line chart

 ezv.plotKLine(data,movingAvg=(3,6,9),plotType="candle",startDate="",endDate="")  
data: pd.Dataframe  
movingAvg: (X1,X2,X3) or X1    
plotType: "candle" / "line" / "renko" / "pnf"  
startDate: "YYYY-MM-DD"  
endDate: "YYYY-MM-DD"  

• Golden Fork Dead Fork

 ezv.plotDoubleCross(data,priceType="Close",movingAvg=(5,40),startDate="",endDate="",returnData=False)  
data: pd.DataFrame with Date(index), Open/High/Low/Close/Volume(Columns)  
priceType: Close/Adj Close/Open/High/Low  
movingAvg: (period1,period2)  
startDate: "YYYY-MM-DD"   
endDate: "YYYY-MM-DD"  
returnData: True/False  

• Bollinger belt

 ezv.plotBollingerBand(data,priceType="Close",n=2,movingAvg=40,startDate="",endDate="",returnData=False)  
data: pd.DataFrame with Date(index), Open/High/Low/Close/Volume(Columns)  
priceType: Close/Adj Close/Open/High/Low  
n: how many times of deviation   
movingAvg: period  # 移动平均时间  
startDate: "YYYY-MM-DD"  
endDate: "YYYY-MM-DD"  
returnData: True/False  

(3) Stock data analysis

---

• Double stock regression analysis

 eza.regression2Stocks(stock1,stock2,startDate="",endDate="",regressDeg=1)  
stock1/stock2: pd.DataFrame with Date(index), Open/High/Low/Close/Volume(Columns)  
startDate: "YYYY-MM-DD"  
endDate: "YYYY-MM-DD"  
regressDeg: num  # 线性回归的次方  

• Custom OLS analysis

 eza.OLS(X,Y)  
Y: T x 1  
X: T x N  

• Dual stock correlation analysis

 eza.correlation2Stocks(stock1,stock2,startDate="",endDate="")  
stock1/stock2: pd.DataFrame  
startDate: "YYYY-MM-DD"  
endDate: "YYYY-MM-DD"  
regressDeg: num  

(4) Stock knowledge

---

• Stock Knowledge

 ezk.getStockKnowledge()  

• Financial analysis knowledge

 ezk.getFinanceAnalysisKnowledge()  

• Quantitative investment knowledge

 ezk.getQuantitativeInvestmentKnowledge()  

(4) Stock Model

---

• LSTM

 ezm.EZLSTM(outputSize, returnSequence)  
outputsize: XX   # 数字  
returnSequence: False/True