Screener.py

#Quellcode:

import quandl
import csv
import datetime
import numpy as np
import pandas as pd
import talib

#"relative strenght index"

def rsi():
	global rsid
	close = np.array(data_stock["Close"], dtype=float)
	high = np.array(data_stock["High"], dtype=float)
	low = np.array(data_stock["Low"], dtype=float)
	rsiu = talib.RSI(close, timeperiod=14)
	rsia = pd.Series(list(rsiu))
	rsib = pd.concat([rsia])
	rsic = pd.DataFrame(rsib)
	rsid= (rsic[0].tail(1))
	rsid = float(rsid)
	rsid = round (rsid,2)
	if rsid <20:
		print ("long:  ",name,rsid," rsi")
	if rsid >80:
		print ("short: ",name,rsid," rsi")


#"chande money oscillator"

def cmo():
	global cmoe
	stocknp = np.array(data_stock["Close"], dtype=float)
	cmoa = talib.CMO(stocknp, timeperiod=14)
	cmob = pd.Series(list(cmoa))
	cmoc = pd.concat([cmob])
	cmod = pd.DataFrame(cmoc)
	cmoe= (cmod[0].tail(1))
	cmoe = float(cmoe)
	cmoe = round (cmoe,2)
	if cmoe <-50:
		print ("long:  ",name,cmoe," cmo")
	if cmoe >50:
		print ("short: ",name,cmoe," cmo")

#"momentum"

def mom():
	global momd
	close = np.array(data_stock["Close"], dtype=float)
	mom = talib.MOM(close, timeperiod=10)
	moma = pd.Series(list(mom))
	momb = pd.concat([moma])
	momc = pd.DataFrame(momb)
	momd= (momc[0].tail(1))
	momd = float(momd)
	if momd <-10:
		print ("long:  ",name,cmoe," mom")
	if momd >10:
		print ("short: ",name,cmoe," mom")

def getstocks():
	global data_stock
	global data_stocklast
	global name
	un=["FSE/ADS_X","FSE/ALV_X","FSE/BAS_X","FSE/BAYN_X","FSE/BEI_X","FSE/BMW_X","FSE/CON_X","FSE/DAI_X","FSE/DB1_X","FSE/LHA_X","FSE/DPW_X","FSE/DTE_X","FSE/EON_X","FSE/FME_X","FSE/FRE_X","FSE/HEI_X","FSE/HEN3_X","FSE/IFX_X","FSE/LIN_X","FSE/MRK_X","FSE/MUV2_X","FSE/RWE_X","FSE/SAP_X","FSE/SIE_X","FSE/TKA_X","FSE/VOW3_X","FSE/WDI_X","FSE/SIX2_X","FSE/PUM_X","FSE/QIA_X","FSE/JEN_X","FSE/AFX_X","FSE/COK_X","FSE/BC8_X","FSE/AIXA_X","FSE/TEG_X","FSE/RHM_X","FSE/KU2_X","FSE/HNR1_X","FSE/DWNI_X","FSE/GIL_X","FSE/S92_X","FSE/SAZ_X","EURONEXT/GNE","EURONEXT/NOKIA","EURONEXT/CCE","EURONEXT/UNA","EURONEXT/UBI","EURONEXT/FP","EURONEXT/RTL","EURONEXT/RDSA","EURONEXT/RNO","EURONEXT/PGP","EURONEXT/UG","EURONEXT/ML","EURONEXT/HSB","EURONEXT/RMS","EURONEXT/HEIA","EURONEXT/ES","EURONEXT/BN","EURONEXT/CDI","EURONEXT/SANTA","EURONEXT/CS","EURONEXT/AMG","EURONEXT/ALO","EURONEXT/AIR","EURONEXT/MSF","EURONEXT/INCO","EURONEXT/CIS"]

	names=["Adidas","Allianz","Basf","Bayer","Beiersdorf","Bmw","Continental","Daimler","DeutscheBoerse","Lufthansa","DeutschePost","DeutscheTelekom","Eon","FreseniusMedicalCare","Fresenius","HeidelbergCement","Henkel","Infineon","Linde","Merck","MuenchnerRueck","Rwe","Sap","Siemens","ThyssenKrupp","Volkswagen","Wirecard","Sixt","Puma","Quiagen","Jenoptik","CarlZeissMeditec","Cancom","Bechtle","Aixtron","TagImmobilien","Rheinmetall","Kuka","HannoverRueck","DeutscheWohnen","DmgMori","SmaSolar","Stada","GeneralElectric","Nokia","CocaColaEurope","Unilever","Ubisoft","Total","RtlGroup","RoyalDutchShell","Renault","ProcterGamble","Peugeot","Michelin","HsbcHoldings","HermesIntl","Heineken","Esso","Danone","Dior","Santander","Axa","Amg","Alstom","Airbus","Microsoft","Intel","Cisco"]

	for name,un in zip(names,un):

		startdate = datetime.date(2018, 1, 1)
		today = datetime.date.today()
		quandl.ApiConfig.api_key ="Quandl Schlüssel hier einsetzen"
		data_stock = quandl.get(un,start_date=startdate, end_date=today)#, collapse = "weekly")
		data_stock = data_stock.rename(index=str, columns={"Last": "Close"})
		data_stock = data_stock.rename(index=str, columns={"Volume": "Traded Volume"})
		data_stocklast = data_stock["Close"].tail(1)
		try:

			data_stocklast = float(data_stocklast)
			cmo()
			mom()
			rsi()

		except:
			pass
		#print (data_stocklast)

getstocks()