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exprfuncs.py
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exprfuncs.py
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#
# Expression Functions
##
import datetime, yfinance as yfinance
import math
def expr_test_b(x,d):
return x*((d%2)+1) # starts with 5
def expr_test_a(x,d):
return x # starts with 10
def get_price_expr(tick,d):
if isinstance(d,datetime.date):
res = yfinance.get_historical(tick,d)
print 'result: ',res
return res
else:
return yfinance.get_price(tick)
def get_change(tick,d):
return yfinance.get_change(tick)
def get_volume(tick,d):
return yfinance.get_volume(tick)
def get_avg_daily_volume(tick,d):
return yfinance.get_avg_daily_volume(tick)
def get_book_value(tick,d):
return yfinance.get_book_value(tick)
def get_ebitda(tick,d):
return yfinance.get_ebitda(tick)
def get_dividend_yield(tick,d):
return yfinance.get_dividend_yield(tick)
def get_dividend_per_share(tick,d):
return yfinance.get_dividend_per_share(tick)
def get_earnings_per_share(tick,d):
return yfinance.get_earnings_per_share(tick)
def get_52_week_high(tick,d):
return yfinance.get_52_week_high(tick)
def get_52_week_low(tick,d):
return yfinance.get_52_week_low(tick)
def get_50day_moving_avg(tick,d):
return yfinance.get_50day_moving_avg(tick)
def get_200day_moving_avg(tick,d):
return yfinance.get_200day_moving_avg(tick)
def get_price_earnings_ratio(tick,d):
return yfinance.get_price_earnings_growth_ratio(tick)
def get_price_earnings_growth_ratio(tick,d):
return yfinance.get_price_earnings_growth_ratio(tick)
def get_price_sales_ratio(tick,d):
return yfinance.get_price_sales_ratio(tick)
def get_price_book_ratio(tick,d):
return yfinance.get_price_book_ratio(tick)
def get_short_ratio(tick,d):
return yfinance.get_short_ratio(tick)
def get_market_cap(tick,d):
"""print d
print str(isinstance(d, datetime.date))"""
mktcap = yfinance.get_market_cap(tick)
'''print "MKT CAP is " + str(mktcap)'''
""" this is an example, only supported in realtime """
return mktcap
def mean(tick, d, days=10.0):
end = datetime.date.today()
price_sum = 0.0
for i in xrange(1,int(days) + 1):
price_sum += float(get_price_expr(tick, end - datetime.timedelta(i)))
return price_sum/days
def mean_10_day(tick,d):
return mean(tick, d, 10.0)
def mean_30_day(tick,d):
return mean(tick, d, 30.0)
def std_dev(tick,d,days=10.0):
return math.sqrt(variance(tick,d,days))
def std_dev_10_days(tick,d):
return std_dev(tick,d,10.0)
def std_dev_30_days(tick,d):
return std_dev(tick,d,30.0)
def variance(tick, d, days=10.0):
end = datetime.date.today()
summand = 0.0
the_mean = mean(tick, d, days)
sum_squares = 0.0
for i in xrange(1, int(days) + 1):
price = float(get_price_expr(tick, end - datetime.timedelta(i)))
sum_squares += price * price
summand += price
variance = (sum_squares - (summand * the_mean))/(days - 1)
return variance
def variance_10_day(tick,d):
return variance(tick,d,10.0)
def variance_30_day(tick,d):
return variance(tick,d,30.0)
'''Technical functions'''
def covariance(tickA, tickB, d, days=10.0):
end = datetime.date.today()
summand = 0.0
meanA = mean(tickA, d, days)
meanB = mean(tickB, d, days)
for i in xrange(1,int(days) + 1):
day = end - datetime.timedelta(i)
priceA = float(get_price_expr(tickA, day))
priceB = float(get_price_expr(tickB, day))
summand += (priceA - meanA)*(priceB - meanB)
return (1/(days - 1))*summand
def covariance_10_days(tickA, tickB, d):
return covariance(tickA, tickB, d, 10.0)
def covariance_30_days(tickA, tickB, d):
return covariance(tickA, tickB, d, 30.0)
def correlation(tickA, tickB, d, days=10.0):
#correlation is simply covariance deflated by its standard deviations
return covariance(tickA, tickB, d, days)/(std_dev(tickA, d, days)*std_dev(tickB,d,days))
def correlation_10_day(tickA, tickB, d):
return correlation(tickA, tickB, d, 10.0)
def correlation_30_day(tickA, tickB, d):
return correlation(tickA, tickB, d, 30.0)
#### Set up attributes
def exprfunc_data():
return {
'expr_test_b':'ALL',
'expr_test_a':'ALL',
'get_price_expr':'ALL',
'get_market_cap':'REALTIME',
'get_change':'REALTIME',
'get_volume':'REALTIME',
'get_avg_daily_volume':'REALTIME',
'get_book_value':'REALTIME',
'get_ebitda':'REALTIME',
'get_dividend_per_share':'REALTIME',
'get_dividend_yield':'REALTIME',
'get_earnings_per_share':'REALTIME',
'get_52_week_high':'REALTIME',
'get_52_week_low':'REALTIME',
'get_50day_moving_avg':'REALTIME',
'get_200day_moving_avg':'REALTIME',
'get_price_earnings_ratio':'REALTIME',
'get_price_sales_ratio':'REALTIME',
'get_price_book_price':'REALTIME',
'get_short_ratio':'REALTIME',
'correlation_10_day':'REALTIME',
'correlation_30_day':'REALTIME',
'covariance_10_day':'REALTIME',
'covariance_30_day':'REALTIME',
'std_dev_10_day':'REALTIME',
'std_dev_30_day':'REALTIME',
'mean_10_day':'REALTIME',
'mean_30_day':'REALTIME',
'variance_10_day':'REALTIME',
'variance_30_day':'REALTIME',
}