def update(symbol):
stock = Stock(symbol)
#update stock
if stock.update_history() == False:
print 'this one is a dud'
return False
print 'got history'
#if no data, discard
#if data, add to list
#calculate 52 week high
#calculate n week average volume
#return stock
return stock
def strategy(symbol):
stock = Stock(symbol)
stock.update_history()
stock.analyze()
buy_dates = []
buy_prices = []
sell_dates = []
sell_prices = []
wiggly = piggy(sim=True,holdings=300)
buy_flag = False
staleness = 0
sell_flag = False
earn_flag = False
last_bought = 0
for itx, date in enumerate(stock.history_data['Date']):
ptrn_lookahead = 5
prox_thres = .02 * float(stock.history_data['Close'][itx])
if float(stock.history_data['30_Day'][itx-ptrn_lookahead]) - prox_thres <= float(stock.history_data['10_Day'][itx-ptrn_lookahead]) <= float(stock.history_data['30_Day'][itx-ptrn_lookahead]) + prox_thres\
and float(stock.history_data['30_Day'][itx-ptrn_lookahead]) - prox_thres <= float(stock.history_data['5_Day'][itx-ptrn_lookahead]) <= float(stock.history_data['30_Day'][itx-ptrn_lookahead]) + prox_thres\
and float(stock.history_data['30_Day'][itx]) > float(stock.history_data['10_Day'][itx]) > float(stock.history_data['5_Day'][itx]):
buy_flag = True
staleness = 0
gains_thres = 1.1
buy_slop_err = 0.001
if buy_flag \
and float(stock.history_data['5_Day'][itx]) * gains_thres < float(stock.history_data['30_Day'][itx]) \
and float(stock.history_data['5_Day'][itx]) > float(stock.history_data['5_Day'][itx-1]) * (1+buy_slop_err): ##Once there is enough margin betweet the 5 day and 30 day, buy
buy_dates.append(date)
buy_prices.append(float(stock.history_data['Close'][itx]))
buy_flag = False
staleness = 0
earn_flag = True
num = int(wiggly.holdings * .5 / float(stock.history_data['Close'][itx]))
wiggly.buy(stock,num,date=date)
buy_dates.append(date)
buy_prices.append(float(stock.history_data['Close'][itx]))
last_bought = itx
if (buy_flag
and staleness > 20
or (float(stock.history_data['5_Day'][itx]) > float(stock.history_data['10_Day'][itx]))):
buy_flag = False
staleness = 0
earn_thres = 1.2
if (earn_flag
and float(stock.history_data['10_Day'][itx]) > float(stock.history_data['10_Day'][itx-1]) * (1+buy_slop_err)
and float(stock.history_data['Close'][itx]) > float(stock.history_data['5_Day'][last_bought]) * earn_thres): ## and the 5 Day is increasing, then throw the EARNING flag
earn_flag = False
sell_flag = True
ceiling = .5
if (sell_flag
and float(stock.history_data['5_Day'][itx]) < float(stock.history_data['5_Day'][itx-1])) \
or (sell_flag and float(stock.history_data['5_Day'][itx]) > float(stock.history_data['5_Day'][itx]) * (ceiling + 1)):
sell_flag = False
wiggly.sell(stock,-1,date=date)
sell_dates.append(date)
sell_prices.append(float(stock.history_data['Close'][itx]))
staleness += 1
if wiggly.current_stock[stock.symbol] > 0:
print "\n\n#####Closing Out######"
wiggly.sell(stock,-1,date=date)
##Make a plot
import matplotlib.pyplot as plt
import matplotlib.dates as plotdate
import matplotlib.lines as line
import numpy as np
months = plotdate.MonthLocator() # every year
days = plotdate.DayLocator() # every month
monthsFmt = plotdate.DateFormatter('%m %d')
fig, ax = plt.subplots()
#ax2 = ax.twinx()
t = [datetime.datetime.strptime(date,'%Y-%m-%d') for date in stock.history_data['Date']]
ax.axis('auto')
# format the ticks
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(monthsFmt)
ax.xaxis.set_minor_locator(days)
fig.autofmt_xdate()
ax.plot(t, stock.history_data['5_Day'], '#0000FF')
ax.plot(t, stock.history_data['10_Day'], '#5555FF')
ax.plot(t, stock.history_data['30_Day'], '#9999FF')
#ax.plot(t, stock.history_data['80_Day'], '#AAAAFF')
#ax2.plot(t, stock.history_data['Volume'], '#CCFFCC')
#ax2.plot(t, stock.history_data['10_Day_Vol'], '#88AA88')
buy_dates = [datetime.datetime.strptime(date,'%Y-%m-%d') for date in buy_dates]
ax.plot(buy_dates,buy_prices, 'g|',ms=100)
sell_dates = [datetime.datetime.strptime(date,'%Y-%m-%d') for date in sell_dates]
ax.plot(sell_dates,sell_prices, 'b|',ms=100)
ax.plot(t, stock.history_data['Close'], 'r-')
plt.title(stock.symbol)
#ax.text(t[12], 250, 'hello')
plt.show()
return {'gains': wiggly.gains, 'symbol': stock.symbol, 'initial_value':stock.history_data['Open'][1]}
##Stragegy File
import datetime
from stock import Stock, piggy
from sys import argv
if __name__ == "__main__":
if len(argv) > 1:
if argv[1] == '--simulate':
if len(argv) < 3:
print 'Please specify symbol'
exit()
symbol = argv[2]
stock = Stock(symbol)
stock.update_history()
stock.analyze()
buy_dates = []
buy_prices = []
sell_dates = []
sell_prices = []
wiggly = piggy(sim=True,holdings=300)
for itx, date in enumerate(stock.history_data['Date']):
## Sell if the 10_day drops
trigger_drop = .02
trigger_starved = 1.5
if float(stock.history_data['10_Day'][itx]) <= float(stock.history_data['10_Day'][itx-5]) - trigger_drop*float(stock.history_data['10_Day'][itx]) \
and bool(wiggly.current_stock.get(stock.symbol)) and wiggly.current_stock[stock.symbol] >= 1:
wiggly.sell(stock,-1,date=date)
sell_dates.append(date)
