def show_random_walks():
"plot 3 random walks of each type"
from models import test_sequences
iMinutesPerDay = 24*60
iDays = 1
iLen = iDays * iMinutesPerDay
lHours = [i/60.0 for i in range(iLen)]
lWalk_norm = test_sequences.random_walk(iLen, sTrend="normal")
lWalk_bull = test_sequences.random_walk(iLen, sTrend="bullish")
lWalk_bear = test_sequences.random_walk(iLen, sTrend="bearish")
import matplotlib.pyplot as plt
plt.plot(lHours, lWalk_bull, 'g', label="bull " + "{0:.2f}".format(lWalk_bull[-1]))
plt.plot(lHours, lWalk_norm, 'b', label="norm " + "{0:.2f}".format(lWalk_norm[-1]))
plt.plot(lHours, lWalk_bear, 'r', label="bear " + "{0:.2f}".format(lWalk_bear[-1]))
plt.legend(loc=3)
plt.title("normal, bullish, bearish random walks")
plt.xlabel("steps (hours)")
plt.ylabel("simulated stock price")
plt.show()
def trade():
"buy low, sell high"
from models import strategies, meta
iMinutesPerDay = 24*60
iDays = 1
iLen = iDays * iMinutesPerDay
iInitialAmount = 10000
oAccount = meta.Account(iInitialAmount, {})
from models import test_sequences
lWalk_norm_hist = test_sequences.random_walk(iLen, sTrend="normal", iStart=100)
oData = meta.Data("NormWalk", lData=lWalk_norm_hist)
oActiveTrading = strategies.Active(oData, oAccount)
#build the data as we go for every minute for one day
for i in range(iLen):
oActiveTrading.buy_low_sell_high(99, 101, 90, 0.1, "simple")
oData.add_random_walk("normal")
print oAccount.dStock[oData.sName], oData.lData[-1]
iAllStock = oAccount.dStock[oData.sName]['iNr']
oActiveTrading.sell(iAllStock, oData)
iProfit = oAccount.iCash - iInitialAmount
print "Profit made = {}".format(iProfit)
import matplotlib.pyplot as plt
plt.plot(oData.lData)
plt.title(iProfit)
plt.show()
