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'''
Created on 2016年12月4日

@author: EricTseng
'''
import unittest


class Test(unittest.TestCase):


def testName(self):
pass


if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName']
unittest.main()
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'''
Created on 2016年11月日

@author: EricTseng
'''

from Investment.investment import *
from Investment.exp_handle import *

while True:
try:
positions = eval(input('Please input a list of positions.\n'))
num_trials = eval(input('Please input the number of trials.\n'))
simulationInit = trialInput(positions, num_trials)
simulationInit.simulate()
break
except InvalidListError:
print('Invalid position list.')
except PositionError:
print('Invalid positions in your list.')
except IntegerError:
print('Invalid Value. Trail number must be a integer.')

if __name__ == '__main__':
pass
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'''
Created on 2016年12月4日

@author: EricTseng
'''

import numpy as np
import matplotlib.pyplot as plt
from Investment.exp_handle import *

class trialInput(object):
def __init__(self, positionList, num_trials):
if not isinstance(positionList, list):
raise InvalidListError()
else:
denominations = [1000,100,10,1]
for i in range(len(positionList)):
if 1000/positionList[i] != denominations[i]:
raise PositionError()
if not isinstance(num_trials, int):
raise ValueError()

self.positionList = positionList
self.num_trials = num_trials


'''function that repeat num_trail times stimulation for each in
position_values and return their results as daily_ret.
Meanwhile, '''
def simulate(self):
f = open('results.txt', 'w')
for p in self.positionList:
cumu_ret=np.zeros(self.num_trials)
daily_ret=np.zeros(self.num_trials)
for t in range(self.num_trials):
cumu_num = 0
for i in range(int(1000/p)):
random_num = np.random.rand()
if (0 <= random_num <= 0.51):
cumu_num = cumu_num + 2 * p
elif (1 > random_num > 0.51):
cumu_num = cumu_num
cumu_ret[t]=cumu_num
daily_ret[t]=(cumu_ret[t]/1000)-1
plt.clf()
plt.hist(daily_ret,100,range=[-1,1])
plt.xlabel('Daily Returns')
plt.ylabel(str(p) + 'trails result')

if p ==1:
plt.savefig('histogram_0001_pos.pdf')
elif p == 10:
plt.savefig('histogram_0010_pos.pdf')
elif p ==100:
plt.savefig('histogram_0100_pos.pdf')
elif p ==1000:
plt.savefig('histogram_1000_pos.pdf')

ret_mean = np.mean(daily_ret)
ret_std = np.std(daily_ret)
f.write('mean of return for position ' + str(p) + ' : ' + str(ret_mean) + '\n')
f.write('std of return for position ' + str(p) + ' : ' + str(ret_std) + '\n')

f.close()
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'''
Created on 2016年12月4日

@author: EricTseng
'''

from investment.investment import *
import sys

if __name__ == '__main__':
while True:
try:
inputstr=input('Please enter a list of numbers of shares to buy in parallel, such as [1,10,100,1000]')
if (inputstr=='quit'):
print("User Directed Quit.")
sys.exit()
inputstr=inputstr.replace(' ','')#Remove extra blank
if inputstr=='':
raise ValueError('Invalid Input: Need a list of numbers of shares to buy in parallel')
if inputstr[0]!='[' or inputstr[-1]!=']':
raise ValueError('Invalid Input: Need a list of number in [ and ], such as [1,10,100,1000]')
positions=list(map(int,inputstr[1:-1].split(",")))
if any(x<=0 for x in positions):
raise ValueError('Invalid Input: all numbers of shares need to be positive')
break
except ValueError as msg:
print(msg)
except KeyboardInterrupt:
print('Keyboard Interruption')
sys.exit()
except EOFError:
print('EOFError')
sys.exit()

while True:
try:
inputstr2=input('Please enter the number of times you want to repeat the simulation')
if (inputstr2=='quit'):
print("User Directed Quit.")
sys.exit()
num_trials=int(inputstr2)
investment.investment(positions,num_trials).simulation()
break
except ValueError as msg:
print(msg)
except KeyboardInterrupt:
print('Keyboard Interruption')
sys.exit()
except EOFError:
print('EOFError')
sys.exit()
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'''
Created on 2016年11月日

@author: EricTseng
'''

from Investment.investment import *
from Investment.exceptions import *

while True:
try:
positions = eval(input('Please input a list of positions.\n'))
num_trials = eval(input('Please input the number of trials.\n'))
simulationInit = trialInput(positions, num_trials)
simulationInit.simulate()
break
except InvalidListError:
print('The position list you input is invalid. Please try again.')
except PositionError:
print('The positions in your list is invalid. Please try again.')
except IntegerError:
print('The number of trial must be an integer. Please try again.')

if __name__ == '__main__':
pass
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'''
Created on 2016年12月4日

@author: EricTseng
'''

import numpy as np
import matplotlib.pyplot as plt
from Investment.exceptions import *

class trialInput(object):
def __init__(self, positionList, num_trials):
if not isinstance(positionList, list):
raise InvalidListError()
else:
denominations = [1000,100,10,1]
for i in range(len(positionList)):
if 1000/positionList[i] != denominations[i]:
raise PositionError()
if not isinstance(num_trials, int):
raise IntegerError()

self.positionList = positionList
self.num_trials = num_trials

def simulate(self):
f = open('results.txt', 'w')
for position in self.positionList:
cumu_ret=np.zeros(self.num_trials)
daily_ret=np.zeros(self.num_trials)
for trial in range(self.num_trials):
num_win=np.random.binomial(position,0.49)
num_lost=position-num_win
position_value=1000/position
cumu_ret[trial]=(num_win*(1+1)+num_lost*(1-1))*position_value
daily_ret[trial]=(cumu_ret[trial]/1000)-1
plt.clf()
plt.hist(daily_ret,100,range=[-1,1])
plt.xlabel('Daily Returns')
plt.title('Histogram of Daily Returns for position = ' + str(position))
plt.savefig('histogram_'+'{:04d}'.format(position)+'_pos.pdf')
mean_ret = np.mean(daily_ret)
std_ret = np.std(daily_ret)
f.write('mean of return for position ' + str(position) + ' : ' + str(mean_ret) + '\n')
f.write('std of return for position ' + str(position) + ' : ' + str(std_ret) + '\n')
f.close()
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'''
Created on 2016年12月4日

@author: EricTseng
'''

from Investment.investment import *
import sys
import Investment

if __name__ == '__main__':
try:
inputstr=input('Please enter a list of numbers of shares to buy in parallel, such as [1,10,100,1000]')
if (inputstr=='quit'):
print("User Directed Quit.")
sys.exit()
inputstr=inputstr.replace(' ','')#Remove extra blank
if inputstr=='':
raise ValueError('Invalid Input: Need a list of numbers of shares to buy in parallel')
if inputstr[0]!='[' or inputstr[-1]!=']':
raise ValueError('Invalid Input: Need a list of number in [ and ], such as [1,10,100,1000]')
positions=list(map(int,inputstr[1:-1].split(",")))
if any(x<=0 for x in positions):
raise ValueError('Invalid Input: all numbers of shares need to be positive')
break
except ValueError as msg:
print(msg)
except KeyboardInterrupt:
print('Keyboard Interruption')
sys.exit()
except EOFError:
print('EOFError')
sys.exit()

while True:
try:
inputstr2=input('Please enter the number of times you want to repeat the simulation')
if (inputstr2=='quit'):
print("User Directed Quit.")
sys.exit()
num_trials=int(inputstr2)
Investment.investment(positions,num_trials).simulation()
break
except ValueError as msg:
print(msg)
except KeyboardInterrupt:
print('Keyboard Interruption')
sys.exit()
except EOFError:
print('EOFError')
sys.exit()
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'''
Created on 2016年12月4日

@author: EricTseng
'''

import numpy as np
import matplotlib.pyplot as plt
from Investment.exceptions import *

class trialInput(object):
def __init__(self, positionList, num_trials):
if not isinstance(positionList, list):
raise InvalidListError()
else:
denominations = [1000,100,10,1]
for i in range(len(positionList)):
if 1000/positionList[i] != denominations[i]:
raise PositionError()
if not isinstance(num_trials, int):
raise IntegerError()

self.positionList = positionList
self.num_trials = num_trials

def simulate(self):
f = open('results.txt', 'w')
for position in self.positionList:
cumu_ret=np.zeros(self.num_trials)
daily_ret=np.zeros(self.num_trials)
for trial in range(self.num_trials):
num_win=np.random.binomial(position,0.49)
num_lost=position-num_win
position_value=1000/position
cumu_ret[trial]=(num_win*(1+1)+num_lost*(1-1))*position_value
daily_ret[trial]=(cumu_ret[trial]/1000)-1
plt.clf()
plt.hist(daily_ret,100,range=[-1,1])
plt.xlabel('Daily Returns')
plt.title('Histogram of Daily Returns for position = ' str(position))
plt.savefig('histogram_'+'{:04d}'.format(position)+'_pos.pdf')
mean_ret = np.mean(daily_ret)
std_ret = np.std(daily_ret)
f.write('mean of return for position ' str(position) ' : ' str(mean_ret) '\n')
f.write('std of return for position ' str(position) ' : ' str(std_ret) '\n')
f.close()
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