LEC 23 DYNAMIC AND READ DATA FROM TXT.py

import pylab
import random


class Stock(object):
    def __init__(self, price, distribution):
        self.price = price
        self.history = [price]
        self.distribution = distribution
        self.last_change = 0

    def set_price(self, price):
        self.price = price
        self.history.append(price)

    def get_price(self):
        return self.price

    def make_move(self, market_bias, momentum=False):
        old_price = self.price
        base_move = self.distribution() + market_bias
        self.price *= 1 + base_move
        if momentum:
            self.price += self.last_change * random.gauss(.5, .5)
        if self.price < .01:
            self.price = 0
        self.history.append(self.price)
        self.last_change = old_price - self.price

    def show_history(self, figure_number):
        pylab.figure(figure_number)
        pylab.plot(self.history)
        pylab.title('Closing Price, Test ' + str(figure_number))
        pylab.xlabel('DAY')
        pylab.ylabel('PRICE')
def get_dat(file_name):
    data = open(file_name, 'r')
    res = []
    for line in data:
        res.append(line.split(','))
    return res

def test():
    def run_simulation(stocks, fig):
        mean = 0
        for stock in stocks:
            for day in range(num_days):
                stock.make_move(market_bias, momentum)
            stock.show_history(fig)
            mean += stock.get_price()
        mean = mean / float(num_stocks)
        pylab.axhline(mean)

    data = get_dat('deviated data.txt')
    counter = 0
    for A in data:
        num_days = int(A[0])
        market_bias = float(A[2])
        momentum = bool(int(A[3]))
        num_stocks = int(A[1])
        stokes1 = []
        stokes2 = []
        for i in range(num_stocks):
            volatility = random.uniform(0, .20)
            d1 = lambda: random.uniform(-volatility, volatility)
            d2 = lambda: random.gauss(0, volatility / 2)
            stokes1.append(Stock(100, d1))
            stokes2.append(Stock(100, d2))
        counter += 1
        run_simulation(stokes1, counter)
        counter += 1
        run_simulation(stokes2, counter)


test()
pylab.show()