def __init__(self, n_shares):
'''Each position is associated with: initial investment value (1000), number of shares, an unfair coin, and an array with entries representing each share's value'''
self.investment = 1000
self.nshares = n_shares
#You can only buy the shares in $1, $10, $100, $1000 denominations so nshares must be 1000, 100, 10 or 1
if self.nshares not in [1,10,100,1000]:
raise InvalidPositionError
else:
self.heads_return = 2 #Know that returns are either x0 or x2. Associate flipping heads on the coin with a x2 return.
self.coin = UnfairCoin()
self.shares = np.empty(self.nshares) #Array representing the position (set of shares). Each is valued at 1000/n_shares.
self.shares.fill(self.investment/self.nshares)
class Position(object):
'''Represents a set of shares with total value $1000 on the following investment:
With a one-day holding time, there is 51% chance the return is 1 (value doubles) and 49% chance that the return is -1 (all value is lost).'''
def __init__(self, n_shares):
'''Each position is associated with: initial investment value (1000), number of shares, an unfair coin, and an array with entries representing each share's value'''
self.investment = 1000
self.nshares = n_shares
#You can only buy the shares in $1, $10, $100, $1000 denominations so nshares must be 1000, 100, 10 or 1
if self.nshares not in [1,10,100,1000]:
raise InvalidPositionError
else:
self.heads_return = 2 #Know that returns are either x0 or x2. Associate flipping heads on the coin with a x2 return.
self.coin = UnfairCoin()
self.shares = np.empty(self.nshares) #Array representing the position (set of shares). Each is valued at 1000/n_shares.
self.shares.fill(self.investment/self.nshares)
def n_flips(self):
'''Flip an unfair coin nshares number of times.'''
flips = []
for f in range(self.nshares):
flips.append(self.coin.flip())
return np.asarray(flips)
def evaluate_return(self,arr):
'''Take a flip array and convert it to corresponding returns array: 2 for heads (1) and 0 for tails (0) using elementwise multiplication'''
return arr*self.heads_return
def simulate(self):
'''Flip a coin nshares number of times and evaluate the return that each flip corresponds to.
The return on investment is the sum of the element-wise product of evaluation*shares'''
return (self.evaluate_return(self.n_flips()) * self.shares).sum()