Programming performance/TimN Python
- Language: Python
- Skill: Advanced. I've been coding in Python for several years and use it on a regular basis for work and fun. I've written several large programs in Python.
- Time: Less than 30 minutes. I did not keep track of time well and this is just an estimate.
- Notes: The noisy flag can be used to adjust the amount of output.
Code
#!/usr/bin/python
noisy = True
def lines(fn) :
return (l.strip() for l in file(fn))
def fields(fn) :
return (l.split(' ') for l in lines(fn) if l[0] != '#')
def closes(fn) :
return ((fs[0],float(fs[-1])) for fs in fields(fn))
def delta(p, oldp) :
return (p - oldp) / oldp
def strategy(ps) :
cash = 10000.0
held = 0.0
queue = []
p = 0.0
lastp = 1.0
for n,(date,p) in enumerate(ps) :
if delta(p, lastp) < -0.03 : # down 3%, buy 10%
cost = 0.10 * cash
quant = cost / p
queue.append((quant, p, n))
cash -= cost
held += quant
if noisy : print date, "buy %.2f at $%.2f ($%.2f)" % (quant, p, cost)
while len(queue) > 0 : # check triggers
quant, buyp, n2 = queue[-1]
if delta(p, buyp) > 0.06 : # up 6%, sell
queue.pop()
cost = quant * p
cash += cost
held -= quant
if noisy : print date, "sell %.2f at $%.2f ($%.2f)" % (quant, p, cost)
else :
break
lastp = p
if noisy : print queue
cash += held * p
return cash
# data is stored in reverse order.
series = list(closes('gspc'))
series.reverse()
val = strategy(series)
print '$%.2f' % val