|
|
#!/usr/bin/env python
|
|
|
# encoding: utf-8
|
|
|
"""Run a Monte-Carlo options pricer in parallel."""
|
|
|
|
|
|
from IPython.kernel import client
|
|
|
import numpy as N
|
|
|
from mcpricer import MCOptionPricer
|
|
|
|
|
|
|
|
|
tc = client.TaskClient()
|
|
|
rc = client.MultiEngineClient()
|
|
|
|
|
|
# Initialize the common code on the engines
|
|
|
rc.run('mcpricer.py')
|
|
|
|
|
|
# Push the variables that won't change
|
|
|
#(stock print, interest rate, days and MC paths)
|
|
|
rc.push(dict(S=100.0, r=0.05, days=260, paths=10000))
|
|
|
|
|
|
task_string = """\
|
|
|
op = MCOptionPricer(S,K,sigma,r,days,paths)
|
|
|
op.run()
|
|
|
vp, ap, vc, ac = op.vanilla_put, op.asian_put, op.vanilla_call, op.asian_call
|
|
|
"""
|
|
|
|
|
|
# Create arrays of strike prices and volatilities
|
|
|
K_vals = N.linspace(90.0,100.0,5)
|
|
|
sigma_vals = N.linspace(0.0, 0.2,5)
|
|
|
|
|
|
# Submit tasks
|
|
|
taskids = []
|
|
|
for K in K_vals:
|
|
|
for sigma in sigma_vals:
|
|
|
t = client.StringTask(task_string,
|
|
|
push=dict(sigma=sigma,K=K),
|
|
|
pull=('vp','ap','vc','ac','sigma','K'))
|
|
|
taskids.append(tc.run(t))
|
|
|
|
|
|
print "Submitted tasks: ", taskids
|
|
|
|
|
|
# Block until tasks are completed
|
|
|
tc.barrier(taskids)
|
|
|
|
|
|
# Get the results
|
|
|
results = [tc.get_task_result(tid) for tid in taskids]
|
|
|
|
|
|
# Assemble the result
|
|
|
vc = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
|
|
|
vp = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
|
|
|
ac = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
|
|
|
ap = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
|
|
|
for i, tr in enumerate(results):
|
|
|
ns = tr.ns
|
|
|
vc[i] = ns.vc
|
|
|
vp[i] = ns.vp
|
|
|
ac[i] = ns.ac
|
|
|
ap[i] = ns.ap
|
|
|
vc.shape = (K_vals.shape[0],sigma_vals.shape[0])
|
|
|
vp.shape = (K_vals.shape[0],sigma_vals.shape[0])
|
|
|
ac.shape = (K_vals.shape[0],sigma_vals.shape[0])
|
|
|
ap.shape = (K_vals.shape[0],sigma_vals.shape[0])
|
|
|
|
|
|
|
|
|
def plot_options(K_vals, sigma_vals, prices):
|
|
|
"""Make a contour plot of the option prices."""
|
|
|
import pylab
|
|
|
pylab.contourf(sigma_vals, K_vals, prices)
|
|
|
pylab.colorbar()
|
|
|
pylab.title("Option Price")
|
|
|
pylab.xlabel("Volatility")
|
|
|
pylab.ylabel("Strike Price")
|
|
|
|
