mcpricer.ipynb
379 lines
| 68.5 KiB
| text/plain
|
TextLexer
Brian E. Granger
|
r4634 | { | |
MinRK
|
r5486 | "metadata": { | |
"name": "mcpricer" | |||
}, | |||
"nbformat": 2, | |||
"worksheets": [ | |||
{ | |||
"cells": [ | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"# Parallel Monto-Carlo options pricing" | |||
] | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"## Problem setup" | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"import sys", | |||
"import time", | |||
"from IPython.parallel import Client", | |||
"import numpy as np", | |||
"from mckernel import price_options", | |||
"from matplotlib import pyplot as plt" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 1 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"cluster_profile = \"default\"", | |||
"price = 100.0 # Initial price", | |||
"rate = 0.05 # Interest rate", | |||
"days = 260 # Days to expiration", | |||
"paths = 10000 # Number of MC paths", | |||
"n_strikes = 6 # Number of strike values", | |||
"min_strike = 90.0 # Min strike price", | |||
"max_strike = 110.0 # Max strike price", | |||
"n_sigmas = 5 # Number of volatility values", | |||
"min_sigma = 0.1 # Min volatility", | |||
"max_sigma = 0.4 # Max volatility" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 2 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"strike_vals = np.linspace(min_strike, max_strike, n_strikes)", | |||
"sigma_vals = np.linspace(min_sigma, max_sigma, n_sigmas)" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 3 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"## Parallel computation across strike prices and volatilities" | |||
] | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"The Client is used to setup the calculation and works with all engines." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"c = Client(profile=cluster_profile)" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 4 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"A LoadBalancedView is an interface to the engines that provides dynamic load", | |||
"balancing at the expense of not knowing which engine will execute the code." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"view = c.load_balanced_view()" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 5 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"print \"Strike prices: \", strike_vals", | |||
"print \"Volatilities: \", sigma_vals" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "stream", | |||
"stream": "stdout", | |||
"text": [ | |||
"Strike prices: [ 90. 94. 98. 102. 106. 110.]", | |||
"Volatilities: [ 0.1 0.175 0.25 0.325 0.4 ]" | |||
] | |||
} | |||
], | |||
"prompt_number": 6 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Submit tasks for each (strike, sigma) pair." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"t1 = time.time()", | |||
"async_results = []", | |||
"for strike in strike_vals:", | |||
" for sigma in sigma_vals:", | |||
" ar = view.apply_async(price_options, price, strike, sigma, rate, days, paths)", | |||
" async_results.append(ar)" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 7 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"print \"Submitted tasks: \", len(async_results)" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "stream", | |||
"stream": "stdout", | |||
"text": [ | |||
"Submitted tasks: 30" | |||
] | |||
} | |||
], | |||
"prompt_number": 8 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Block until all tasks are completed." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"c.wait(async_results)", | |||
"t2 = time.time()", | |||
"t = t2-t1", | |||
"", | |||
"print \"Parallel calculation completed, time = %s s\" % t" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "stream", | |||
"stream": "stdout", | |||
"text": [ | |||
"Parallel calculation completed, time = 4.46057891846 s" | |||
] | |||
} | |||
], | |||
"prompt_number": 9 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"## Process and visualize results" | |||
] | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Get the results using the `get` method:" | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"results = [ar.get() for ar in async_results]" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 10 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Assemble the result into a structured NumPy array." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"prices = np.empty(n_strikes*n_sigmas,", | |||
" dtype=[('ecall',float),('eput',float),('acall',float),('aput',float)]", | |||
")", | |||
"", | |||
"for i, price in enumerate(results):", | |||
" prices[i] = tuple(price)", | |||
"", | |||
"prices.shape = (n_strikes, n_sigmas)" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 11 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Plot the value of the European call in (volatility, strike) space." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"plt.figure()", | |||
"plt.contourf(sigma_vals, strike_vals, prices['ecall'])", | |||
"plt.axis('tight')", | |||
"plt.colorbar()", | |||
"plt.title('European Call')", | |||
"plt.xlabel(\"Volatility\")", | |||
"plt.ylabel(\"Strike Price\")" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "pyout", | |||
"prompt_number": 12, | |||
"text": [ | |||
"<matplotlib.text.Text at 0x106b618d0>" | |||
] | |||
}, | |||
{ | |||
"output_type": "display_data", | |||
"png": 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8/fTTmDp1KmJiYlBTU4PXX38dI0aMwB133IG9e/fKPYLyJLUH0CZPDTFXxaa563niztq6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\nxkREGvD/vLHqAgUOcYsAAAAASUVORK5CYII=\n" | |||
} | |||
], | |||
"prompt_number": 12 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Plot the value of the Asian call in (volatility, strike) space." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"plt.figure()", | |||
"plt.contourf(sigma_vals, strike_vals, prices['acall'])", | |||
"plt.axis('tight')", | |||
"plt.colorbar()", | |||
"plt.title(\"Asian Call\")", | |||
"plt.xlabel(\"Volatility\")", | |||
"plt.ylabel(\"Strike Price\")" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "pyout", | |||
"prompt_number": 13, | |||
"text": [ | |||
"<matplotlib.text.Text at 0x106bd90d0>" | |||
] | |||
}, | |||
{ | |||
"output_type": "display_data", | |||
"png": 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lAZezHN514cIFvP7668jOzsbs2bObdURsUZuT72aqra1FcHAwLl68iJCQEABA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\nEUnGEBMRSfb/3Vuei4TCOWYAAAAASUVORK5CYII=\n" | |||
} | |||
], | |||
"prompt_number": 13 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Plot the value of the European put in (volatility, strike) space." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"plt.figure()", | |||
"plt.contourf(sigma_vals, strike_vals, prices['eput'])", | |||
"plt.axis('tight')", | |||
"plt.colorbar()", | |||
"plt.title(\"European Put\")", | |||
"plt.xlabel(\"Volatility\")", | |||
"plt.ylabel(\"Strike Price\")" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "pyout", | |||
"prompt_number": 14, | |||
"text": [ | |||
"<matplotlib.text.Text at 0x106d34150>" | |||
] | |||
}, | |||
{ | |||
"output_type": "display_data", | |||
"png": 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al3Ues3PnTm688Ubi4uKq3R8WFsbs2bOJiIigR48e/Pa3v+XOO++sdw1uxyDR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\nQmCC\n" | |||
} | |||
], | |||
"prompt_number": 14 | |||
}, | |||
{ | |||
"cell_type": "markdown", | |||
"source": [ | |||
"Plot the value of the Asian put in (volatility, strike) space." | |||
] | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": false, | |||
"input": [ | |||
"plt.figure()", | |||
"plt.contourf(sigma_vals, strike_vals, prices['aput'])", | |||
"plt.axis('tight')", | |||
"plt.colorbar()", | |||
"plt.title(\"Asian Put\")", | |||
"plt.xlabel(\"Volatility\")", | |||
"plt.ylabel(\"Strike Price\")" | |||
], | |||
"language": "python", | |||
"outputs": [ | |||
{ | |||
"output_type": "display_data", | |||
"png": 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eHq72MkhtHFW4HEcVnkP1HXF5eTlGjRqF4uJi+Pv7Y/v27Th16hQWLlyIVq1a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\nAeyS/5wqC8i5AAAAAElFTkSuQmCC\n" | |||
} | |||
], | |||
"prompt_number": 15 | |||
}, | |||
{ | |||
"cell_type": "code", | |||
"collapsed": true, | |||
"input": [ | |||
"plt.show()" | |||
], | |||
"language": "python", | |||
"outputs": [], | |||
"prompt_number": 16 | |||
} | |||
] | |||
} | |||
] | |||
Brian E. Granger
|
r4634 | } |