Financial Modelling in Python

P1: JYS

c12 JWBK378-Fletcher May 28, 2009 10:59 Printer: Yet to come

188 Financial Modelling in Python

reg clsid = "{08632905-0B63-45B5-B388-30C73CAE611C}"

public methods = \

[

"CreateHullWhiteLatticePricer"

, "InvokePricer"

]

pricers = {}

retrieve = staticmethod(

lambda tag, which :

utils.retrieve(’pricer

server’, ’PricerServer’, tag, which))

def CreateHullWhiteLatticePricer(

self

, tag

, trade

id

, env

id

, num

states

, num

std dev):

try:

from trade

server import TradeServer

from market

server import MarketServer

trade = TradeServer.retrieve(trade

id, ’trades’)

env = MarketServer.retrieve(env

id, ’environments’)

model

args = {"num states": num states, "num std dev":

num

std dev}

factory = ppf.model.hull

white lattice model factory()

model = factory(trade, env, model

args)

pricer = ppf.pricer.lattice

pricer(trade, model, env, None)

PricerServer.

pricers[tag] = pricer

return tag

except RuntimeError, e: ppf.com.utils.raise

com exception(e)

def InvokePricer(self, tag):

try:

return PricerServer.retrieve(tag, ’pricers’).

call ()

except RuntimeError, e: utils.raise

com exception(e)

if

name == " main ": utils.register com class(PricerServer)

The explanations provided by the earlier sections should make the above code self-explanatory

rendering further comment unnecessary. Figure 12.6 shows an example session pricing a

Bermudan in an Excel session.

Pricer VBA Client

Here is the example client code for interfacing to the ‘ppf.pricer’ COM object. ...