Financial Modelling in Python

P1: JYS

c06 JWBK378-Fletcher May 12, 2009 18:55 Printer: Yet to come

88 Financial Modelling in Python

self. legs = legs

self.

exercise info = exercise info

def legs(self):

return self.

legs

def exercise

type(self):

if not self.

exercise info:

raise RuntimeError, "missing exercise information"

return self.

exercise info[1]

def exercise

schedule(self):

if not self.

exercise info:

raise RuntimeError, "missing exercise information"

return self.

exercise info[0]

def has

exercise schedule(self):

return self.

exercise schedule != None

The following snippet shows a simple example of how to assemble a trade:

>>> #semi-annual flows

>>> flows = generate

flows(

... start = date(2007, Jun, 29)

... , end = date(2017, Jun, 29)

... , duration = ppf.date

time.months

... , period = 6

... , shift

method = shift convention.modified following

... , basis = "ACT/360")

>>> pay

leg = leg(flows, PAY)

>>> receive

leg = leg(flows, RECEIVE)

>>> #1y nc

>>> ex

sched = generate exercise table(

... start = date(2008, Jun, 29)

... , end = date(2016, Jun, 29)

... , period = 1

... , duration = ppf.date

time.years

... , shift

method = shift convention.modified following)

>>> structure = trade([pay

leg, receive leg], [ex sched, \

exercise

type.callable])

>>> print ("callable", "cancellable")[structure.exercise

type()

== -1]

callable

6.7 TRADE UTILITIES

It is not uncommon to perform standard operations on the trade representation. For example,

the writer of a pricing model