P1: JYS
Ind JWBK378-Fletcher May 23, 2009 6:5 Printer: Yet to come
232 Index
PPF GenerateFixedCoupon
Observables 182
PPF
GenerateFlows 184–5
PPF
GenerateLiborObservables
182–3
ppf.market... 63–7, 101–22, 169–76
ppf.math... 2–3, 6–9, 17–19, 23–6, 28–9,
31–4, 35–7, 40–1, 44–9, 50–61, 100–22,
132–42, 170–6, 205
ppf
math.pyd 23
ppf.model... 97–8, 100–22, 124–8, 129–42,
146–57
ppf.pricer 6, 134–42, 145–52, 176–87,
188–9
ppf.test... 6–7, 9, 17–19, 59–61, 64–7,
109–22, 148–57
ppf.utility... 6–7, 29–61, 64–7
pricer 6, 134–42, 145–52, 176–89
pricer server, COM servers 187–9
pricer VBA client 188–9
PricerServer 187–9
pricer
server 187–9
pricing models 3–4, 5–9, 28–9, 49–51, 61, 65–7,
99–122, 123–43, 145–57, 165–89, 217–18,
219–20
see also controller; events
analytic/semi-analytic pricing formulae 99
approaches 3–4, 99, 108–9, 123–43,
145–57
Bermudan swaptions 4, 101–2, 115–16,
126–8, 132–42, 145–52, 157, 168–89
Black–Scholes option pricing formula 5–9,
28–9, 111–22, 165–8
C++/Python ‘Hybrid Systems’ 4, 159–63
classes 3
Hull–White model 3–4, 6, 65–7, 99–122,
145–57, 168–89, 217–18
lattice-based pricing framework 3, 6, 49–51,
67, 99, 101–22, 123–31, 142–3, 149–52,
168–89
Microsoft Excel 165–89
Monte-Carlo simulations 3, 4, 6, 99, 101–2,
108–22, 123, 128–43, 150–7, 219–20
numerical techniques 99–122, 123–43,
145–57, 168–89
path-dependency issues 99, 123–43, 157
TARNs 4, 101–2, 145, 152–7
pricing
date 66–7, 96–8, 125–8
productivity benefits of Python 1
proj
basis 71–9, 105–22
projection periods
see also proj...
LIBOR rate 70–9, 105–22
proj
end date 71–9, 105–22
proj
roll 73–9
proj
start date 71–9, 105–22
pseudo random number generation, concepts 3,
27–8
public
methods 169–76, 177–87, 188–9
put options 5–9
see also options
pv 77, 106–22, 126–8, 131–42, 148–57
‘py’ file suffix 194, 203–5
PyArray... 20–6
PyArray
Check 21–6
PyArray
ContiguousFromObject
21–6
PyArray
DOUBLE 22–6
PyArrayObject 20–6
Py
DECREF 20–1
PyErr
SetString 21–6
Py
Finalize 214–15
Py
Initialize 162–3, 214–15
PyObject 20–6, 215
Python
see also ActiveState...; Boost...; mathematics;
NumPy; ppf package
basics 193–205
batch interpreter mode 193–4
benefits 1–4
built-in data types 1, 195–7
C++/Python ‘Hybrid Systems’ 4, 159–63
C API routines 19–26, 161–3
C/C++ interoperability benefits 2, 3–4, 7–9,
11–26, 157
class basics 2–3, 201–3
COM servers 4, 5–6, 98, 165–89
concepts 1–4, 193–205
control flow statements 197–200
dictionaries 119–22, 181, 196–7, 215–16
dynamic type system 2–3
encapsulation support 2–3, 58–61, 209
expressiveness aspects 1
extensibility aspects 1–4, 7–9, 11–26
financial engineering 1–4, 11–26
function basics 2–3, 200–1
functional programming idioms 1
GUI toolkits 2
high-level aspects 1
indented code 198–200
inheritance basics 122, 202–3, 209–11
interactive interpreter mode 193–4
interoperability aspects 1–4, 7–9, 11–26, 157
interpreters 2, 24–6, 45–6, 193–4, 208–9
list basics 3, 196–7, 215
Microsoft Excel 4, 165–89
misconceptions 2–3
module basics 203–5
overview of the book 3–4
package basics 1, 203–5
productivity benefits 1
simple expressions 194–5

Get Financial Modelling in Python now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.