Financial Modelling in Python

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