May 2014
Intermediate to advanced
688 pages
17h 47m
English
book
Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics
by Paolo Brandimarte
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Index
absolute loss
acceptance–rejection
ACF, see autocorrelation, function
action (in dynamic programming)
additive model
ADP, see dynamic programming, approximate
antithetic sampling
APT, see arbitrage pricing theory
AR, see autoregressive
arbitrage
opportunity
pricing theory
arc (in a network)
ARCH
model
ARIMA
ARMA
asset pricing
asset–liability management
association, linear
autocorrelation
function
sample
partial, see partial autocorrelation
autocorrelogram
autocovariance
autoregressive
conditionally heteroskedastic, see ARCH
integrated moving-average, see ARIMA
model
moving-average, see ARMA
process
backshift operator
balance condition for Markov chains
detailed
global
bandwidth
barrier option, see option, barrier
basis
function
of a lattice
batch method
batching
Bayes’ theorem
Bayesian
computational statistics
estimation
parameter estimation
statistics
view
bequest, utility from
Bernoulli
random variable
trial
beta
distribution
function
variate generation
bias
big-M constraint
binomial
coefficient
distribution
lattice
model
random variable
black swan
Black–Scholes–Merton formula
partial differential equation
world
Boltzmann constant
bond
bootstrap
bootstrapping
bond yields
Box–Jenkins model
Box–Muller method
branching factor
Brownian bridge
BSM, see Black–Scholes–Merton
Buffon’s needle
burn-in
càdlàg function
capital asset pricing model
CAPM, see capital asset pricing model
cardinality constraint
Cartesian product
CDF, see cumulative distribution function
central limit ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.