Index
acceptable portfolios 23, 25–6
accumulated value 77–83
advanced measurement approach
(AMA) 2
calibration 12–16
aggregate desirability of a portfolio
29–30
Agrawal, D. 108
Akhavein, J. 109
α-stable distributions 146–50
α-stable intensity-based model
148–50
properties of the family 146–7
simulation 147–8
American Depository Receipts (ADRs)
305
Andersen, L. 354
Andersen, T.G. 115, 246
Andersson, E. 242
Andreasen, J. 354
approximations, models as 198
Aragó, V. 304
Aramov, D. 108
arbitrage models 92
ARCH models 48, 86–7
conditional volatility 89–91
ARCH test 306–7
Artzner, P. 22, 24–5, 27, 28
asymmetric covariance 328–9, 348,
349–50, 351
asymmetric dynamic covariance
(ADM) model 329–51
asymmetric volatility 328–9, 348,
349–50, 351
asymmetric volatility impulse response
function (AVIRF) 311–12, 317–21,
322, 323
asymmetrical information 283
asymmetries analysis 342–5
asymptotic MEWMA control charts
251, 253, 254–8
atomic simulation 165
augmented Dickey–Fuller (ADF) test
307
Australia 328
autocorrelation 339
autoregressive models 48
NPV probability distribution and
autoregressive cash flows 286–7,
288, 289–93, 297–301
average run lengths (ARLs) 247, 254,
255–8
average stock risk 108–9Bachelier, L. 194
backtesting 200
VaR models 214–17
backward-looking models 200
Balkema, A.A. 7
bankruptcy, probability of 283–4
Basel Committee on Banking
Supervision 1
Basel II framework 1–2, 8
basic indicator approach (BIA) 2
basic multivariate normal (BMVN)
method 161–8
accurate estimation of correlation
matrix 162–3
consistency between valuation of
single contracts and portfolios
166–7
dealing with non-normality 163–4
estimating model error 164
estimating sampling error 167
estimating VaR 167–8365