Optimizing Optimization: The Next Generation of Optimization Applications and Theory (Quantitative Finance)

Index 303

Global minimum variance (GMV) , 236
Grid-search (GS) procedure , 256 , 260

H
Heatmap representations
of tracking error
and sector bounds , 39
and turnover values , 37 , 42 , 44
Heuristic portfolio optimization, Bayesian
updating with Johnson family
distributions , 247
algorithm
maximization problem , 257 – 9
threshold acceptance , 260 – 1
alpha information , 262 – 5
brief history of , 248 – 50
data reweighting , 261 – 2
empirical application , 265
decay factor ρ , 266
disappointment aversion coeffi cient,
A , 268
non-Gaussianity, importance , 268 – 70
Johnson family , 251
basic properties , 251 – 4
density estimation , 254 – 6
parameters of , 272 – 3
random variates , 256 – 7
quantile estimator under
misspecifi cation , 275 – 8
threshold acceptance pseudocode ,
273 – 4
Z* optimality , 274 – 5
Hyperbolic absolute risk aversion
(HARA) , 257

I
Income and Substitution effects , 85
Index tracking , 56

J
Johnson family
basic properties , 251 – 4
bounded distribution , 251
density estimation , 254 – 6
lognormal distribution , 251
normal distribution , 251
parameters estimates of
S B distribution , 272 – 3
S L distribution , 273

S N distribution , 273

S U distribution , 272

random variates , 256 – 7

unbounded distribution , 251

K

Kalman fi lter and smoother (KFS) , 148 ,

150 , 155

L

Log-wealth utility function , 104

Lognormal cumulative distribution

function, formula for ,

174 – 5

Lognormal curve, formula for , 174

Lognormal distribution , 251

Loss aversion coeffi cient, determination

of , 76 – 7

M

Market portfolio , 131 , 132

Markowitz, Harry , 74 , 94 , 204

Maximization problem , 257 – 9

Maximum drawdown (MDD) ,

77 , 268

Mean forecast intervals, of BITA ,

65

Mean, meaning , 173

Mean – ES portfolio selection , 67 – 8

Mean – var portfolio selection , 67 – 8

Mean – variance (MV) analysis , 67 , 69 ,

132 , 179 , 201 , 225

BITA optimizer , 57 – 8

effi cient frontier , 96

and mean – EVaR allocation, difference

between , 157

reformulation of , 59 – 61

technical overview , 56 – 7

utility function , 74

Mean-absolute deviation (MAD) ,

292

Meta-Gaussian model , 248 , 263

Monte Carlo analysis , 112 , 156

based average methods , 225

Moore, Gordon , 247

Multigoal optimization, of WPA ,

93 , 94

problem , 94

WPA solution , 94 – 6