Risk and Asset Allocation

Front Cover
Springer Science & Business Media, Jun 12, 2007 - Business & Economics - 532 pages

This encyclopedic, detailed exposition spans all the steps of one-period allocation from the foundations to the most advanced developments.

Multivariate estimation methods are analyzed in depth, including non-parametric, maximum-likelihood under non-normal hypotheses, shrinkage, robust, and very general Bayesian techniques. Evaluation methods such as stochastic dominance, expected utility, value at risk and coherent measures are thoroughly discussed in a unified setting and applied in a variety of contexts, including prospect theory, total return and benchmark allocation.

Portfolio optimization is presented with emphasis on estimation risk, which is tackled by means of Bayesian, resampling and robust optimization techniques.

All the statistical and mathematical tools, such as copulas, location-dispersion ellipsoids, matrix-variate distributions, cone programming, are introduced from the basics. Comprehension is supported by a large number of figures and examples, as well as real trading and asset management case studies.

At symmys.com the reader will find freely downloadable complementary materials: the Exercise Book; a set of thoroughly documented MATLABŪ applications; and the Technical Appendices with all the proofs. More materials and complete reviews can also be found at symmys.com.

 

What people are saying - Write a review

User Review - Flag as inappropriate

Attilio Meucci (One day overlap at RVI.)

Contents

562 Building coherent indices
301
LXXVII
302
LXXVIII
303
563 Explicit dependence on allocation
305
LXXIX
306
61 The general approach
311
LXXX
313
613 Computing the optimal allocation
315

132 Normal distribution
24
133 Cauchy distribution
26
134 Student t distribution
28
136 Gamma distribution
32
XIII
34
XIV
38
Multivariate statistics
40
22 Factorization of a distribution
45
XVI
48
XVIII
50
XIX
54
242 Dispersion
57
XX
59
244 Higherorder statistics
64
XXII
67
XXIII
70
XXV
72
26 Taxonomy of distributions
77
XXVI
81
XXVII
82
263 Student t distribution
84
XXVIII
87
265 Logdistributions
89
266 Wishart distribution
91
268 Order statistics
96
27 Special classes of distributions
98
XXIX
101
XXX
103
XXXI
105
Modeling the market
109
XXXII
114
313 Derivatives
122
XXXIII
126
XXXV
129
XXXVI
131
XXXVII
133
XXXVIII
138
XXXIX
143
XL
145
XLI
147
XLII
150
343 Explicit vs hidden factors
151
XLIV
160
XLV
162
353 The invariants at the investment horizon
168
354 From invariants to prices
171
XLVI
172
XLVII
173
Estimating the distribution of the market invariants
178
411 Definition
181
XLVIII
184
XLIX
185
L
186
421 Location dispersion and hidden factors
190
LI
192
422 Explicit factors
193
LII
200
432 Explicit factors
201
LIII
204
44 Shrinkage estimators
209
LIV
211
LV
216
LVI
221
LVII
223
LIX
229
46 Practical tips
232
LX
234
LXII
235
LXIII
237
LXIV
239
464 Overlapping data
243
LXV
249
LXVI
260
LXVII
262
LXVIII
270
LXIX
274
LXX
276
LXXI
277
LXXII
278
LXXIII
282
544 Sensitivity analysis
285
551 Properties
287
LXXIV
288
LXXV
292
56 Coherent indices expected shortfall
296
LXXVI
298
LXXXI
316
LXXXII
319
62 Constrained optimization
320
LXXXIII
323
LXXXIV
326
LXXXV
327
LXXXVI
330
634 Meanvariance in terms of returns
332
64 Analytical solutions of the meanvariance problem
335
641 Efficient frontier with affine constraints
336
LXXXVII
338
LXXXVIII
340
LXXXIX
342
XC
343
652 MV as an index of satisfaction
347
XCI
354
XCII
355
XCIV
357
XCV
361
XCVI
364
671 Collecting information on the investor
366
XCVIII
369
XCIX
370
CI
373
712 Summarizing the posterior distribution
377
713 Computing the posterior distribution
380
CII
383
CIII
385
CIV
387
CV
389
CVI
390
74 Determining the prior
394
CVIII
397
81 Allocations as decisions
401
CIX
403
CXI
404
CXII
406
CXIII
407
813 Opportunity cost as loss of an estimator
408
814 Evaluation of a generic allocation decision
412
823 Discussion
417
83 Samplebased allocation
418
832 Evaluation
419
CXV
421
CXVI
422
CXVII
425
CXVIII
426
91 Bayesian allocation
429
913 Evaluation
433
914 Discussion
436
92 BlackLitterman allocation
437
CXX
438
linear expertise on normal markets
440
CXXI
443
CXXII
445
CXXV
450
CXXVI
453
933 Evaluation
454
CXXVII
455
CXXVIII
457
CXXIX
459
CXXX
463
951 General definition
468
CXXXII
469
the meanvariance setting
470
CXXXIII
471
953 Discussion
472
CXXXIV
474
CXXXVI
475
Linear algebra
478
CXXXVIII
480
A3 Linear transformations
482
A31 Matrix representation
483
A4 Invariants
485
A42 Trace
487
CXXXIX
490
A6 Matrix operations
493
CXL
494
A63 The vec and vech operators
496
CXLII
499
CXLIII
501
CXLIV
505
CXLV
514
CXLVI
519
CXLVII
525
Copyright

Other editions - View all

Common terms and phrases

Popular passages

Page 510 - Eq. (8-5), that the Fourier transform of the convolution of two functions is the product of the Fourier transforms of the individual functions; that is, ) (8-7) The inverse of Eq.
Page 34 - We recall that the x2 distribution with v degrees of freedom is defined as the distribution of the sum of squares of v mutually independent unit normal N(0,\) variables.

About the author (2007)

Attilio Meucci holds a BA summa cum laude in Physics and a PhD in Mathematics from the University of Milan, an MA in Economics from Bocconi University in Milan, and is CFA chartholder.

Attilio Meucci is a vice president at Lehman Brothers, Inc., New York, in the fixed-income research division. Previously, the author was a trader at Relative Value International, a hedge fund in Greenwich, CT that trades in equities and fixed-income securities worldwide. Previously, he was a consultant in the Milan office of Bain & Co., where he designed tools of personal financial planning, credit-and market-risk management, portfolio insurance, tactical and strategic asset allocation.

Attilio Meucci is the author of several publications in mathematics and finance and has taught graduate courses on Asset Allocation and Risk Management worldwide.