Efficient asset management: a practical guide to stock portfolio optimization and asset allocation
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Oxford University Press
[2008]
|
| Ausgabe: | second edition |
| Schriftenreihe: | Financial Management Association survey and synthesis series
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | xvi, 128 Seiten Diagramme 1 CD-ROM, 12 cm |
| ISBN: | 9780195331912 |
Internformat
MARC
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| 100 | 1 | |a Michaud, Richard O. |e Verfasser |0 (DE-588)1031928782 |4 aut | |
| 245 | 1 | 0 | |a Efficient asset management |b a practical guide to stock portfolio optimization and asset allocation |c by Richard O. Michaud and Robert O. Michaud |
| 250 | |a second edition | ||
| 264 | 1 | |a New York [u.a.] |b Oxford University Press |c [2008] | |
| 264 | 4 | |c © 2008 | |
| 300 | |a xvi, 128 Seiten |b Diagramme |e 1 CD-ROM, 12 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 490 | 0 | |a Financial Management Association survey and synthesis series | |
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Datensatz im Suchindex
| _version_ | 1804137353240903680 |
|---|---|
| adam_text | Contents
1
Introduction
3
Markowitz
Efficiency
3
An Asset Management Tool
4
Traditional Objections
5
The Most Important Limitations
5
Resolving the Limitations of Mean-Variance
Optimization
6
Illustrating the Techniques
6
2
Classic Mean-Variance Optimization
7
Portfolio Risk and Return
7
Defining
Markowitz
Efficiency
9
Optimization Constraints
9
The Residual Risk-Return Efficient Frontier
10
Computer Algorithms
10
Asset Allocation Versus Equity Portfolio Optimization
11
A Global Asset Allocation Example
13
Reference Portfolios and Portfolio Analysis
14
Return Premium Efficient Frontiers
16
Appendix: Mathematical Formulation of
MV
Efficiency
17
3
Traditional Criticisms and Alternatives
20
Alternative Measures of Risk
20
Utility
Function Optimization
22
Multiperiod Investment Horizons
23
Asset-Liability Financial Planning Studies
25
Linear Programming Optimization
27
4
Unbounded
MV
Portfolio Efficiency
29
Unbounded
MV
Optimization
30
The Fundamental Limitations of Unbounded
MV
Efficiency
31
Repeating Jobson and Korkie
32
Implications of Jobson and Korkie Analysis
33
Statistical
MV
Efficiency and Implications
34
5
Linear Constrained
MV
Efficiency
35
Linear Constraints
35
Efficient Frontier Variance
37
Rank-Associated Efficient Portfolios
39
How Practical an Investment Tool?
40
6
The Resampled Efficient Frontier™
42
Efficient Frontier Statistical Analysis
42
Properties of Resampled Efficient Frontier Portfolios
45
True and Estimated Optimization Inputs
47
Simulation Proofs of Resampled Efficiency Optimization
48
Why Does It Work
51
Certainty Level and RE Optimality
51
FC
Level Applications
52
The
REF
Maximum Return Point (MRP)
53
Implications for Asset Management
55
Conclusion
55
Appendix A: Rank- Versus
λ
-Associated
RE Portfolios
56
Appendix B: Robert s Hedgehog
57
7
Portfolio Rebalancing, Analysis, and Monitoring
60
Resampled Efficiency and Distance Functions
61
Portfolio Need-to-Trade Probability
62
Meta-Resampling Portfolio Rebalancing
63
Portfolio Monitoring and Analysis
64
Conclusion
66
Appendix:
Confidence
Region
for the Sample
Mean Vector
66
8
Input Estimation and Stein Estimators
68
Admissible Estimators
69
Bayesian Procedures and Priors
69
Four Stein Estimators
70
James-Stein Estimator
70
James-Stein
MV
Efficiency
71
Out-of-Sample James-Stein Estimation
72
Frost-Savarino Estimator
73
Covariance Estimation
74
Stein Covariance Estimation
76
Utility Functions and Input Estimation
77
Ad Hoc Estimators
77
Stein Estimation Caveats
78
Conclusions
78
Appendix: Ledoit Covariance Estimation
78
9
Benchmark Mean-Variance Optimization
80
Benchmark-Relative Optimization Characteristics
80
Tracking Error Optimization and Constraints
81
Constraint Alternatives
83
Roll s Analysis
85
Index Efficiency
85
A Simple Benchmark-Relative Framework
86
Long-Short Investing
86
Conclusion
88
10
Investment Policy and Economic Liabilities
89
Misusing Optimization
90
Economic Liability Models
90
Endowment Fund Investment Policy
91
Pension Liabilities and Benchmark Optimization
92
Limitations of Actuarial Liability Estimation
92
Current Pension Liabilities
93
Total and Variable Pension Liabilities
93
Economic Significance of Variable Liabilities
94
Economic Characteristics of
VBO
Liabilities
95
An Example: Economic Liability Pension
Investment Policy
96
Past and Future of Defined Benefit Pension Plans
98
Conclusion
99
11
Bayes
and Active Return Estimation
101
Current Practices
102
Bayes
Principles
102
The
Bayes
Return Formula
102
A Bayes
Panel Illustration
103
Bayesian Mixed Estimation Issues
104
Enhanced Inputs or Enhanced Optimizer
106
Bayesian Caveats
107
12
Avoiding Optimization Errors
109
Scaling Inputs
109
Financial Reality 111
Liquidity Factors 111
Practical Constraint Issues
112
Biased Portfolio Characteristics
112
Index Funds and Optimizers
113
Optimization from Cash
114
Forecast Return Limitations
115
Conclusion
116
Epilogue
117
Bibliography
119
Index
125
L
.n spite
of theoretical benefits,
Markowitz
mean-
variance
(MV)
optimized portfolios often fail to
meet practical investment goals of marketability,
usability, and performance, prompting many
investors to seek simpler alternatives. Financial
experts Richard and Robert Michaud demonstrate
that the limitations of
MV
optimization are not
the result of conceptual flaws in
Markowitz
theory
f
but of the unrealistic representation of investment
information. What is missing is a realistic treat¬
ment of estimation error in the optimization and
rebalancing process.
The text provides a non-technical review of
classical
Markowitz
optimization and traditional
objections. The authors demonstrate that in prac¬
tice the single most important limitation of
MV
optimization is oversensitivity to estimation error.
Portfolio optimization requires a modern statisti¬
cal perspective. Efficient Asset Management, Second
Edition uses Monte Carlo resampling to address
information uncertainty and define Resampled
Efficiency (RE) technology. RE optimized portfo¬
lios represent a new definition of portfolio opti-
mality that is more investment intuitive, robust,
and
provably
investment effective. RE rebalancing
provides the first rigorous portfolio trading, mon¬
itoring, and asset importance rules, avoiding wide¬
spread ad hoc methods in current practice.
The second edition resolves several open
issues and misunderstandings that have emerged
since the original edition. The new edition includes
new proofs of effectiveness, substantial revisions of
statistical estimation, extensive discussion of long-
short optimization, and new tools for dealing with
estimation error in applications and enhancing
computational efficiency. RE optimization is
shown to be a Bayesian-based generalization and
enhancement of Markowitz s solution. RE technol¬
ogy corrects many current practices that may
adversely impact the investment value of trillions
of dollars under current asset management. RE
optimization technology may also be useful in
other financial optimizations and more generally
in multivariate estimation contexts of information
uncertainty with Bayesian linear constraints.
Michaud and Michaud s new book includes
numerous additional proposals to enhance invest¬
ment value, including Stein and Bayesian methods
for improved input estimation, the use of port¬
folio priors, and an economic perspective for
asset-liability optimization. Applications include
investment policy, asset allocation, and equity
portfolio optimization. A final chapter includes
practical advice for avoiding simple portfolio
design errors.
A simple global asset allocation problem
illustrates portfolio optimization techniques. The
presentation is intuitive, rigorous, and informed
with institutional management experience to
appeal to investment management executives,
consultants, fund trustees, brokers, academics, and
anyone seeking to stay abreast of the future of
investment technology.
With its important implications for invest¬
ment practice, Efficient Asset Management s highly
intuitive yet rigorous approach to defining optimal
portfolios will appeal to investment management
executives, consultants, brokers, and anyone seeking
to stay abreast of current investment technology.
Through practical examples and illustrations,
Michaud and Michaud update the practice of opti¬
mization for modern investment management.
|
| adam_txt |
Contents
1
Introduction
3
Markowitz
Efficiency
3
An Asset Management Tool
4
Traditional Objections
5
The Most Important Limitations
5
Resolving the Limitations of Mean-Variance
Optimization
6
Illustrating the Techniques
6
2
Classic Mean-Variance Optimization
7
Portfolio Risk and Return
7
Defining
Markowitz
Efficiency
9
Optimization Constraints
9
The Residual Risk-Return Efficient Frontier
10
Computer Algorithms
10
Asset Allocation Versus Equity Portfolio Optimization
11
A Global Asset Allocation Example
13
Reference Portfolios and Portfolio Analysis
14
Return Premium Efficient Frontiers
16
Appendix: Mathematical Formulation of
MV
Efficiency
17
3
Traditional Criticisms and Alternatives
20
Alternative Measures of Risk
20
Utility
Function Optimization
22
Multiperiod Investment Horizons
23
Asset-Liability Financial Planning Studies
25
Linear Programming Optimization
27
4
Unbounded
MV
Portfolio Efficiency
29
Unbounded
MV
Optimization
30
The Fundamental Limitations of Unbounded
MV
Efficiency
31
Repeating Jobson and Korkie
32
Implications of Jobson and Korkie Analysis
33
Statistical
MV
Efficiency and Implications
34
5
Linear Constrained
MV
Efficiency
35
Linear Constraints
35
Efficient Frontier Variance
37
Rank-Associated Efficient Portfolios
39
How Practical an Investment Tool?
40
6
The Resampled Efficient Frontier™
42
Efficient Frontier Statistical Analysis
42
Properties of Resampled Efficient Frontier Portfolios
45
True and Estimated Optimization Inputs
47
Simulation Proofs of Resampled Efficiency Optimization
48
Why Does It Work
51
Certainty Level and RE Optimality
51
FC
Level Applications
52
The
REF
Maximum Return Point (MRP)
53
Implications for Asset Management
55
Conclusion
55
Appendix A: Rank- Versus
λ
-Associated
RE Portfolios
56
Appendix B: Robert's Hedgehog
57
7
Portfolio Rebalancing, Analysis, and Monitoring
60
Resampled Efficiency and Distance Functions
61
Portfolio Need-to-Trade Probability
62
Meta-Resampling Portfolio Rebalancing
63
Portfolio Monitoring and Analysis
64
Conclusion
66
Appendix:
Confidence
Region
for the Sample
Mean Vector
66
8
Input Estimation and Stein Estimators
68
Admissible Estimators
69
Bayesian Procedures and Priors
69
Four Stein Estimators
70
James-Stein Estimator
70
James-Stein
MV
Efficiency
71
Out-of-Sample James-Stein Estimation
72
Frost-Savarino Estimator
73
Covariance Estimation
74
Stein Covariance Estimation
76
Utility Functions and Input Estimation
77
Ad Hoc Estimators
77
Stein Estimation Caveats
78
Conclusions
78
Appendix: Ledoit Covariance Estimation
78
9
Benchmark Mean-Variance Optimization
80
Benchmark-Relative Optimization Characteristics
80
Tracking Error Optimization and Constraints
81
Constraint Alternatives
83
Roll's Analysis
85
Index Efficiency
85
A Simple Benchmark-Relative Framework
86
Long-Short Investing
86
Conclusion
88
10
Investment Policy and Economic Liabilities
89
Misusing Optimization
90
Economic Liability Models
90
Endowment Fund Investment Policy
91
Pension Liabilities and Benchmark Optimization
92
Limitations of Actuarial Liability Estimation
92
Current Pension Liabilities
93
Total and Variable Pension Liabilities
93
Economic Significance of Variable Liabilities
94
Economic Characteristics of
VBO
Liabilities
95
An Example: Economic Liability Pension
Investment Policy
96
Past and Future of Defined Benefit Pension Plans
98
Conclusion
99
11
Bayes
and Active Return Estimation
101
Current Practices
102
Bayes
Principles
102
The
Bayes
Return Formula
102
A Bayes
Panel Illustration
103
Bayesian Mixed Estimation Issues
104
Enhanced Inputs or Enhanced Optimizer
106
Bayesian Caveats
107
12
Avoiding Optimization Errors
109
Scaling Inputs
109
Financial Reality 111
Liquidity Factors 111
Practical Constraint Issues
112
Biased Portfolio Characteristics
112
Index Funds and Optimizers
113
Optimization from Cash
114
Forecast Return Limitations
115
Conclusion
116
Epilogue
117
Bibliography
119
Index
125
L
.n spite
of theoretical benefits,
Markowitz
mean-
variance
(MV)
optimized portfolios often fail to
meet practical investment goals of marketability,
usability, and performance, prompting many
investors to seek simpler alternatives. Financial
experts Richard and Robert Michaud demonstrate
that the limitations of
MV
optimization are not
the result of conceptual flaws in
Markowitz
theory
f
but of the unrealistic representation of investment
information. What is missing is a realistic treat¬
ment of estimation error in the optimization and
rebalancing process.
The text provides a non-technical review of
classical
Markowitz
optimization and traditional
objections. The authors demonstrate that in prac¬
tice the single most important limitation of
MV
optimization is oversensitivity to estimation error.
Portfolio optimization requires a modern statisti¬
cal perspective. Efficient Asset Management, Second
Edition uses Monte Carlo resampling to address
information uncertainty and define Resampled
Efficiency (RE) technology. RE optimized portfo¬
lios represent a new definition of portfolio opti-
mality that is more investment intuitive, robust,
and
provably
investment effective. RE rebalancing
provides the first rigorous portfolio trading, mon¬
itoring, and asset importance rules, avoiding wide¬
spread ad hoc methods in current practice.
The second edition resolves several open
issues and misunderstandings that have emerged
since the original edition. The new edition includes
new proofs of effectiveness, substantial revisions of
statistical estimation, extensive discussion of long-
short optimization, and new tools for dealing with
estimation error in applications and enhancing
computational efficiency. RE optimization is
shown to be a Bayesian-based generalization and
enhancement of Markowitz's solution. RE technol¬
ogy corrects many current practices that may
adversely impact the investment value of trillions
of dollars under current asset management. RE
optimization technology may also be useful in
other financial optimizations and more generally
in multivariate estimation contexts of information
uncertainty with Bayesian linear constraints.
Michaud and Michaud's new book includes
numerous additional proposals to enhance invest¬
ment value, including Stein and Bayesian methods
for improved input estimation, the use of port¬
folio priors, and an economic perspective for
asset-liability optimization. Applications include
investment policy, asset allocation, and equity
portfolio optimization. A final chapter includes
practical advice for avoiding simple portfolio
design errors.
A simple global asset allocation problem
illustrates portfolio optimization techniques. The
presentation is intuitive, rigorous, and informed
with institutional management experience to
appeal to investment management executives,
consultants, fund trustees, brokers, academics, and
anyone seeking to stay abreast of the future of
investment technology.
With its important implications for invest¬
ment practice, Efficient Asset Management's highly
intuitive yet rigorous approach to defining optimal
portfolios will appeal to investment management
executives, consultants, brokers, and anyone seeking
to stay abreast of current investment technology.
Through practical examples and illustrations,
Michaud and Michaud update the practice of opti¬
mization for modern investment management. |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Michaud, Richard O. Michaud, Robert O. |
| author_GND | (DE-588)1031928782 |
| author_facet | Michaud, Richard O. Michaud, Robert O. |
| author_role | aut aut |
| author_sort | Michaud, Richard O. |
| author_variant | r o m ro rom r o m ro rom |
| building | Verbundindex |
| bvnumber | BV023097191 |
| callnumber-first | H - Social Science |
| callnumber-label | HG4529 |
| callnumber-raw | HG4529 |
| callnumber-search | HG4529 |
| callnumber-sort | HG 44529 |
| callnumber-subject | HG - Finance |
| classification_rvk | QK 530 QK 810 |
| classification_tum | WIR 160f |
| ctrlnum | (OCoLC)138339873 (DE-599)BVBBV023097191 |
| dewey-full | 332.6 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.6 |
| dewey-search | 332.6 |
| dewey-sort | 3332.6 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | second edition |
| format | Book |
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| id | DE-604.BV023097191 |
| illustrated | Not Illustrated |
| index_date | 2024-07-02T19:43:25Z |
| indexdate | 2024-07-09T21:10:57Z |
| institution | BVB |
| isbn | 9780195331912 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016299972 |
| oclc_num | 138339873 |
| open_access_boolean | |
| owner | DE-739 DE-355 DE-BY-UBR DE-945 |
| owner_facet | DE-739 DE-355 DE-BY-UBR DE-945 |
| physical | xvi, 128 Seiten Diagramme 1 CD-ROM, 12 cm |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Oxford University Press |
| record_format | marc |
| series2 | Financial Management Association survey and synthesis series |
| spelling | Michaud, Richard O. Verfasser (DE-588)1031928782 aut Efficient asset management a practical guide to stock portfolio optimization and asset allocation by Richard O. Michaud and Robert O. Michaud second edition New York [u.a.] Oxford University Press [2008] © 2008 xvi, 128 Seiten Diagramme 1 CD-ROM, 12 cm txt rdacontent n rdamedia nc rdacarrier Financial Management Association survey and synthesis series Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Portfolio Selection (DE-588)4046834-3 gnd rswk-swf Finanzanalyse (DE-588)4133000-6 gnd rswk-swf Finanzanalyse (DE-588)4133000-6 s Mathematisches Modell (DE-588)4114528-8 s DE-604 Portfolio Selection (DE-588)4046834-3 s Michaud, Robert O. Verfasser aut Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016299972&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016299972&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Michaud, Richard O. Michaud, Robert O. Efficient asset management a practical guide to stock portfolio optimization and asset allocation Mathematisches Modell (DE-588)4114528-8 gnd Portfolio Selection (DE-588)4046834-3 gnd Finanzanalyse (DE-588)4133000-6 gnd |
| subject_GND | (DE-588)4114528-8 (DE-588)4046834-3 (DE-588)4133000-6 |
| title | Efficient asset management a practical guide to stock portfolio optimization and asset allocation |
| title_auth | Efficient asset management a practical guide to stock portfolio optimization and asset allocation |
| title_exact_search | Efficient asset management a practical guide to stock portfolio optimization and asset allocation |
| title_exact_search_txtP | Efficient asset management a practical guide to stock portfolio optimization and asset allocation |
| title_full | Efficient asset management a practical guide to stock portfolio optimization and asset allocation by Richard O. Michaud and Robert O. Michaud |
| title_fullStr | Efficient asset management a practical guide to stock portfolio optimization and asset allocation by Richard O. Michaud and Robert O. Michaud |
| title_full_unstemmed | Efficient asset management a practical guide to stock portfolio optimization and asset allocation by Richard O. Michaud and Robert O. Michaud |
| title_short | Efficient asset management |
| title_sort | efficient asset management a practical guide to stock portfolio optimization and asset allocation |
| title_sub | a practical guide to stock portfolio optimization and asset allocation |
| topic | Mathematisches Modell (DE-588)4114528-8 gnd Portfolio Selection (DE-588)4046834-3 gnd Finanzanalyse (DE-588)4133000-6 gnd |
| topic_facet | Mathematisches Modell Portfolio Selection Finanzanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016299972&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016299972&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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