Decision making in financial markets: development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Hamburg
Kovač
2009
|
| Schriftenreihe: | Schriftenreihe Finanzmanagement
61 |
| Schlagworte: | |
| Online-Zugang: | Ausführliche Beschreibung Inhaltsverzeichnis |
| Beschreibung: | XXIV, 508 S. graph. Darst. |
| ISBN: | 9783830042150 |
Internformat
MARC
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| 100 | 1 | |a Lampenius, Niklas |e Verfasser |0 (DE-588)137611285 |4 aut | |
| 245 | 1 | 0 | |a Decision making in financial markets |b development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation |c Niklas Lampenius |
| 264 | 1 | |a Hamburg |b Kovač |c 2009 | |
| 300 | |a XXIV, 508 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Schriftenreihe Finanzmanagement |v 61 | |
| 502 | |a Zugl.: Neubiberg, Univ. der Bundeswehr München, Diss., 2008 | ||
| 650 | 7 | |a Agent-based Model |2 stw | |
| 650 | 7 | |a Aktienmarkt |2 stw | |
| 650 | 7 | |a Börsenkurs |2 stw | |
| 650 | 4 | |a Entscheidungsfindung - Kapitalmarkt | |
| 650 | 7 | |a Evolutionärer Algorithmus |2 stw | |
| 650 | 7 | |a Simulation |2 stw | |
| 650 | 7 | |a Theorie |2 stw | |
| 650 | 7 | |a Verhaltensökonomik |2 stw | |
| 650 | 0 | 7 | |a Kapitalmarkt |0 (DE-588)4029578-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Entscheidungsfindung |0 (DE-588)4113446-1 |2 gnd |9 rswk-swf |
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| 689 | 0 | 0 | |a Entscheidungsfindung |0 (DE-588)4113446-1 |D s |
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| 830 | 0 | |a Schriftenreihe Finanzmanagement |v 61 |w (DE-604)BV013087358 |9 61 | |
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| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017149566&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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Datensatz im Suchindex
| _version_ | 1804138663525744640 |
|---|---|
| adam_text | Table of content
I. Introduction and motivation of the topic
...............................................1
A. Introduction
...........................................................................................1
B. Scientific orientation and approach
..................................................16
C. Further structure
..................................................................................22
II. Decision making from an economic point of view
.............................23
A. Decision
makingin
the presence of risk
..........................................24
1.
Expected utility theory
....................................................................24
a. Criticism regarding the axioms of expected utility
.................34
b. Famous paradigms deviating from expected utility
...............37
i.
Allais
paradox
...........................................................................37
ii.
Ellsberg
paradox
......................................................................41
iii.
Comments about the discussed anomalies
..........................43
с
Commonly assumed utility functions and some empirical
evidence
.........................................................................................45
2.
Non-expected utility theories
/
generalized expected utility
theories
..............................................................................................58
a. Prospect theory
............................................................................61
b. Reference point in prospect theory
..........................................76
B. Concluding remarks
............................................................................82
III. Decision making from a behavioral point of view
..............................85
A. Systematic biases in human decision making
..................................87
1.
Systematic cognitive biases
............................................................87
2.
Systematic judgmental biases
.........................................................93
a. Framing effect
..............................................................................93
b. Overconfidence, optimism bias, and the illusion of
control
.........................................................................................101
с
Hindsight bias
............................................................................106
B. Documented behavioral anomalies for economic settings
.........113
1.
Loss aversion and the endowment effect
..................................113
2.
Status quo bias, omission bias, and regret aversion
.................119
3.
Mental accounting
.........................................................................126
4.
Disposition effect
..........................................................................132
5.
Herding
...........................................................................................139
a. Individual investors
...................................................................143
b. Institutional investors
...............................................................147
VI Table of content
с.
Analysts
.......................................................................................151
6.
Overconfidence in financial markets
..........................................152
7.
Under/overreaction
......................................................................162
8.
Myopic loss aversion
.....................................................................168
9.
Winners curse
.................................................................................172
10.
Sunk cost effect
..............................................................................174
С
Expert and laymen decisions
...........................................................176
D. Implications for the stock market simulation and concluding
remarks
................................................................................................181
IV. Computer aided simulation
...................................................................189
A. Algorithms that replicate human behavior
....................................189
1.
Machine learning as proxy for individual learning in
financial markets
............................................................................195
a. Various potential learning algorithms
....................................196
b. Selection of a proper algorithm
...............................................201
с
Genetic algorithms: Technical details
.....................................204
i. Goodness of fit
......................................................................205
ii. Selection and reproduction
..................................................206
iii.
Genetic operators
..................................................................211
iv.
Replacement of the parental generation
............................212
v. Particular application using GAs: The classifier system..
213
d. Genetic algorithms: Properties when applied to an
economic context
......................................................................215
e. Concluding remarks
..................................................................233
2.
Cellular automata as proxy for social learning
..........................235
B. Financial market simulations
...........................................................242
1.
Conceptual issues when designing financial market
simulations
......................................................................................243
a. Agent related design
..................................................................244
b. Market related design
................................................................253
2.
Review of the simulation literature
.............................................255
a. Santa Fe Institute Simulation
...................................................255
i. Market structure
....................................................................255
ii. Agent design.....
......................................................................260
iii.
Condition/forecast classifier system
..................................261
iv.
Learning algorithm
................................................................265
v. Simulation results
..................................................................269
Table of content
VII
vi. Conceptual
problems of the Santa Fe Institute
Simulation
...............................................................................274
b. Alternative forms of market simulations
...............................278
3.
Shortfall of existing simulations
..................................................300
С
Concluding remarks and motivation of the simulation
...............302
V. Simulation design
....................................................................................305
A. Design of the market
........................................................................307
1.
Market rules and regulations
........................................................307
2.
Pricing process
...............................................................................315
a. Individual demand function
.....................................................315
b. Establishment of an equilibrium price
...................................317
с
Properties of the market and the demand function
.............321
d. Fundamental value
....................................................................325
e. Return and monetary status
.....................................................326
B. Design of the agents: Individual and social learning
....................328
1.
Individual learning: Input variables for the genetic
algorithm
.........................................................................................328
a. News
............................................................................................329
b. Fundamental value
....................................................................331
с
Social learning
............................................................................331
d. Charting
.......................................................................................333
2.
Social learning: Cellular automaton applied to the agent-
based model
....................................................................................333
a. Design of the cellular automaton
............................................334
b. Agent specifications
..................................................................336
с
Communication amongst agents
.............................................345
3.
Implementation of the genetic algorithm
..................................346
C. Design of the agents: Behavioral model
........................................355
1.
Risk-aversion
..................................................................................356
2.
Overconfidence
.............................................................................359
3.
Disposition effect
..........................................................................364
D. Concluding remarks
........................................................,.................367
VI. Methods and simulation results
............................................................369
A. Methods
..............................................................................................369
1.
Theoretically expected properties of stock prices
....................369
2.
Empirically observed properties of stock prices
......................375
a. Heavy-tailed asset return distribution
....................................381
VIII Table of content
b.
Testing for the random walk hypothesis
...............................389
с
Testing for memory effects
......................................................400
3.
Concluding remarks
......................................................................404
B. Simulation results
...............................................................................405
1.
Rational scenarios
..........................................................................410
2.
Complex behavioral scenarios
.....................................................422
a. Comparison of the all-horizon, short-horizon, and long-
horizon scenarios
.......................................................................424
b. Analysis of a particular all-horizon scenario
.........................440
3.
Individual agent learning properties for the complex
behavioral scenario
........................................................................446
4.
Interpretation and summary of the simulation results
............456
VII.
Conclusion and outlook
...................................................................459
VIII.
Appendix
.........................................................................................467
IX.
literatúr
....................................................................................................475
|
| any_adam_object | 1 |
| author | Lampenius, Niklas |
| author_GND | (DE-588)137611285 |
| author_facet | Lampenius, Niklas |
| author_role | aut |
| author_sort | Lampenius, Niklas |
| author_variant | n l nl |
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| bvnumber | BV035345332 |
| classification_rvk | QK 620 |
| ctrlnum | (OCoLC)551910436 (DE-599)DNB992643058 |
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| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.40322 658.403 |
| dewey-search | 658.40322 658.403 |
| dewey-sort | 3658.40322 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Thesis Book |
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| id | DE-604.BV035345332 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:31:46Z |
| institution | BVB |
| isbn | 9783830042150 |
| language | English |
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| physical | XXIV, 508 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
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| publisher | Kovač |
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| series | Schriftenreihe Finanzmanagement |
| series2 | Schriftenreihe Finanzmanagement |
| spelling | Lampenius, Niklas Verfasser (DE-588)137611285 aut Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation Niklas Lampenius Hamburg Kovač 2009 XXIV, 508 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Schriftenreihe Finanzmanagement 61 Zugl.: Neubiberg, Univ. der Bundeswehr München, Diss., 2008 Agent-based Model stw Aktienmarkt stw Börsenkurs stw Entscheidungsfindung - Kapitalmarkt Evolutionärer Algorithmus stw Simulation stw Theorie stw Verhaltensökonomik stw Kapitalmarkt (DE-588)4029578-3 gnd rswk-swf Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Entscheidungsfindung (DE-588)4113446-1 s Kapitalmarkt (DE-588)4029578-3 s DE-604 Schriftenreihe Finanzmanagement 61 (DE-604)BV013087358 61 text/html http://www.verlagdrkovac.de/978-3-8300-4215-0.htm Ausführliche Beschreibung Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017149566&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Lampenius, Niklas Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation Schriftenreihe Finanzmanagement Agent-based Model stw Aktienmarkt stw Börsenkurs stw Entscheidungsfindung - Kapitalmarkt Evolutionärer Algorithmus stw Simulation stw Theorie stw Verhaltensökonomik stw Kapitalmarkt (DE-588)4029578-3 gnd Entscheidungsfindung (DE-588)4113446-1 gnd |
| subject_GND | (DE-588)4029578-3 (DE-588)4113446-1 (DE-588)4113937-9 |
| title | Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation |
| title_auth | Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation |
| title_exact_search | Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation |
| title_full | Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation Niklas Lampenius |
| title_fullStr | Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation Niklas Lampenius |
| title_full_unstemmed | Decision making in financial markets development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation Niklas Lampenius |
| title_short | Decision making in financial markets |
| title_sort | decision making in financial markets development and validation of a behavioral model utilizing a multi agent multi period stock market simulation |
| title_sub | development and validation of a behavioral model utilizing a multi-agent-multi-period stock market simulation |
| topic | Agent-based Model stw Aktienmarkt stw Börsenkurs stw Entscheidungsfindung - Kapitalmarkt Evolutionärer Algorithmus stw Simulation stw Theorie stw Verhaltensökonomik stw Kapitalmarkt (DE-588)4029578-3 gnd Entscheidungsfindung (DE-588)4113446-1 gnd |
| topic_facet | Agent-based Model Aktienmarkt Börsenkurs Entscheidungsfindung - Kapitalmarkt Evolutionärer Algorithmus Simulation Theorie Verhaltensökonomik Kapitalmarkt Entscheidungsfindung Hochschulschrift |
| url | http://www.verlagdrkovac.de/978-3-8300-4215-0.htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017149566&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV013087358 |
| work_keys_str_mv | AT lampeniusniklas decisionmakinginfinancialmarketsdevelopmentandvalidationofabehavioralmodelutilizingamultiagentmultiperiodstockmarketsimulation |