| Description |
1 online resource : illustrations |
| Series |
Clarendon lectures in finance |
|
Clarendon lectures in finance
|
| Contents |
2.1.4 Asymptotic Properties -- 2.2 Probability Matching -- 2.2.1 Exact Probability Matching -- 2.2.2 The General Case -- 2.2.3 Individually Optimal vs Growth-Optimal Behaviour -- 2.3 Risk Preferences -- 2.3.1 Growth-Optimal Risk Preferences -- 2.3.2 Risk Aversion -- 2.3.3 Loss Aversion -- 2.4 Idiosyncratic versus Systematic Risk -- 2.4.1 Idiosyncratic Risk -- 2.4.2 The General Case -- 2.5 Discussion -- 3 Mutation -- 3.1 Environments with Mutation -- 3.1.1 Asymptotic Population Dynamics -- 3.1.2 Extinction Probability -- 3.2 The Optimal Degree of Irrationality |
|
3.2.1 An Example with Two Behaviours -- 3.3 Generalization and Simulation -- 3.3.1 Symmetric Regimes -- 3.3.2 Asymmetric Regimes -- 3.3.3 When Mutation Is Undesirable -- 3.3.4 Optimal Degree of Irrationality -- 3.4 Discussion -- 4 Group Selection -- 4.1 Environments with Factor Structure -- 4.2 Individual versus Group Optimality -- 4.3 Multinomial Choice with Multiple Factors -- 4.4 A Numerical Example -- 4.5 Discussion -- Part II. BEHAVIOUR -- 5 Probability Matching -- 5.1 The Binary Choice Game -- 5.2 Summary Statistics -- 5.3 A Model of Individual Behaviour -- 5.4 Initial Learning |
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5.5 Decision Autocorrelation -- 5.6 Probability Matching -- 5.7 Individual Differences -- 5.8 Discussion -- 6 Risk Aversion -- 6.1 Environments with Mixed Risks -- 6.2 Individual Preferences -- 6.3 Risk Aversion and Systematic Risk -- 6.4 Common Distributions of Relative Fecundity -- 6.5 Testable Implications -- 6.5.1 Biology and Behavioural Ecology -- 6.5.2 Financial Economics -- 6.5.3 The Equity Premium and Systematic Risk -- 6.6 Discussion -- 7 Cooperation -- 7.1 Environments with Interactions -- 7.1.1 Assumptions -- 7.1.2 Results -- 7.1.3 Evolutionary Optimality -- 7.1.4 Idiosyncratic Risk |
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7.1.5 Random Matching -- 7.1.6 Density Dependence -- 7.2 Behavioural Implications -- 7.2.1 Specialization -- 7.2.2 Sacrifice -- 7.2.3 Coordination -- 7.3 Discussion -- 8 Bounded Rationality and Intelligence -- 8.1 Environments with Intelligence -- 8.2 An Evolutionary Definition of Intelligence -- 8.3 Bounded Rationality -- 8.4 A Universal Measure of Intelligence and its Cost -- 8.5 Upper Bound on Correlation -- 8.6 Intelligence across Generations -- 8.6.1 No Inter-Generational Variation -- 8.6.2 Inter-Generational Variation -- 8.7 Discussion -- 9 Learning to be Bayesian |
| Summary |
'The Adaptive Markets Hypothesis' (AMH) presents a formal and systematic exposition of a new narrative about financial markets that reconciles rational investor behaviour with periods of temporary financial insanity. In this narrative, intelligent but fallible investors learn from and adapt to randomly shifting environments. Financial markets may not always be efficient, but they are highly competitive, innovative, and adaptive, varying in their degree of efficiency as investor populations and the financial landscape change over time. Andrew Lo and Ruixun Zhang develop the mathematical foundations of the AMH - a simple yet surprisingly powerful set of evolutionary models of behaviour - and then apply these foundations to show how the most fundamental economic behaviours that we take for granted can arise solely through natural selection |
| Notes |
Also issued in print: 2024 |
| Bibliography |
Includes bibliographical references and index |
| Audience |
Specialized |
| Notes |
Description based on online resource and publisher information; title from PDF title page (viewed on January 5, 2024) |
| Subject |
Investments -- Psychological aspects
|
|
Efficient market theory -- Mathematical models
|
|
Economics.
|
|
Finance and Accounting.
|
| Genre/Form |
Electronic books
|
| Form |
Electronic book
|
| Author |
Zhang, Ruixun, author
|
| ISBN |
9780191767289 |
|
019176728X |
|
