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The microscopic simulation of financial markets [electronic resource]
להגדלת הטקסט להקטנת הטקסט- ספר
Microscopic Simulation (MS) uses a computer to represent and keep track of individual (""microscopic"") elements in order to investigate complex systems which are analytically intractable. A methodology that was developed to solve physics problems, MS has been used to study the relation between microscopic behavior and macroscopic phenomena in systems ranging from those of atomic particles, to cars, animals, and even humans. In finance, MS can help explain, among other things, the effects of various elements of investor behavior on market dynamics and asset pricing. It is these issues in parti
| כותר |
The microscopic simulation of financial markets [electronic resource] : from investor behavior to market phenomena / Moshe Levy, Haim Levy, Sorin Solomon. |
|---|---|
| מוציא לאור |
San Diego : Academic Press |
| שנה |
c2000 |
| הערות |
Description based upon print version of record. Includes bibliographical references (p. 277-289) and index. English |
| הערת תוכן ותקציר |
Front Cover Microscopic Simulation of Financial Markets: From Investor Behavior to Market Phenomena Copyright Page CONTENTS PREFACE Chapter 1. Classic Models in Finance: Solved and Unsolved Issues 1.1 Introduction 1.2 EUT, Alternative Models, and Noise Traders 1.3 Classical Analysis in Modern Finance 1.4 Summary Chapter 2. Decision Weights, Change of Wealth, and Value Function: The Experimental Evidence 2.1 Introduction 2.2 Decision Weights and Objective Probabilities 2.3 Change in Wealth versus Total Wealth 2.4 Risk Aversion and Risk Seeking 2.5 Cumulative Prospect Theory: Decision Weights and Stochastic Dominance2.6 Summary Chapter 3. Empirical and Experimental Evidence Regarding Preferences: Absolute and Relative Risk Aversion 3.1 Introduction 3.2 Arrow and Pratt Risk Premium and the Subject's Wealth 3.3 The Gordon, Paradis, and Rorke Experiment 3.4 The Kroll, Levy, and Rapoport Experiment 3.5 DARA and IRRA When Financial Rewards and Penalties Are Possible 3.6 The Implication of the Findings Regarding Preferences to Microscopic Modeling 3.7 Summary Chapter 4. Inefficient Choices and Investors' Irrationality 4.1 Introduction4.2 Investors' Inefficiency and Irrationality 4.3 The ''Hot Hand'' in Basketball and Looking for Trends in the Stock Market 4.4 Correlations and the Portfolio Investment Decision: How Close Are Investors to the Efficient Frontier? 4.5 Testing the CAPM: An Experimental Setting with Ex Ante Parameters 4.6 Summary Chapter 5. The Microscopic Simulation Method 5.1 Introduction 5.2 A Simple Example of a Microscopic Simulation Application: Nuclear Fission 5.3 Considerations in Applying Microscopic Simulations 5.4 The Effects of Discreteness-Comparison with the Analytical ''Continuum'' Approach5.5 Philosophical Remarks Chapter 6. Microscopic Simulations in Various Fields 6.1 Introduction 6.2 Traffic Flow Microscopic Simulations 6.3 Population Dynamics, Mobility, and Segregation 6.4 Microsimulation in Social Science 6.5 The Outbreak of Cooperation, Inductive Reasoning, and Investment Strategies 6.6 Dynamics of Expectations: the Formation of Coalitions 6.7 Microscopic Simulation of the Neolithic Revolution 6.8 Microscopic Simulation in Marketing 6.9 Microscopic Simulation in Biology Chapter 7. The LLS Microscopic Simulation Model7.1 Introduction 7.2 The Model 7.3 Results of the Benchmark Model 7.4 Results of the LLS Model with a Small Minority of EMBs 7.5 Survivability of the EMB Investors 7.6 Summary Appendix 7.1 Appendix 7.2 Appendix 7.3 Chapter 8. Various Financial Microscopic Simulations 8.1 Introduction 8.2 Stigler's Random Tender Stream Model 8.3 The Portfolio Insurers Model of Kim and Markowitz 8.4 The Financial Life of Arthur, Holland, Lebaron, Palmer, and Tayler 8.5 Lux's Intermittent Fluctuations Induced by Traders Dynamics 8.6 The Herding Model of Bak, Paczuski, and Shubik |
| היקף החומר |
1 online resource (319 p.) |
| שפה |
אנגלית |
| מספר מערכת |
997010712464805171 |
תצוגת MARC
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