In recent decades, the financial markets have experienced various crises, shocks and disruptive events, driving high levels of volatility. This volatility is too strong to be fully justified simply by changes in fundamentals. This volume discusses these highly relevant issues with special focus on asset pricing and behavioral finance. Financial price assets of the 2020s appear to be driven by various attractors in addition to fundamentals, and there is no doubt that investor emotions, market sentiment, the news, and external factors such as uncertainty all play a key role. This has been clearly observed in recent years, especially during the ongoing coronavirus pandemic that has changed the common perception of the way financial markets work.
Author(s): David Bourghelle, Pascal Grandin, Fredj Jawadi, Philippe Rozin
Series: Contributions to Finance and Accounting
Publisher: Springer
Year: 2023
Language: English
Pages: 227
City: Cham
Foreword
Acknowledgments
References
Contents
About the Editors
Part I Asset Pricing
Oil Price Uncertainty: Panel Evidence from the G7 and BRICSCountries
1 Introduction
2 The Panel Structural VAR Model
3 The Data
4 Panel Evidence
4.1 The G7 Countries
4.2 The BRICS Countries
5 Conclusion
References
Climate Risk and the Volatility of Agricultural Commodity Price Fluctuations: A Prediction Experiment
1 Introduction
2 Data
3 Prediction Models
4 Empirical Results
5 Concluding Remarks
References
Linking Covid-19 Epidemic and Emerging Market OAS: Evidence Using Dynamic Copulas and Pareto Distributions
1 Introduction
2 A Brief Literature Review on Covid-19 and Corporate Spreads
3 Data and Distributional Characteristics of the Variables of Interest: Corporate OAS and Epidemiological Variables
3.1 Distributional Characteristics of Corporate OAS
3.1.1 Some Theoretical Backgrounds
3.1.2 Fitting Log-Normal, Weibull. and Gamma Distributions to OAS Data
3.2 Epidemiological Variables
4 Which Epidemiological Variables Are Correlated with Corporate OAS?
4.1 Rank Correlation Through a Dynamic Copula Analysis
4.2 Epidemiological Variables Are Strong Determinants of the Right Tail Index of Corporate OAS Distribution Function
4.2.1 Fitting Pareto Laws
4.2.2 Implications for the Underlying Dynamics of the Short Rate
5 Conclusion
Appendix 1: Fitting Weibull, Log-Normal, and Gamma Distributions to OAS
Appendix 2: Graphs of Time-Varying Copulas
Appendix 3: Evidence of Nonlinear Relationships
References
Part II Behavioral Finance
On the Relevance of Employee Stock Option Behavioral Models
1 Introduction
2 Behavioral Aspects of ESO Exercise Decisions
3 ESO Behavioral Models
3.1 The Economy of ESO Contracts
3.2 Preferences of the Representative Employee
3.3 Choice of the Probability Weighting Function
3.4 Specification of the Reference Point
3.5 The Exercise Model
3.6 Prediction of Exercise Decisions
4 Managerial Implications
4.1 Cost to Shareholders: ESO Fair Value
4.2 Incentive Effect and ESO Contract Design
4.3 Implied Employee Sentiment
5 Conclusion
References
The Term Structure of Psychological Discount Rate: Characteristics and Functional Forms
1 Introduction
2 Literature Review
3 Experimental Design and Data
3.1 Experimental Design
3.2 Empirical Methodology
4 Results
4.1 Characteristics of the Psychological Price of Time
4.1.1 Time Preference Consistency
4.1.2 Term Structure of the Psychological Price of Time
4.2 Form and Parameters of the Term Structure of Psychological Discounting Rates
4.2.1 Comparison Between Psychological Discount Function Parameter Estimations
4.2.2 Allocation of Psychological Discount Functions to Classes
4.2.3 Distribution of the Population by the Psychological Function Discount
4.2.4 Homogeneity of Time Preference Trade-Off Media
5 Conclusion
References
An Experimental Analysis of Investor Sentiment
1 Introduction
2 Experimental Methodology and Related Hypotheses
2.1 Experimental Design
2.2 Experimental Implementation
2.3 Related Hypotheses
3 Results
3.1 Distributions and Means of Investment Proportions
3.2 Regression Analysis
3.2.1 Main Treatment Variables
3.2.2 Subdivision of the Language Conditions and Additional Control Variables
4 Conclusion
Appendix
References
On the Evolutionary Stability of the Sentiment Investor
1 Introduction
2 Intertemporal Consumption Model
3 Beliefs Structure
3.1 Bayesian Agent
3.2 BSV Agent
4 Market Selection and Evolutionary Stability
4.1 Bayes Accuracy
4.2 BSV Accuracy
4.2.1 Case λ1+λ2=1
4.2.2 Case 0<λ1+λ2<1
4.3 Survival and Dominance of Sentiment Investor
5 Conclusions
References
Institutional Investor Field Research: The Company's Fundamentals Are Driven by Investor Attention
1 Introduction
2 Literature Review and Research Hypothesis
3 Research Design
3.1 Data Source
3.2 Variable
3.2.1 Dependent Variable: Institutional Investor Field Research
3.2.2 Independent Variable 1: Company Fundamentals
3.2.3 Independent Variable 2: Investor Attention
3.2.4 Control Variable
3.3 Measurement Model Setting
4 Empirical Analysis
4.1 Descriptive Statistics
4.2 Correlation Analysis
4.3 Multicollinearity Test
4.4 Analysis of Measurement Model Results
4.4.1 Whether Institutional Investors Will Conduct Driving Factors for Field Research
4.4.2 Company Fundamentals Affect Positively the Number of On-Site Visits Conducted by Institutional Investors
4.4.3 The Attention of Investors Positively Affects the Number of On-Site Visits by Institutional Investors
4.5 Robustness Test (Replace Arguments)
5 Conclusion
Appendix 1: Industry Group and Sector Classification Structure (8 Industry Groups and 28 Sectors) According to “The Stock Exchange of Thailand (SET) in 2015”
References
What Drives the US Stock Market in the Context of COVID-19: Fundamentals or Investors' Emotions?
1 Introduction
2 Literature
3 Empirical Results
3.1 Data and Preliminary Analysis
3.2 Empirical Analysis
4 Conclusion
References
