A Fast and Frugal Finance: Bridging Contemporary Behavioral Finance and Ecological Rationality adds psychological reality to classical financial reasoning. It shows how financial professionals can reach better and quicker decisions using the ‘fast and frugal’ framework for decision-making, adding dramatically to time and outcome efficiency, while also retaining accuracy. The book provides the reader with an adaptive toolbox of heuristic tools and classification systems to aid real-world decisions. Throughout, financial applications are presented alongside real-world examples to help readers solve established problems in finance, including stock buying and selling decisions, even in situations of considerable uncertainty and risk.
The book concludes by describing potential solutions to financial problems, including discussions on high frequency trading and machine learning algorithms.
- Demonstrates how well-constructed ‘fast and frugal’ models can outperform standard models in time and outcome efficiency
- Focuses on how financial decisions are made in reality rather than how they should be made
- Discusses how cognition and the decision-making context interact in producing ‘fast and frugal’ choices
- Explores the development of decision-making trees in finance to aid in decision-making
Graduate students studying for a degree in finance, accounting, or economics that include a course in behavioral finance or finance, and early career researchers conducting primary research in behavioral finance. Professionals, including finance managers, financial controllers and treasurers
1. Fast and frugal reasoning versus expected-utility as a framework for financial reasoning
2. A taxonomy of heuristics for financial decision-making
3. The failure of the standard model during the 2008 Crisis
4. Risk and uncertainty: when heuristics can be rational
5. Portfolio Theory and the value of arbitrary portfolio restrictions
6. Factor pricing models
7. Investment appraisal and capital structure: Heuristics for corporate decision-making and forecasting
8. Financial Analysis: Context and the inference of value
9. Earnings Management models are simpler models of more predictive value?
10. Inference under the law of small numbers: earnings sequences rather than earning numbers
11. The future of the fast and frugal decision-making in finance and social science
- No. of pages:
- © Academic Press 2019
- 1st February 2019
- Academic Press
- Paperback ISBN:
William Forbes is a visiting Professor of Economics at Waterford Institute of Technology, Ireland and Groningen University, Netherlands. Forbes has researched and taught upon behavioural finance for nearly twenty years. Previously he has worked in Exeter, Manchester, Glasgow and Loughborough Universities.
Waterford Institute of Technology, Ireland and Groningen University, The Netherlands
Aloysius Igboekwu, Aloysius joined the School of Management and Business at Aberystwyth in January 2012 as a lecturer in Finance from Loughborough University School of Business and Economics. He has recently completed a PhD entitled “Representative agent models of earnings momentum” and is currently working on papers from that Thesis. He was also a University lecturer at Loughborough where he taught both Economics and Finance. Prior to this time he spent several years in Commercial and Corporate Banking overseas where he held different management roles.
School of Management and Business, Aberystwyth University, UK
Shabnam Mousavi, PhD (Virginia Polytechnic Institute) joined the Johns Hopkins Carey Business School in April 2013. She is a fellow of the Max Planck Institute for Human Development in Berlin (Center for Adaptive Behavior and Cognition), as well as a Network member of the University of Chicago Wisdom Project (Grant recipient, 2008). She has served on the faculty of statistics at Penn State University and finance at Georgia State and Santa Clara University. Her research is focused on actual decision processes used in daily and professional choice situations, simple and successful heuristic strategies used in complex situations, axiomatic frameworks for rationality and wisdom, Markov chain processes, characterizations of uncertainty, and communication of risk.
Johns Hopkins Carey Business School