Research Workshop on “Learning-to-Forecast Experiments”
Date: July 20 – 21, 2023
Instructor: Assoc. Prof. Annarita Colasante (La Sapienza, Rome)
Bounded rationality and behavioral economics
Experimental finance and economics
Forecasts and expectations in the heuristic switching model
The field of experimental finance is becoming more and more important in explaining empirical evidence through the investigation of investors behavior. This course is designed to introduce students with the main pillars of both behavioral and experimental finance and to provide some hints on how to integrate experimental and computational methods. The first part of the course will be devoted to the review of the main theoretical concepts related to behavioral and experimental approaches. In the second part we will explore the importance of expectations in financial markets by going through the review of experimental forecasting literature. We will then conclude with some practical examples on how to infer expectations from forecasts and, furthermore, on how to deploy computational methods to replicate experimental evidence.
No prior knowledge is required. I suggest previously downloading the software R and z-tree.
This course is open for advanced masters students and PhD candidates. If you would like to participate, please send a short email describing your motivation, together with your CV to xanthi.tsoukli(at)uni-bamberg.de before 15.07.2023. You will be notified of your acceptance.
The course will be held in a hybrid-mode. External participation is only virtually possible. No financial support is available.
About the instructor:
Annarita Colasante is associate professor in applied economics at Unitelma Sapienza. She obtained the PhD in economics at the Università Politecnica delle Marche (Italy) in 2014 and she spent 4 years at the Universitat Jaume I (Spain) to improve her knowledge in the field of experimental economics. The main focus of her research is to investigate how economic policies can be shaped taking into account individuals' behavior. She applies the tools of behavioral economics in many fields such as financial markets, social economy organization and energy consumption. Her work has been published in several academic journals, such as the International Journal of Forecasting, Journal of Economic Interaction and Coordination and the Journal of Behavioral and Experimental Finance.
16.15-17.45: Introduction to experimental economics
17.45-19.15: Introduction to experimental finance
09.00 - 10.00: Tutorial: experiments' design with z-tree
10.00 - 11.30: Forecasts and expectations in experimental finance
11.30- 12:30: Lunch break
12.30 - 14.00: Tutorial: learning models applied to experimental data
Anufriev, M., & Hommes, C. (2012). Evolutionary selection of individual expectations and aggregate outcomes in asset pricing experiments. American Economic Journal: Microeconomics, 4(4), 35-64.
Assenza, T., Heemeijer, P., Hommes, C. H., & Massaro, D. (2021). Managing self-organization of expectations through monetary policy: A macro experiment. Journal of Monetary Economics, 117, 170-186.
Bloomfield, R., & Anderson, A. (2010). Experimental finance. Behavioral finance: Investors, corporations, and markets, 113-130.
Colasante, A., Alfarano, S., Camacho-Cuena, E., & Gallegati, M. (2020). Long-run expectations in a learning-to-forecast experiment: a simulation approach. Journal of Evolutionary Economics, 30, 75-116.
Croson, R. (2005). The method of experimental economics. International Negotiation, 10(1), 131-148.
Duffy, J., & Fisher, E. O. N. (2005). Sunspots in the Laboratory. American Economic Review, 95(3), 510-529.