Zurich Trading Simulator
Experimental Design | Open Source Software | Research Programme | Open Science Data
Experimental Design | Open Source Software | Research Programme | Open Science Data
Free to use. Please cite: Andraszewicz, S., Friedman, J., Kaszas, D. & Hölscher, C. (2023). Zurich Trading Simulator (ZTS) - A dynamic trading experimental tool for oTree. Journal of Behavioural and Experimental Finance, 37, 100762
The Zurich Trading Simulator (ZTS) is an Open Source and Open Science experimental design and platform developed within the Chair of Cognitive Science and the Decision Science Laboratory at ETH Zurich for studying dynamic decision-making in financial markets. The simulator allows researchers to observe how individuals trade, take risks, and respond to market information in simulated environments that reproduce historical or desired artificial market scenarios.
Within the ZTS, participants interact with continuously changing asset price, enabling researchers to measure trading behaviour, such as risk-taking and trading activity (volume, trading frequency), and the psychological factors that shape investment decisions. The code, materials, and documentation are openly available so that researchers can reproduce and extend the experimental design.
Design Features
The Zurich Trading Simulator is an experimental paradigm designed to study how people make financial decisions in dynamic, simulated stock market environments. Rather than presenting static scenarios, the ZTS exposes participants to continuously changing price data, producing rich behavioral records of individual investment paths.
Built on an open-source scientific experimenral platform oTree (python) the ZTS can display historical or artificially generated price patterns alongside contextual news. Participants buy and sell a risky asset using six quick-time buttons, and every decision is recorded with high temporal precision. The price path evolves on a tick-by-tick basis, such that the first price point appears in the middle of the y-axis and the margins of the y-axis adjust to make the price chart agnostic wrt. to the trend.
Because each participant's sequence of trades is unconstrained, the design captures a variable number of decisions per person. This differentiates the ZTS from paradigms with fixed trial structures. This also makes the ZTS particularly well-suited for studying trading frequency, volume, timing, and the physiological responses recorded in a continuous fashion. In that sense, the ZTS is more than a piece of software. It is an experimental design that can be implemented in other programming tools.
Observed behavioural data can be linked with psychometric or other self-reported variables. By default, a ZTS task ends with a link to a survey softare of the researcher's choice. A researcher can can adjust various features directly in the ZTS source code (knowledge of Python is necessary).
PARADIGM
Dynamic sequential decision making
PLATFORM
oTree (Python)
INPUT
CSV file with historical or artificial price data and news
INTERFACE
6 quick-trade buttons, price chart, portfolio, news box
OUTPUT
High-frequency behavioural data
LICENSE
Creative Commons