Technological Shocks and Algorithmic Decision Aids in Credence Goods Markets
By Alexander Erlei, Lukas Meub
Rating
1286
Battle Count: 26
Relevance
3/10
While not directly applicable to quantitative trading, insights on expert decision-making and technology adoption may be relevant for algorithmic trading strategy development
Implementation Complexity
6/10
Experimental design is complex, but implementation of findings would require significant adaptation to trading contexts
Reproducibility
4/5
Detailed experimental design and parameters provided, data and programming available in online appendix
About this paper
Methodology: Online Experiment. Problem types: Experimental Economics, Decision Making, Market Efficiency.
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