Deploying Behavioral Finance Tools To Improve Financial Decision Making

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Type and Duration

Preproposal PhD-Thesis, since February 2019

Coordinator

Chair in Finance

Main Research

Wealth Management

Field of Research

Behavioural Finance

Description

Behavioral Finance tools have already been successfully incorporated within the FinTech sector. They mainly assess client risk tolerances and whether clients are susceptible to common cognitive biases. The author opts to write a cumulative dissertation format with three to four articles, subsequently the research project can be also divided into various parts: First, the author wants to develop his own software for continuous double auction market experiments based on the open-source and online software platform O-Tree. So far, experimental research has largely ignored algorithmic trading, however OTree offers the possibility to implement this feature. Second, he wants to incorporate Behavioral Finance tools into the robo-advisory process. He wants to identify clients at risk of making poor financial decisions during a market downturn and evaluate whether nudges can decrease the risk to exit the market at the wrong time. Third, he will further develop the theoretical aspects of his paper "The Rating Game" and analyse the rating reputation premium by running multivariate regressions.

Finally, he will be part of the FFF project "Perception and processing of informative signals on financial markets" at the Chair of Finance and use to some extent the derived results for his experimental designs.

Keywords

Behavioural Finance, experimental research design, Experimental Research, Continuous Double Auction, Laboratory Experiment