Open Access

Helena Barden

• This thesis aims to investigate the presence of herding behaviour in the German DAX40 market during the period of the COVID-19 pandemic. Herding behaviour is a phenomenon in behavioural finance where investors ignore their own information and base their decisions on fellow market participants. This behaviour most often presents during times of high market volatility. The COVID-19 pandemic has had a critical effect on the German financial markets, making it an appropriate time period to detect herding behaviour among investors of the DAX40.To begin this investigation, a literature review is used to build a good understanding of the causes and effects of herding behaviour. The literature review also presents some of the most influential models which aim to explain herding behaviour in financial markets. This is followed by using the methodology of the Cross-sectional standard deviation (CSSD) and the cross-sectional absolute deviation (CSAD), two empirical models to detect herding in financial markets. For the investigation, daily stock data of the DAX40 performance index and the DAX40 companies was collected for two years surrounding the pandemic's beginning in March 2020. No significant evidence of herding was detected in the DAX40 market during the sampling period of the COVID-19 pandemic.