In the past decades, behavioural finance has steadily gained importance with respect to better understanding decision-mak- ing under uncertainty. Traditional economic models, among them neo-classical capital market theories or Austrian Econom- ics, for example, fail to adequately assess market agents’ behav- iour. In contrast to these theories, market agents appear to be prone to biased judgements. Individuals prefer to maintain the status quo as they are afraid of committing mistakes, which could ceteris paribus afterwards cause a feeling of regret. They thus rather refrain from any action and accept opportunity costs as these, according to Prospect Theory, are considered to be
missed profits instead of realized losses. Another explanation for biased judgement is overconfidence, which implies that indi- vidual investors trade too often as they consider their informa- tion to be more valuable than that of others. Overconfidence and status quo preference, are just two explanations for biased judge- ments. This triggers the question to what extent individual deci- sions actually exist. According to Hayek (1996), individualism is non-existent in an environment in which subjectivism generates a spontaneous order by interacting with other (market) partici- pants. Notwithstanding unpredictable future developments, there will always be particular behavioural patterns occurring repeatedly (Rapp and Cortés, 2017). Hence, the predictive power of any model could be greatly enhanced in case these patters, typically shaped by the social environment, i.e. (a herd) could ex ante be reliably identified .
In light of the above, speculative bubbles, which, assuming strictly rational economic agents, are a prime example of how investors’ biased perceptions about losses and gains trigger an emotions-based process of decision-making. Institutional Eco- nomics, among others, illustrates that investors appear to follow an institutional system, which shapes their behaviours and thus their decision-making. Simply mimicking a herd’s decisions, it seems, can meaningfully reduce uncertainty. Preliminary find- ings, however, suggest contradictions concerning biases in deci- sion-making of individuals versus those of a herd. Further, literature distinguishes between rational and irrational herd behaviour. Ultimately, this leads to the question to which extent investor herding could indeed be a rational phenomenon (Dierks and Tiggelbeck, 2019).
The remainder of this article as structured as follows: Chapter two outlines principles of (individual) decision-making under uncertainty and identifies select biases, which affect the behaviour of economic agents. Chapter three then portrays the phenomenon of investor herding and seeks to correctly embed the latter into Austrian Economics and Behavioural Economics. Chapter four investigates the extent to which any such behaviour can be consid- ered (ir-) rational before chapter five provides both a conclusion and an outlook for future research.
Progress in environmental gentrification research and hotspot analysis based on CiteSpace analysis
