Luc
Introduction#
Nice start: point of reference is efficient market hypothesis. I agree! But: try to give the reader some references on where to look up EMH and CAPM.
CAPM is also a theory, not a ‘fact’.
Gamestop is (of course) a very nice example to motivate your research with!
In this investigation, such instances with extreme stock price growth and/or volatility over relatively short periods of time will be investigated to explore whether or not markets are becoming increasingly irrational and dependent on popular belief, rather than fundamental analysis.
The reference points for these discussions are the noise trader model and the rational bubbles literature. Try to touch upon this literature briefly, to explain that extreme stock price growth can also happen within the confines of (certain) ‘classical’ assumptions.
RQ:
Do extreme trading volumes, stock volatility, affect, and investor sentiment (cumulatively referred to as hype) lead to increased security mispricing due to the overshadowing of security analysis by aggregated irrationality?
Maybe omit the due to (…) part, because that already relates to the explanation/the mechanism.
Literature#
A persistent reference to hype specifically was made in 2019, by Jeffrey Funk, in a modern journal.
What do you mean by “in a modern journal”?
Structure: I think the mispricing part should come before the hype part. There should be a couple of definitions of mispricing in that section, which you can later employ in your methodology section. This is a crucial section of your thesis: the more convincing (and robust) your definitions of mispricing, the likely one is to believe that hype is measuring what it wants to measure.
Try to answer common sense questions: when a model marks an asset as ‘mispriced’, how do we know that it is true, instead of thinking that the model of a ‘well-priced’ asset is erroneous?
Methodology not yet developed, although the hypothesis seem to be good! A detail: you define your hypotheses in terms of extremes, whereas it is also possible that the effects are ‘just’ of a continuous nature, rather than a dichotomy between extreme and non-extreme values.
Think about: data collection, measures/proxies