Okke
Introduction#
The introduction is very well structure, but the first paragraph seems very ad hoc now. These …
However, research shows that market participants are prone to irrational behavior (Bunting, 2013). Bunting states that investors are overconfident, excitable and lazy.
.. claims should be backed up by more evidence, and you should also make clear how various research arrived at these and similar conclusions. Then, you can smoothly proceed from the very general (irrationality) to the very specific (alphabet bias), which you do in a very natural way.
Literature#
Structure should be improved.
Structure now as far as I can see:
- effect(s) of inexperienced traders on stock prices (turnover)
- increase in turnover since 2004
- other effect of inexperienced traders (alphabet bias)
- impact of alphabet bias on investor behavior (why is it relevant? you are explaining risk, not necessarily 2nd order effects of how other investors respond to stocks being traded by ‘biased’ investors)
My suggestion:
- Irrationality manifests itself in various ways
- One way is alphabet bias
- Effects: turnover
- Effects: crash risk
- Effects: other risk(?)
Methodology#
- How do you measure risk apart from $\sigma_i$?
- Why not a $\beta$ from an asset pricing model?
- I see later it is there, but you should structure so that all DV’s are together!
Re: bad news. I think that should then also be introduced in the theory section (as it is de facto a new hypothesis). Although I agree that it can be interest to find out!
Try to write your models in equations:
$Crash_{i} = F(\alpha_i + \beta \cdot \text{Alphabet}_i + \gamma X_{i} + \epsilon_i)$
$\sigma_i = \alpha + \beta \cdot \text{Alphabet}_i + \dots + \epsilon_i$
Lastly, I will try to make an effort to see how the alphabet bias might add to the explanatory power of the CAPM. Unfortunately, I have not been able to figure this out. Yet I am hopeful that I will still be able to deliver on this.
$R_i = \alpha + \beta R_m + \gamma \cdot \text{Alphabet}_i + \epsilon_i$