Feedback Proposals 2024

Author

Stijn Masschelein

Luke Pham

  • The overall idea and the research question you identify from the literature is interesting. However, the interesting part is the combination of the finding that capital markets reward “green” disclosure but that not all of that capital gets invested. The empirical part seems to indicate that you only are going to focus on the first part (SEO underpricing). This would take away a lot of the contribution of the study.

  • One important distinction from the previous literature that I could not discern is what the counterfactual is for the finding that green firms invest less of the capital raised. Is the finding that let’s say green firms invest 80% and brown firms invest 100%? (Actual numbers don’t matter)? It’s still impotant to know from a policy perspective whether the overall effect of green disclosure is more investments in green projects or not. That is, had the green firms not done any disclosure would they have raised less capital and invested in less projects overall? Would that capital have gone to other companies?

  • On p.4 you mention the findings of the Al-Hadi et al. (2017) study. The reduction of financial risk effect of ESG performance is consistent with the main argument that “green” disclosure leads to more capital raised that does not get spend.

  • You need to explain what SEOs are before you discuss the literature around SEOs.

Daniel Poland

  • When reading your proposal, I did not really understand the mechanism behind the differential effect of short selling bans on liquid vs illiquid stocks. My very simple simulation in the last week was an attempt to better understand potential explanations. My guess was that when a short selling ban basically puts a floor under the price of a stock, it decreases the risk of information asymmetry in illiquid stock which might lead to more volume of trades. I think that your thesis would benefit from more theoretical thinking to hypothesise the type of effect that a self-regulated short selling ban can have. This would also help to better sell your setting to the reader.

  • When you have the data, it would be good to make some graphs with the days on the x-axis. There could be some anticipation effects. If some of the members of the exchanges are in favour of a short-selling ban, they might have already anticipated in the days before that it will be coming.

Thomas Dempster

The proposal has two different research questions that are only tenously connected. The first one is around the effect of the delisting risk on earnings management. Basically, arguing that firms will manipulate earnings to not get delisted. The second one is that earnings management attracts attention of institutional investors. These two effects seem at face value to contradict each other. If earnings management leads to more attention from professional and more sophisticated investors, firms don’t really have an incentive to manage their earnings. I would expect that if earnings management has the goal of (temporarily) misleading investors that it would be aimed at retail investors.

In general, if you look at earnings management. I think it would be good to have a look at the Ball (2013) paper in Accounting Horizons (see here hopefully)

For assignment 6, in your simulation you do not merge the quarterly data and montly data correctly. If this comes as news to you let me know and I’ll explain it in more detail. I think the way you set it up in the simulation, you combine every quarterly observation with every montly observation in a given year.

Rafferty Smith

I find that there is a disconnect between the introduction and motivation on the one hand and the actual empirical study on the other hand. The front end is mostly focused on the potential benefits of tokenisation for the real (estate) economy but that is not what you are investigating. You are investigation the health of the financial token market and to what extent it is driven by sentiment and transaction costs. If that is what you do, you cannot really speak to the benefits of tokenisation but you can speak about what makes a tokenised market raise funds. If you want to speak about the benefits of tokenisation, you need to make a comparison with non-tokenised real estate or at least provide a credible estimate of what would have happened without tokenisation.

I would suggest that if the tokenised market is driven too much by sentiment as measured by ETH prices that might actually be a disadvantage for the tokenisation. Just like stable coins are more likely to be used for actual payments compared to bitcoin, I woudl expect that tokenised real estate markets are more useful if they “only” reflect the underlying value of the real estate.

Sami Rasmussen

  • Excellent simulation for assignment 6 but I think there is a mistake in one of the calculations. I could not exactly trace it. Just don’t put too much stock in the figures you made.

  • The last paragraph of 2.2 sounds a bit too bombastic to my ears. It’s fine here or there but be careful not to oversell your study.

  • The Elliot et al. paper is about interdependencies between countries (or organisations). Just be aware that there could be differences with systems that could have one person in charge.

  • The contributions to the literature can have a tighter connection with the literature.