Meizhu Chen
- The motivation is well written and connects the different parts quite well but it is somewhat spare. For the thesis, you should try to add more. This could be partly based on the results.
- With the threshold for regulations (for instance from 2007 in Australia), how does the government know which firms are above and below the threshold? (minor issue).
- Just above H2, you write about the effect of short-term incentives on environmental performance and you seem to be somewhat surprised that these incentives work sometimes. In the section for H2, you focus on the distinction between different reward types (long-term versus short-term) but the underlying argument is that they could be measuring the same thing, i.e. the beneficial effect of for instance reducing emissions on the firm’s performance. This is why I think it’s useful to distinguish between the reward and the measure when you talk about incentives.
- You basically have a staggered difference-in-difference research design. See my lecture 6 for FINA4590.
Philip Nguyen
- In the introduction, watch out with using big numbers. For instance, a 384% increase from 1990 to 2020 is just an increase of 5% per year. This is a minor issue but it bothers me, probably less your assessors.
- In the introduction, it took me until the competing hypotheses to really understand why it is interesting to look at cross-border M&A with respect to anti-slavery legislation. I think you want to make that link earlier.
- In your competing hypotheses (which I really like!), I think you are making some implicit assumptions and it would be good for yourself to spell these out in more detail. Not because the hypotheses could be wrong but because it might help you to understand when some of the hypotheses are not supported. For instance for H1a, you are assuming that the value of the firm will temporarily drop, but that acquirers will realise that this drop is temporary. That means, that acquirers are outsmarting the market because the market does not realise (to the same extent) that the drop is temporary. So, there is some weak market inefficiency in this argument. Like I said, this is fine but it might be one reason why this hypothesis does not hold in the data. Or it might be more likely to hold for less financially developed markets.
- I also think that the hypotheses are not necessarily competing. Both things could happen, acquirers are smarter than the market (1a) and they have more difficulty creating synergies (1b). These two effects could offset each other on average in your sample.
- Be careful with your introduction. At the start, you argue that slavery is always bad but in the last paragraphs you seem to suggest that policy makers should way up the good of anti-slavery legislation to the risk of being able to attract more capital. So you take a more utilitarian approach to slavery. Similarly, while from a rational theory point of view, anti-slavery legislation and generous employee benefits can be analysed similarly, I would be careful not to equate the two. Make it clear that you analyse them in a similar way but that they are not the same.
- You basically have a staggered difference-in-difference research design. See my lecture 6 for FINA4590. You are taking one difference directly by calculating the change in the dependent variable. One option you could take is to not look at changes but use a model for counts (i.e. poisson) for the number of deals and use a diff-in-diff specification. This is just an idea an no obligation to follow.
Joshua Laubsch
- Introduction: The 9/11 attacks are over 20 years ago. Probably not the best example of a recent geopolitical event.
- I think you could also motivate your study by what happened in the Nickel market: https://on.ft.com/3xfdCgv
- The proposal now reads too much like it’s about the relation between different variables and less about the underlying economics/financial reality. If I understand your setting, you are interesting in commodity markets where there are two types of market participants: traders and physical producers/users. The motivation for the producers/users is to hedge price risk and for traders it’s to benefit from arbitrage. I think your research question involves around what happens if there is more political risk. I would think that the first order effect is that this will affect the producers/users and consequently the traders. Next, you want to investigate whether the positioning by traders influences the how the geopolitical risk gets incorporated in those markets. For me, the story would be easier to understand if you start your thesis with explaining the basic economic structure of these participants and how they interact. You can support that explanation with all the empirical results you cite.
- I think a more critical evaluation of the Geopolitical Risk Index would also be good. The index is based on English language newspapers and therefor will probably be biased towards certain risks. This might be important if you are going to investigate the different markets which may or may not be more exposed to “the West”.
Chloe Truscott
- From the motivation it was not entirely clear what you meant by “information transmission” (i.e. that the information is about the health of the industry) and why firms would react to that information. After reading the whole document I get the relation between “information transmission” and “peer reaction”. It’s probably a matter of being a bit more specific in the introduction.
- I think for most of the reaction hypotheses, you are sort of assuming that the focal firm is announcing a dividend increase, and the peer firms need to follow because this would mean good news for the industry. You don’t really deal with dividend decreases. In that case, not decreasing as a peer could actually be a signal that you are doing better than the focal firm. I assume that this is not really a large part of the sample and you are going to exclude it. Still, it might be good to think about it and make it clear what your assumptions are.
Henry Miao
- In the motivation, you introduce that you are going to study different valuation models for crypto assets. My first thought there was that you probably want different models for different types of crypto tokens/assets. You mention this later but it seems worthwile thinking about it more carefully.
- This might be specific to me. However, when you talk about valuation models, I would like to see you define more specifically what you mean by valuation models. I think that you have something in mind where the valuation model is a way of estimating the fundamental value of an asset which can be different from the price, maybe due to speculation or limited liquidity in the market. This is important because we cannot observe the fundamental value only the price and market cap of the asset. The reason I mention this is that the fundamental value model might be correct but you might not find support in the data because the price is too noisy. That is fine, it’s just one explanation for insignificant results. For instance, some people might say that the fundamental value of Luna is 0. The price was temporary different from 0 but the fundamental value is 0.
- I wonder whether you cannot integrate the different models more. For instance, G in H2 and the total addressable market seem to be related to each other. Similarly, network effects seem to be a way of estimating the total market. That is G = V = kN^2. If true, this might give you more insight in what model you can estimate and whether it is appropriate to test the variables together or separately.
Tom Butler
- In the motivation, you are quite vague about the research question. You are going to “explore” how economic policy uncertainty impacts the yield curve. You also talk about spillovers but it is not really clear what you mean by that from the introduction. Later in the hypothesis development, you explain that for instance the role of the U.S. and the exposure of an economy to the U.S. could moderate the relation between uncertainty and the yield curve. I think these more precise predictions are better as a proposal (i.e. it focuses your attention and you have a mechanism to investigate) and as a writing device (i.e. it focuses the attention of the reader). I would focus more on this mechanism for heterogeneity in the relation between uncertainty and yield curve. Or an any other mechanism that can help explain the heterogeneity.
- In the motivation, you are mention that you might uncover the reaction of bond traders to uncertainty and that other (?) traders might use your results to anticipate these reactions. I would think that professional traders are already doing this if it impacts their profit/loss.
- Method: Based on the hypotheses it was not clear to me why you want to investigate the lagged effect of EPU.
- Don’t say that you are going to use an instrumental variable approach if you don’t know what the instrument is. That is like saying that you are going to do a regression but you don’t know what the dependent variable is. It’s fine to not have a perfect research design.
Jackson Fletcher
- In paragraph 2, you say that Bitcoin is a scarce unit of account and in the next sentence that there are 1925 different cryptocurrencies. This at least seems to suggests that scarcity is not generally a required feature in the crypto world.
- The introduction feels very big to me, you seem to want to tackle a lot of research questions at once and I am not sure you can do them all justice by investigating them with a good research design. I would focus on the ones where you have a strong research design or a strong theoretical argument.
- While you say that your study aims to investigate the research question objectively, your motivation and introduction does not feel objective. It is written with a very negative view of intermediaries. From a very simplistic economic point of view, this does not make any sense. If the prices charged by those intermediaries why have they not be competed away? Is it possible that intermediaries have an important function maybe to reduce counterparty risk or search costs? I think it would be useful to think more about these kind of questions. It might give you a more precise idea of where intermediaries could be vulnerable to competition from DeFi.
- Measurement & Methodology: I don’t think it’s feasible to do all 6 empirical studies. I could not assess them all because of the short description. I think it’s better to focus on 1 or 2 so that you can explain them well and the reader can assess whether your method is appropriate for your research question.
Chen Cui
- I quite like the match of the research design and the research question. I think you can frame the contribution stronger as “investigating the role of gender in information quality” and you are using the crowdfunding market to investigate it. This highlights that you are using the crowfunding market because it is better because (1) there are less self-selection issues around gender and (2) disclosure is largely voluntary.
- I think you can use the introduction of the stricter consumer law to do a difference (gender) - in - difference (before/after regulation).
- I think it would be good to think a bit more about your dependent variables. Readability is one part of the disclosure but maybe it might be useful to look at others. For instance, the level of numerical detail or you could look at updates to the original disclosure and how timely they are.
- In the effect book there is a chapter on matching in general. It might be useful to have a read. It will also have R, python, and Stata code.
Qingyi Chen
- Be careful with using a big number to motivate your study. You use USD$1.1 Trillion to describe the green bond market. It is a big number but it probably would be more useful to see it as a percentage of the total corporate bond market. This is something that probably annoys me more than your assessors.
- The basic argument is that the issuance of green bonds is a positive signal for the company that issues the bond and thus a negative signal for it’s competitors (i.e. peers). This suggest that the larger the effect on the issuing company, the larger the effect on the peers, keeping everything else equal. That’s why I think it would be useful to investigate the effect on the issuing firm first. That will give you some confidence that you can actually find an effect for the peers.
- In part 1, you report that the effect of green bond issues is not always positive. It would be good there is a theoretical argument for why that is the case and not just the result of slightly different dependent variables. (This is also why it is useful to first establish an effect for the issuers.)
- In part 2 you introduce a different theoretical mechanism, green bonds attract attention. Attracting attention can be good (if performance is good) but it can also be bad. It might be useful to make a distinction between professional investors and retail investors because the latter are maybe more likely to be attracted by attention grabbing actions.
- The distinction between a signalling explanation and an attention grabbing explanation is probably important to understand the results. I would expect that a positive signal can be detected in the returns while attention grabbing is more likely to show up in the volatility (especially through retail investors?) and liquidity.
Peter Matthews
- The introduction is (understandable given the change of topic) fairly broad and vague about the actual research question. I mainly want to highlight this because you have a fairly casual communication style and you set up an ambitious research question in the introduction. If you don’t deliver in the empirical part, an ambitious project might backfire. I would advice you to better define the scope of your study for your thesis. For instance, you mainly focus on exchange traded equities in Australia. There is nothing wrong with acknowledging that in the introduction.
- I like the structure of the three arguments about the relation between inflation and equity prices. However, I think the categories do not seem necessarily mutually exclusive. The Fisher argument is a pure financial markets argument in the sense that the underlying assumption is that in a world where only inflation changes but all the rest stays the same, equity prices are just going to incorporate changes which lead to the same prices in real terms. The Fama argument is that inflation or the causes for inflation also impact the real economy and therefor equity prices. This then relates to category 3 because some economic sectors might be more sensitive to those real economy effects than others. I think synthesising these two arguments a bit more could lead to sharper hypotheses. I also wonder whether controlling for the Full Sample return in the equation on p9 removes some of the sensitivity to inflation that in real economy effects. That is not necessarily bad, but it might be good to at least be aware of it.
- Can you find the Fama-French factors here: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html#International?
- It’s not really clear what the goal is of the Parikh approach for your specific research question. You could explain this better in the thesis.