Esg investing

Modelling the Impact of Climate Change and Policies on GDP

19.August 2021

Climate change is becoming a central topic among economists, investors, politicians and the general public as well. Scientists warn us that we have to act immediately, but it is not that simple because becoming environmentally friendly is not cheap, and we are somewhat reluctant even though we have only one Earth. Moreover, while fighting climate change might be seen as a cost for developed economies, less developed economies frequently do not have many alternatives to fossil fuels.

A captivating insight to this topic offers a paper by Alestra et al. (2020) since the research provides a model to examine climate change scenarios for GDP forecasting, considering both GDP damage caused by the climate change itself and the impact of measures aimed to mitigate the climate change. It is crucial to emphasise that climate change endangers the economy. Therefore, even though fighting climate change can negatively affect the GDP, not acting might be even worse in the long run.

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ESG Incidents and Shareholder Value

14.May 2021

ESG scores are the modern trend in the financial markets, and while this sustainable investing has its critics, it seems to become a regular part of the markets. Frequently, and probably rightfully, ESG is criticized for the lack of commonality across various “scorers”, and as a result, there might be a large dispersion among the score of one firm. The reason is that the score usually consists of different metrics and aggregation methodology. Apart from this “long-term” score, investors can easily recognize the “short-term” score, which can be proxied by negative incidents such as pollution, poor social aspects, social or governance scandals and so on. Moreover, these incidents could be more informative about (un)sustainable practice compared to ESG scores. These ESG incidents are studied by the novel research of Simon Glossner (2021). Using incidents news, the author provides interesting results that mainly support proponents of sustainable investing. Poor ESG performance proxied by incidents predicts more incidents in the future, lower profitability which should subsequently spill to negative performance in future. For example, portfolios consisting of negative incidents stocks significantly underperform the market for both US and European stocks. Therefore, this research paper is a compelling addition to the literature that, apart from social aspects, connects ESG also with performance.

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ESG and CEO Turnover

19.December 2020

ESG scores are already well-established, and nobody doubts that the scores affect investors or companies. Investors seem to care more and more about the other aspects of the stocks and not just the profits – the human welfare, ecology or social aspects of our lives. Additionally, numerous researches point out that the the ESG scores can positively affect also the portfolios. However, the novel research by Colak et al. (2020), has examined other implications of the ESG scores: how the ESG affect the CEOs. To be more precise, how the adverse ESG events and subsequent negative media attention affects the longevity of the CEOs. The finding is that negative event significantly increase the probability of the CEO being replaced. Overall, the research paper highlights the importance of ESG scores in the corporate world.

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Stock Price Overreaction to ESG Controversies

23.November 2020

Nobody can doubt that in the recent period, ESG investing has significantly grown and is a staple part of the financial markets. The academic literature has also grown with the popularity of ESG investing. The negative, mixed and positive results for ESG scores in portfolios have evolved, and generally, there is a consent that ESG scoring can be a vital part of the portfolio management process. It can be observed that in the past, the ESG scores were not priced in the equity market and still, the ESG is not priced in the corporate bond market (apart from Europe). Nowadays, the investors react to the ESG scores, but the research paper of Cui and Docherty (2020) has novel insights that investors may react too much to the ESG. Their research shows that investors overreact to the negative ESG events and stocks connected with negative ESG events sharply fall, but the prices have mean-reverting properties. As a result, there is a reversal after bad ESG events. Stocks firstly sharply fall, but then their prices are reverted to the previous values. Therefore, this paper is interesting from the market pricing or efficiency point, but it also can be utilized by a reversal investor.

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ESG Investing in Fixed Income

5.November 2020

Corporate bonds and equities of the same firm should share the same fundamentals, but does this preposition hold for the ESG scores and their implications? In the equity market, there is convincing literature that states that ESG scores lower risks or even can improve the performance of portfolios. However, it was shown that the ESG implications could not be universally applied to all countries and their markets. Novel research by Slimane et al. (2020) examines the role of the ESG in the fixed market. The paper shows that the fixed income market is probably some years behind the equity market, but the ESG is also emerging in the fixed income. The performance of ESG outperformers compared to underperformers is continually rising. In Europe, the difference is already economically significant; the rest of the world seems to lag a little. Therefore, the ESG might have a bright future also in the corporate bond market. So far, the results are promising…

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The Knapsack problem implementation in R

16.October 2020

Our own research paper ESG Scores and Price Momentum Are More Than Compatible utilized the Knapsack problem to make the ESG strategies more profitable or Momentum strategies significantly less risky. The implementation of the Knapsack problem was created in R, using slightly modified Simulated annealing optimization algorithm. Recently, we have been asked about our implementation and the code. The code is commented and probably could be implemented more efficiently (in R or in another programming language). For example, R is more efficient with matrices, but the code would not be that “straightforward”. Lastly, the most important tuning parameter is the temperature decrease (the probability of accepting a new solution is falling with the rising number of iterations).

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