PREreview of "Do Technical Indicators Improve Deep Learning Forecasts? An Empirical Ablation Study Across Asset Classes"

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/18778665.

Summary of the Research

This paper looks at how energy companies communicate their ESG information in two places, the European Union and China. The author studies how companies choose between global reporting rules like GRI and SASB, and local rules like the EU CSRD or China's CSDS. The study shows that using global standards does not help companies much anymore because almost everyone uses them. The paper also shows that following strict local rules can improve company performance because it builds trust with local regulators and communities. The author also finds that using too many reporting standards at the same time can confuse investors and hurt company value.

Overall, the paper helps explain how companies can balance investor needs with local expectations. It also introduces the idea that companies should aim for simple and smart reporting instead of using as many standards as possible.

Major Issues

1. The paper uses very complex language and ideas The study is interesting, but the writing is very dense. Readers who are not familiar with ESG rules or economic theory may struggle to follow the argument.

2. The method for coding disclosure choices needs clearer explanation The author says they used manual coding of company reports. It would help to explain more about how this was done and how accuracy was checked.

3. The sample is small Only 25 companies were studied. This limits how much we can generalize the results. The author notes this, but it is still an important concern.

4. The study focuses only on the energy sector The findings may not apply to other industries that face different rules or market pressures.

5. The idea of a complexity penalty needs stronger evidence The inverted U shape is interesting, but more explanation is needed on why the turning point occurs where it does and whether it holds across different types of firms.

Minor Issues

1. Some graphs and tables are hard to read A simpler layout or clearer labeling would help readers understand the results more quickly.

2. The introduction is long The first few pages include many references and details that could be shortened to improve flow.

3. Some terms could be defined earlier For example, terms like strategic interoperability or double materiality may be new to some readers.

4. The paper repeats similar points about signaling and legitimacy Combining these sections could reduce repetition.

5. A few sentences are too long Shorter sentences would improve clarity and make the paper easier to read.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.