NEWSLETTER of May 24, 2024

The following content has been added at finexpert:

EY
CEO OUTLOOK PULSE SURVEY: HOW CEOS JUGGLE TRANSFORMATION PRIORITIES – THE ART OF TAKING BACK CONTROL
There is a clear sense that global CEOs in 2024 are more confident about controlling what they can and managing what they can’t. Resilience has fueled a more positive outlook about their own growth and profitability, and they are more comfortable navigating external challenges outside their own authority. Right now, CEOs are focused on technology, especially artificial intelligence (AI) transformation, as a means to boost productivity and growth. But when they look into the not-too-distant future, their focus shifts to achieving net zero by decarbonizing their business and creating new revenue streams. >more

KPMG
AI IN FINANCIAL REPORTING AND AUDIT: NAVIGATING THE NEW ERA
AI is transforming financial reporting and auditing and is set to dramatically grow with varying levels of speed around the world and across industries – helping businesses create smarter and more joined-up information flows with better identification and response to risk and a much greater ability to detect anomalies and outliers. KPMG’s ‘AI in financial reporting and audit: Navigating the new era’ study of senior executives and business leaders across 1800 companies globally confirms the importance of AI in financial reporting and auditing and clarifies, it is not hype. AI is changing auditing and businesses expect auditors to lead the way. >more

Institut der deutschen Wirtschaft
IW-WOHNINDEX Q1 2024. MIETPREISSTEIGERUNGEN SETZTEN SICH FORT, KAUFPREISE STABILER
The report regularly focuses on general price trends for the purchase and rental market as well as regional evaluations by region type and for the largest German cities. A further chapter takes a closer look at price trends for residential real estate against the backdrop of selected special topics. While the core part of the study concentrates on presenting the results, the final chapter rounds off the study with a classification in terms of real estate economics and housing policy. >more

KfW Research
WETTBEWERBSFÄHIGKEIT – VOM KRANKEN MANN EUROPAS ZUM SUPERSTAR UND ZURÜCK: WO STEHT DIE DEUTSCHE WIRTSCHAFT?
The current gloomy mood among German companies is due to a confusing mix of cyclical factors and structural challenges. A systematic analysis of the relevant business location factors reveals a mixed picture of pronounced strengths and clear weaknesses. Innovative power, an internationally competitive logistics infrastructure and a well-trained labour force continue to be among the strengths. However, demographic change and the clearly negative trend in basic school qualifications threaten to turn this current strength into a weakness. Other weaknesses include relatively low public investment and a high tax burden on companies. In terms of energy supply, Germany is also at a competitive disadvantage due to high costs, particularly in relation to the USA and Canada. Overall, there is an urgent need for action to build on strengths and tackle weaknesses in order to ensure that Germany remains competitive in the future. >more

CAN CHATGPT GENERATE STOCK TICKERS TO BUY AND SELL FOR DAY TRADING?
Sangheum Cho
2024
This paper examines the generative feature of ChatGPT for empirical asset pricing. I show that ChatGPT can generate stock tickers that provide a profitable day trading strategy. Using input prompts as multiple Twitter posts, including both macro and firm-specific news by major news providers, I ask ChatGPT to generate lists of stock tickers to buy and sell. The trading strategy based on the buy and sell lists earns significant long-short returns in open-to-close intraday trading. By asking again about the reason for generating those stock tickers, keywords of ChatGPT’s answer suggest that tech stocks are important for generating the buy lists, whereas sector- or industry-level analysis is important for generating the sell lists. In particular, ChatGPT’s buy and sell lists consist of economically linked stocks through the supply chain, resulting in lower industry concentration than those of their matching groups. The performance is attributable to the stock selection within each industry, the short leg of the strategy, and stronger in the difficult-to-arbitrage stocks, implying that ChatGPT signals’ applicability of extracting mispricing signals in text data. As most of the Twitter data consists of non-firm-specific news, this finding sheds light on the literature by showing that ChatGPT can process a bulk of seemingly non-firm-specific news to generate firm-specific mispricing signals. >more

FINANCIAL STATEMENT ANALYSIS WITH LARGE LANGUAGE MODELS
Alex Kim, Maximilian Muhn, and Valeri V. Nikolaev
2024
We investigate whether an LLM can successfully perform financial statement analysis in a way similar to a professional human analyst. We provide standardized and anonymous financial statements to GPT4 and instruct the model to analyze them to determine the direction of future earnings. Even without any narrative or industry-specific information, the LLM outperforms financial analysts in its ability to predict earnings changes. The LLM exhibits a relative advantage over human analysts in situations when the analysts tend to struggle. Furthermore, we find that the prediction accuracy of the LLM is on par with the performance of a narrowly trained state-of-the-art ML model. LLM prediction does not stem from its training memory. Instead, we find that the LLM generates useful narrative insights about a company's future performance. Lastly, our trading strategies based on GPT's predictions yield a higher Sharpe ratio and alphas than strategies based on other models. Taken together, our results suggest that LLMs may take a central role in decision-making. >more