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Linking microblogging sentiments to stock price movement: An application of GPT-4
This paper investigates the potential improvement of the GPT-4 Language Learning Model (LLM) in comparison to BERT for modeling same-day daily stock price movements of Apple and Tesla in 2017, based on sentiment analysis of microblogging messages.
Company classification using machine learning
The recent advancements in computational power and machine learning algorithms have led to vast improvements in manifold areas of research.
Cross-validated covariance estimators for high-dimensional minimum-variance portfolios
The global minimum-variance portfolio is a typical choice for investors because of its simplicity and broad applicability.
Sparsity and Stability for Minimum-Variance Portfolios
The popularity of modern portfolio theory has decreased among practitioners because of its unfavorable out-of-sample performance.
Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets
In our paper we analyze the relationship between the day-ahead electricity price of the Energy Exchange Austria (EXAA) and other day-ahead electricity prices in Europe.
Efficient Modeling and Forecasting of the Electricity Spot Price
The increasing importance of renewable energy, especially solar and wind power, has led to new forces in the formation of electricity prices.
