Business Process Management

This study investigates the application of machine learning (ML) models in stock market forecasting, with a focus on their integration using PineScript, a domain-specific language for algorithmic trading. Leveraging diverse datasets, including historical stock prices and market sentiment data, we developed and tested various ML models such as neural networks, decision trees, and linear regression. Rigorous backtesting over multiple timeframes and market conditions allowed us to evaluate their predictive accuracy and financial performance.

This database is from a family of studies about the user-perceived quality and functional suitability of DEMO's Process and Fact Models. It includes three different samples. Sample 1 consists of the results from a group of professionals within the urban appraisal area. Sample 2 consists of the results from a group of health professionals. Finally, Sample 3 includes the results from a group of students trained in the DEMO standard.