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The prediction of stock market (SM) indices is a fascinating task. An in-depth analysis in this field can provide valuable information to investors, traders and policy makers in attractive SMs. This article aims to apply a correlation feature selection model to identify important technical indicators (TIs), which are combined with multiple deep learning (DL) algorithms for forecasting SM indices.

The methodology involves using a correlation feature selection model to select the most relevant features. These features are then used to predict the fluctuations of six markets using various DL algorithms, and the results are compared with predictions made using all features by using a range of performance measures.

The experimental results show that the combination of TIs selected through correlation and Artificial Neural Network (ANN) provides good results in the MADEX market. The combination of selected indicators and Convolutional Neural Network (CNN) in the NASDAQ 100 market outperforms all other combinations of variables and models. In other markets, the combination of all variables with ANN provides the best results.

This article makes several significant contributions, including the use of a correlation feature selection model to select pertinent variables, comparison between multiple DL algorithms (ANN, CNN and Long-Short-Term Memory (LSTM)), combining selected variables with algorithms to improve predictions, evaluation of the suggested model on six datasets (MASI, MADEX, FTSE 100, SP500, NASDAQ 100 and EGX 30) and application of various performance measures (Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error(RMSE), Mean Squared Logarithmic Error (MSLE) and Root Mean Squared Logarithmic Error (RMSLE)).

This paper aims to contribute to the existing literature in the field of hospital governance by exploring the relationship between the attributes and performance of hospital boards and hospital performance in terms of quality of healthcare.

A survey of board performance in public hospitals in Morocco was carried out, in which we surveyed all board members of the 13 hospitals in the Casablanca-Settat region. A total of 82 members responded (82% response rate) to the previously adapted and validated self-evaluation questionnaire on board self-assessment questionnaire (BSAQ) board member performance.

On average, the hospital boards studied had eight members. In terms of clinical expertise, half the members were physicians and 17% were nurses. In addition, positive correlations were found between certain board characteristics, notably age, seniority, members' perceptions of their impact on the quality of healthcare and several dimensions of board performance. In parallel, the results showed strong and significant associations between turnover rate and BSAQ score. Negative correlations were also found between average length of stay and BSAQ score. With regard to mortality parameters, it should be noted that we were unable to establish a strong empirical correlation between hospital boards' self-assessed performance and other hospital mortality indicators.

The present study offers a rigorous rationale for the use of the French-translated BSAQ in the hospital context, and we hope that others will use this tool in future work within the framework of evidence-based research. In addition, the BSAQ tool’s focus on board competencies (and not just structure, composition or processes) provides valuable insights into what boards need to learn in order to function effectively. However, despite the insistence of the authors of this study on the need for a comprehensive census of public hospital board members in the region, several obstacles were encountered. Firstly, there were difficulties related to vacancies within the hospitals, which had the effect of restricting the representativeness of the sample. Secondly, access to hospital board members proved complex due to their busy schedules and the confidential nature of their meetings. Finally, it is important to note that national performance indicators in Morocco may not be as reliable as in other countries, which could complicate the identification of high-performing hospital systems and, consequently, make inference difficult.

This study provides large-scale empirical evidence of processes related to the governance of quality of healthcare and elucidates the existence of an association between hospital board performance and clinical performance. The use of validated tools such as the BSAQ should therefore help improve the performance of boards and governance in public hospitals.