Business Perspectives and Research, Ahead of Print.
Stock market forecasting has always piqued the interest of a wide range of investors, practitioners, and researchers. Stock prediction is a complex process due to the presence of an inherent noisy and volatile environment. The stock market’s movement is influenced by a variety of factors. The study of ANN models began in 1969, “when Minsky and Papert discovered two critical flaws in the Artificial Neural Network technique. The first was the machine’s ability to solve complex problems, and the second was the computers’ inability to run large ANN models efficiently”. The study aims to forecast the Nifty 50 using macroeconomic factors as input variables in the two sub-periods, that is, pre-COVID (February 2018–February 2020) and during COVID (March 2020–December 2021). A model trained using the LM algorithm was used for predicting the NSE’s flagship index Nifty 50. The findings reveal that the LM algorithm achieved 95.18% accuracy in predicting the Nifty 50 in the pre-COVID scenario. Whereas during COVID period, the proposed ANN model achieved 94.21% accuracy. The empirical results have important implications for every class of investors, such as FIIs, DIIs, retail investors, and so on.

Business Perspectives and Research, Ahead of Print.
The provincial competitiveness index (PCI) serves as an important measure for the efforts of localities in Vietnam in improving the business environment. However, the methodology of PCI excludes the influence of the traditional conditions on business growth, only measuring the “net” competitiveness at the provincial level. This study is conducted (1) to supplement the approach to measure the relation between the improvement of the business environment and the changes in the business results of the enterprises; at the same time and (2) to pay attention to factors that have been excluded in the PCI methodology. Measuring technical efficiency (TE) by data envelopment analysis, fixed effect model, and random effect model are employed to achieve these research objectives. The findings show that the impact of PCI to business growth has a lag of approximately 1 year. Furthermore, in the TE approach, the business growth indicators are affected not only by the improvement of the business environment created by the local government but also by the basic conditions of that locality. This approach seems to be “fair” across localities, especially those with low starting points. This theoretical approach, however, also needs to be further complemented, especially regarding data, to overcome its potential limitations.