The scale of entrepreneurial ecosystems (EE) assesses the perceptions about entrepreneurial ecosystem domains, finances, capital finances, support, support professions, policies, markets, human resources, and culture. The scales are always error-prone—these scales must possess properties that enable them it to provide maximum information and validity reliability. Convenient sampling data from (n = 474) founders, co-founders, and entrepreneurs were collected. The IRT-GRM model is used to validate and test the instrument-based on polytomous scales. IRT yields discriminating power—the level of difficulty of the items of the scale. The scale consists of 48 items. The item Pol5 (4.13) was found to have the highest discriminating value (4.13), the item mar5 had the lowest discriminating value (1.57), and all items had discriminating values greater than the threshold value of 0.60. The EE Scale showed good reliability based on McDonald’s omega and Cronbach’s alpha (0.80 and 0.88). The parallel and factor analysis showed good agreement of the one-dimesnionality of the scale. The model goodness of fit statistics based on the comparative fit index (CFI) and the Tucker–Lewis index, (TLI) and the standardized root mean square residual (SRMR) showed a satisfactory level of fit; however, the root mean square error of approximation (RMSE) showed a poor fit. The item characteristic curves showed that the all item responses were properly ordered. The items of the scale showed a satisfactory level of discrimination power and level of difficulty, and it was found to have three levels of agreement about entrepreneurial ecosystem scale. It is concluded that the EE scale possesses good psychometric properties and that it is reliable and valid instrument to measure the entrepreneurial ecosystem of the given region.

In this study, the focus is on investigating comovement patterns between eight sectors of companies listed on the Pakistan Stock Exchange. This research aims to use frequency-time bands and multiscale wavelet analysis to enhance portfolio diversification and asset allocation techniques. The results indicate that comovement patterns between pairs of two sectors can be utilized for short-, medium-, and long-term investments, allowing investors to construct portfolios based on their preferred investment horizons. Additionally, the study identifies sectors that are strongly correlated, such as banks-cement, cement-auto, and chemical-auto, where investment is not recommended. The results of the study can be used by policymakers, investors, and fund managers to develop effective portfolio diversification and risk management strategies. It is expected that the findings will contribute to the literature on international finance, providing useful insights into the dynamics of comovements in the Pakistani stock market. By applying the results of this research, investors may be better equipped to navigate the complexities of the stock market, thereby increasing their chances of achieving their investment goals.