Quantitative Credit Risk Modeling and Failure Analytics: A Historical Comparative Discriminant Case Study of Pakistan's Cement Sector
Description
This dataset provides a comprehensive empirical and methodological repository supporting the historical comparative analysis of corporate financial distress and bankruptcy risk within Pakistan's cement sector. Utilizing Edward I. Altman’s pioneering Multiple Discriminant Analysis (MDA) framework, the repository incorporates financial statement variables, weighting coefficients, and sector-specific adaptations ($Z_1$, $Z_2$, $Z_3$, and $Z_4$) to evaluate industrial solvency.Included Research Data Files & Structure:Z-score analysis.docx / Z-score analysis.pdf:Contains the exhaustive methodological framework, theoretical background on Edward Altman’s 1968 study (the original 66-company sample size and 22-to-5 ratio screening), variable specifications ($X_1$ through $X_5$), and sector-specific mapping for public manufacturing, private manufacturing, service sectors, and emerging market credits.Z-score analysis.xlsx:Houses the quantitative financial data models, ratio computations, and historical comparative metrics for selected cement enterprises in Pakistan (including Lucky Cement, D.G. Khan Cement, Kohat Cement, Maple Leaf Cement, and Attock Cement).Z-score analysis.pptx:Presents a structured slide deck summarizing the core diagnostic zones of discrimination (Safe, Grey, and Distress zones) and longitudinal findings across multiple financial reporting periods.Key Methodological Mapping Reference TableFor quick reference by reviewers and dataset users, the underlying analytical mapping utilized across the dataset files is structured as follows:Industry ClassificationPublic StatusApplicable ModelCore Mathematical FormulaSafe ZoneGrey ZoneDistress ZoneManufacturing Public $Z_1$ (Original) $1.2X_1 + 1.4X_2 + 3.3X_3 + 0.6X_4 + 1.0X_5$ $> 2.99$ $1.81 - 2.99$ $< 1.81$ Manufacturing Private $Z_2$ (Model A) $0.717X_1 + 0.847X_2 + 3.107X_3 + 0.42X_4 + 0.998X_5$ $> 2.9$ $1.23 - 2.9$ $< 1.23$ Non-Manufacturing / Service General $Z_3$ (Model B) $6.56X_1 + 3.26X_2 + 6.72X_3 + 1.05X_4$ $> 2.6$ $1.1 - 2.6$ $< 1.1$ Emerging Markets General $Z_4$ $6.56X_1 + 3.26X_2 + 6.72X_3 + 1.05X_4$ $> 2.6$ $1.1 - 2.6$ $< 1.1$