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JAQM Volume 16, Issue 4 - December 30, 2021
Contents
LDA vs PCA in analyzing companies with OFC activity
Alexandra Georgiana SIMA, Gheorghe HURDUZEU, Stefan Alexandru IONESCU
Continuing previous research and aiming to build a system of indicators and risk assessment procedures for companies operating in CFOs, we have extracted and processed financial data for the years 2017-2019 for approximately 8300 companies in over 40 jurisdictions. The data has been processed so that values can be compared, regardless of jurisdiction, currency, or accounting standard. Given the fact that we follow companies from several industries, for a period of more than a year, we chose to use financial data that can be found for as many companies as possible, just to be able to obtain a sufficiently large sample. We performed the PCA analysis using the covariance matrix. The first two principal components preserve about 76% of the variance of the initial causal space, and if we add the third, we have over 84% of the initial information. Next, we employed LDA techniques in order to determine which of the selected indicators provides a better classification of the companies selected in the analysis. Last but not least, we were able to make predictions about the membership of new companies, based on the built model.
Some insights regarding fraud at the baccalaureate exam in Romania
Octavian CEBAN, Ionela-Roxana PETCU, Andreea MIRICA, Roxana-Violeta PARTAS-CIOLAN
Fraud as a deceptive act is observed in a multitude of scenarios, the baccalaureate exams not being bypassed. Our research aims to provide insights into fraud tentative cases at the Baccalaureate exam in Romania based on a quantitative approach using microdata from 2021. How many students attempt fraud at the baccalaureate exam grouped by academic and demographic factors and what are the main aspects that influence the likelihood of fraud attempt are the topics explored in this paper. Author based computations and several logistic regression models are constructed, indicating that males, compared to females, have a higher probability to be expelled from the exam, and rural candidates are more likely to attempt fraud. In 2021, the technical maths exam remains the subject with the highest probability to be removed from exam due to fraud.
Modelling and forecasting the inflation rate in Romania in the post-pandemic period. A comparative analysis of different univariate and multivariate forecasting methods
Eduard Mihai MANTA
The pandemic context triggered globally affected Romania from several points of view including an inflationary wave, observed throughout Europe, reaching in November, an annual level of 7.8%. Given this context, as well as that of the outbreak of the war between Russia and Ukraine, the main purpose of this paper is to model and forecast the inflation rate in Romania based on univariate forecast models, such as SARIMA, the Holt-Winters exponential smoothing model, ETS model, but also based on multivariate models, such as the VAR model. To identify the most appropriate model to forecast future inflation rate values, it was taken into account the period January 2000 - December 2021.