Objective: Verify the relation between the variables in the Fleuriet model and the electoral result given by the exchange or maintenance of the party of the prefectures under analysis. Methodology: Through logistic regression it is possible to explain or predict the probability of the occurrence of the event under analysis, such event discussed here refers to the exchange of the party, which is a dummy variable that assumes a value of 1 when there is an exchange and zero otherwise, the method of estimation used to obtain the coefficients was based on maximum likelihood. Results: The relationship between the variables of the Fleuriet model and the electoral result given by the exchange or maintenance of the party in the prefectures of the group under analysis. Limitation or implication of the research: It is noteworthy that such research does not allow generalizations, being a study with reduced scope considering only the city halls of the State of Rio de Janeiro that have financial information disclosed. Originality: showing that city halls with better financial situation tend not to change the party, which was observed in the group under analysis considering the election event in 2020.

Changes in global economic environment meant that companies, particularly publicly traded, seek adaptations to global market model, which gives preference to the analysis of stock indicators profitability. In this sense, we carried out a quantitative study, based on data published by Petrobras SA, concerning the balance sheet comprising the period 2009 to 2013. Data analysis was carried out through statistical methods of covariance, correlation and linear regression. Among the findings of the paper, we emphasize that more than prove the good relations between the good historical results, the joint techniques of statistical methods serve as warnings to indicate to managers that something is not going as expected, thus helping the decision to promote a change in internal company policies, specifically in the way of investment allocation.

This article investigates whether the usefulness of fundamentalist signals to predict returns are altered in context of high volatility and also considering the sensitivity of assets to the IVol-BR volatility index. In times of high volatility, investors could make their decisions based on risk aversion and not only on the fundamentals signals of companies. In addition, it is possible to see how different delays in fundamentalist signals are related to future returns. The methodological choice is for estimators in panel data for the analysis of non-financial companies that have shares traded on B3 - Brasil, Bolsa, Balcão – in the period from 2011.3Q to 2018.2Q. The results show evidence of changes in the explanatory capacity of fundamentalist signals in different volatility scenarios, and for different sensitivities to IVol-BR. This finding may impact the decision-making of managers and investors as it enables the design of investment strategies based on fundamentalist signals adhering to different risk scenarios.

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The objective of the present article is to use the Fleuriet dynamic model and the statistical method of multiple regression for financial analysis of Rio de Janeiro cities public accounts. The research is classified as a descriptive study with a documentary approach. Regarding the results of the research, the municipalities were grouped in the types of financial situation proposed by the model, for purposes of classification as to solvency. The statistical method of multiple linear regression was applied and its assumptions duly tested. Thus, it can be affirmed that part of the variation occurred in the scissors balance can be in fact explained by the variables Working Capital and Need of Working Capital. The relevance of this study is to present to municipal managers a viable method for analyzing their balance sheets and predicting unsustainable financial levels. This is an opportunity for improvement in the scope of municipal public management, a sphere of power of extreme importance for society.