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Forecasts On Some Financial Indicators: A Case Study For S.C.D.A Simnic

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  • Ramona-Maria DIMITROV

    (University of Craiova, Craiova, Romania)

Abstract

In this paper, several financial indicators at S.C.D.A. Simnic are investigated from a statistical point of view. Using the method of least squares, the mathematical functions that model the trend are found and with the help of which financial forecasts are made, also using the growth rates with a chain basis and a fixed basis for the time series corresponding to the period 2008-2022. Finally, an analysis is made of the correlations between these indicators, such as income, expenses, profit, assets, liabilities, stocks, receivables, capital and the results found are interpreted. Thus, the forecasts on the financial indicators and the correlations between them can be of great help in the management of a company, being able to contribute to the efficiency of the activity through adequate budget planning, performance evaluation, investment decision-making or human resources planning. They can help managers identify opportunities and risks, optimize the use of resources, and achieve better financial results for the firm.

Suggested Citation

  • Ramona-Maria DIMITROV, 2023. "Forecasts On Some Financial Indicators: A Case Study For S.C.D.A Simnic," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 185-211, November.
    • Handle: RePEc:aio:manmar:v:xxi:y:2023:i:2:p:185-211
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    References listed on IDEAS

    as
    1. Elena Pesavento & Barbara Rossi, 2006. "Small‐sample confidence intervals for multivariate impulse response functions at long horizons," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1135-1155, December.
    2. Georgi N. Boshnakov & Bisher M. Iqelan, 2009. "Generation Of Time Series Models With Given Spectral Properties," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 349-368, May.
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    More about this item

    Keywords

    financial indicators; forecasts; time series; correlations;
    All these keywords.

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment

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