Abstract
Conventional financial management methods, based on extrapolation approaches to financial analysis, often reach their limits due to violations of stationary controlled financial variables, for example, interventions in the economy and social life necessary to manage the COVID-19 pandemic. Therefore, we have created a procedure for controlling financial quantities, which respects the non-stationarity of the controlled quantity using the maximum control deviation covering the confidence interval of a random variable or random vector. For this interval, we then determined the algebraic criteria of the transfer functions using the Laplace transform. For the Laplace transform, we determined the theorem on the values of the stable roots of the characteristic equation, including the deductive proof. This theorem is directly usable for determining the stability of the management for selected financial variables. For the practical application, we used the consistency of the stable roots of the characteristic equation with the Stodola and Hurwitz stability conditions. We demonstrated the procedure for selected quantities of financial management in food production. In conclusion, we proposed a control mechanism for the convergence of regulatory deviation using a combination of proportional and integration schemes. We also determined the diversification of action interventions (into development, production, and marketing) using a factorial design.
Highlights
Long-term reliable creditworthiness models and financial analysis models [1,2] or regression of economic variables using factor analysis [3,4] or data envelopment analysis [5,6] are often replaced by financial management models less sensitive to the non-stationarity of the development of controlled variables
Shewart’s control algorithm [9,10] or the control of stochastic systems using Markov’s transitions [11,12] are used to a limited extent. Another area for regulating financial variables in non-stationary conditions is the solution based on creating distributions of random variables of the extreme type [13,14,15,16]
The dynamic system described by equation [20], is asymptotically stable according to [21,22] when the Stodola stability condition is met and all major minors of the Hurwitz matrix Hi are positive: det Hi > 0; i = 1, 2, . . . , n
Summary
Long-term reliable creditworthiness models and financial analysis models [1,2] or regression of economic variables using factor analysis [3,4] or data envelopment analysis [5,6] are often replaced by financial management models less sensitive to the non-stationarity of the development of controlled variables. These are control proposals using state learning and neural networks of artificial intelligence [5,6] and/or control systems of nonlinear systems using the description of symptomatic balance defined by A.
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