Adaptive stochastic risk estimation of firm operating profit

Ahmet Akca () and Ethem Çanakoğlu ()
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Ahmet Akca: Bahçeşehir University
Ethem Çanakoğlu: Bahçeşehir University

Economia e Politica Industriale: Journal of Industrial and Business Economics, 2021, vol. 48, issue 3, No 7, 463-504

Abstract: Abstract This paper presents an adaptive stochastic approach to model and estimate the risk measures of the operating profit of a non-financial business. On the one hand, exogenous financial market variables specific to a country, including foreign exchange, interest, and inflation rates, are stochastically modeled via ARCH/GARCH, Vasicek, and regime-switching mean-reverting processes, respectively. Then, the dependency among all financial variables is captured via a residual Student-t copula. On the other hand, as opposed to traditional business planning whereby a few discrete base/best/worst-case scenarios are developed through a limited number of fixed models, nine distinct revenue and five non-revenue models, including ARIMA, principal component analysis (PCA), and principal component regression (PCR) are introduced to be adaptively selected to calculate the operating profit of a business. Finally, the stochastic exogenous financial market and operating profit model of the business are integrated to estimate various risk measures, including the CVaR, of the operating profit. The paper concludes with a case study on the adaptive generation of a stochastic business operating model and estimation of risk measures of the operating profit of a sample, publicly-traded corporation.

Keywords: Multivariate time series analysis; Stochastic processes; Skewed-t GARCH; Residual Student-t copula; CVaR; Business modeling (search for similar items in EconPapers)
JEL-codes: C53 C63 F37 G17 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40812-021-00184-z

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