Monte Carlo simulated stress test scenario on the case of Macedonian logistic companies

Temjanovski, Riste and Dusko, Todeski and Arsova, Monika and Dimitrova, Janka (2022) Monte Carlo simulated stress test scenario on the case of Macedonian logistic companies. Journal of Economics, 7 (1). pp. 19-26. ISSN 1857-9973

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Abstract

Abstract:
In the face of intense business competition in the global market, transport and logistics companies often do not sufficiently analyze the detailed accounting statements for the incurred costs of individual processes, nor do they pay attention to certain scenarios for more successful management of certain unnecessary costs. Numerous scientific
analyzes made by the academic and business sector indicate that companies would realize significant financial benefits, if they had full insight into the financial statements
structured through multiple scenario simulations, which will see possible gains and losses over a period of analysis.
The subject of this paper is to analyze the potential of logistic companies and their performance capacity though the Monte Carlo simulation of the net income values. We present the case of Macedonian logistic companies with the challenge of using the interactive testing environment in Power Bi for goal testing. For the purpose of testing, we generate 1 million data units in two scenarios of 10% increased and decreased net income value. This case was tested on data from year 2020 for Fershped, Kuehne & Nagel and Quehenberger Logistics as a part of Macedonian logistic industry.
The results suggest that results of the simulations are in small favor of the values less than in the 2020. However, if we know that the values in 2020 are continuing a good result from 2019 we can conclude that the results expected for 2021 will results in strong positive values.

Kew words: Macedonian logistic companies, Net income, Monte Carlo scenario, Power BI

Item Type:	Article
Subjects:	Social Sciences > Economics and business
Divisions:	Faculty of Economics
Depositing User:	Monika Arsova
Date Deposited:	28 Feb 2022 10:10
Last Modified:	28 Feb 2022 10:10
URI:	https://eprints.ugd.edu.mk/id/eprint/29535

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