Adaptive stochastic risk estimation of firm operating profit

Akca, Ahmet; Çanakoğlu, Ethem

doi:10.1007/s40812-021-00184-z

J. Ind. Bus. Econ.

2021

DOI: 10.1007/s40812-021-00184-z

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Adaptive stochastic risk estimation of firm operating profit

Ahmet Akca

Ethem Çanakoğlu

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“…The authors in [11][12][13] note that when creating models and predicting the production and consumption of electricity, noise in the raw data affects the predictive power of models and the quality of forecasts. Stochastic forecasting of risks in business [14], including the risk of operating profit for firms, relies heavily on the assumption of incomplete and noisy data. The authors of [15] point out that when studying the behavior of bank clients by the method of clustering time series, errors and range of the raw data are taken into account.…”

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confidence: 99%

To the question of restoring symbol sequences encoding noisy periodic functions

Zhukova¹,

Ulyanov²

2021

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In business informatics, one of the research subjects is the analysis of data on processes in applied subject areas; here problems of qualitative analysis arise. Such problems arise, for example, in the qualitative study of log files of business processes, in the analysis and prediction of time series and other processes of a different nature. Quite often, to represent information about the processes under study, the methods of qualitative analysis use symbolic coding, which makes it possible to remove unnecessary detailing of numerical descriptions. The relevance of this study is due to the fact that when working with the raw data, researchers often face the presence of noise and distortions of the data, which significantly complicates the solution of the problems of qualitative analysis. When working with symbolic representations of the processes under study, which quite often have a periodic nature, we observe noise of deletion, insertion and replacement of symbols, which complicate the solution of the problem of revealing and analyzing the periodicity. This article deals with the problem of recovering periodic symbolic sequences obtained by coding from samples of continuous periodic functions and distorted by noise of insertion, replacement and deletion of symbols. Trigonometric functions are considered as a specific example of synthetic time series data. To encode trigonometric functions, alphabets of various cardinalities are used. The article presents an experimental study of the dependence of the quality characteristics of the method of period and a periodically repeating fragment recovery, previously proposed by the authors and improved in this study. For alphabets of different cardinalities at fixed sampling intervals, the fraction of sequences with a satisfactorily reconstructed period and the relative error in determining the period are given. The quality of reconstruction of a periodically repeating fragment is estimated by the edit distance from the reconstructed periodic sequence to the original sequence distorted by noise.

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mentioning

confidence: 99%

To the question of restoring symbol sequences encoding noisy periodic functions

Zhukova¹,

Ulyanov²

2021

Bus. Inform.

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Stability of profits and earnings management in the transport sector of Visegrad countries

Klieštik

Sedláčková

Bugaj

et al. 2022

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Research background: Business profit and its stable development are key performance indicators. Many enterprises performed earnings manipulation, either upward or downward, according to the current business and macroeconomic situation, as well as time. These activities may interrupt the stationarity of time series. This article focuses on the transport enterprises, and the assessment of bonds in their earnings. Purpose of the article: The target of the article was to identify the occurrence of non-stationary and its unit root in the EBITDA of transport enterprises for each country in V4 during the period of 2010?2019. Methods: The stationarity and unit roots in time series were tested by the Kwiatkowski, Phillips, Schmidt, and Shin tests and the Augmented Dickey-Fuller based on the samples of 470 Slovak, 405 Czech, 774 Polish, and 1,056 Hungarian. The behavior of earnings manipulation (the first cause of non-stationarity) was indicated by the Modified Jones model. Additional causes for non-stationarity were confirmed by the regression analysis, including factors such as the GDP, unemployment rate, average monthly gross wage, and the Ease of doing business index. Findings & value added: The non-stationarity in the time series of EBITDA was disclosed for each country in the V4 region. Earnings management was discovered to be the cause of this erratic development. Thus, the value-added for the authorities and auditors is to show the association between non-stationary and creative accounting. In addition, purposeful downward manipulation in the transport sector occurs, not upward, which is typical in general. The methodology used in the study may be applied cross-sectorally in emerging countries. The labelling of specific macroeconomic variables depending on the country offers enterprises the opportunity to focus on factors with a crucial influence on their existence and activities.

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Adaptive stochastic risk estimation of firm operating profit

Cited by 2 publications

References 46 publications

To the question of restoring symbol sequences encoding noisy periodic functions

To the question of restoring symbol sequences encoding noisy periodic functions

Stability of profits and earnings management in the transport sector of Visegrad countries

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