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Прогнозирование прибыли предприятия с помощью мультитрендовой модели

Прогнозирование прибыли предприятия с помощью мультитрендовой модели

Abstract

Применен метод, предложенный В.В.Давнисом, основанный на совместном использовании авторегрессионной модели с фиктивными переменными и мультиномиальной логит-модели для прогнозирования прибыли предприятия. Полученная в результате комбинированная модель позволяет строить прогноз с помощью вероятностного распределения траекторий мультитрендовой модели. На основе данной модели получены прогнозные значения прибыли ОАО «Казанский вертолетный завод».The method proposed by Davnis V.V., was applied for income forecast of Kazan Helicopters Joint Stock Company. The method is based on the joint use of autoregressive model with dummy variable and the model of the expert preferences. A combined model allows to build the forecast with the help of the probability distribution of the trajectories of multitrend model.

Keywords

ПРОГНОЗИРОВАНИЕ, МУЛЬТИТРЕНДОВАЯ МОДЕЛЬ, МУЛЬТИНОМИАЛЬНАЯ ЛОГИТ-МОДЕЛЬ, АВТОРЕГРЕССИОННАЯ МОДЕЛЬ, MULTINOMIAL LOGIT (MNL) MODEL, AUTOREGRESSIVE (AR) MODEL

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold