本文選題：費米分布模型 + 因子分析��； 參考：《會計之友》2017年03期

【摘要】：通過引入一種具有統(tǒng)計學(xué)原理的費米分布模型對企業(yè)財務(wù)狀況進行了預(yù)警實證研究,結(jié)果發(fā)現(xiàn):當(dāng)賦予費米分布模型在財務(wù)預(yù)警領(lǐng)域的物理內(nèi)涵后,一定程度上能夠?qū)斎氲钠髽I(yè)綜合財務(wù)得分值E進行準確預(yù)測,其準確性主要決定于研究樣本費米面E_F的選擇。E_F越接近樣本的實際值,則預(yù)警準確率會顯著提高;同時,獲得具有正、負相關(guān)性的E值對該模型的財務(wù)預(yù)警準確率至關(guān)重要。采用因子分析法和正、負相關(guān)性財務(wù)指標(biāo)算術(shù)和的方法,分別對獲取的E值輸入費米分布模型進行研究,表明采用因子分析法所得的E值由于考慮的企業(yè)財務(wù)指標(biāo)過多過雜,對因子分析法所建模型和費米分布模型的預(yù)警準確率均產(chǎn)生了一定干擾。相比之下,采用正、負相關(guān)性財務(wù)指標(biāo)算術(shù)和得到的E值能夠有效提高費米分布模型的二進制預(yù)警準確率。
[Abstract]:By introducing a kind of Fermi distribution model with statistical principle, this paper makes an empirical study on the financial situation of an enterprise. The results show that: when the Fermi distribution model is endowed with the physical connotation in the field of financial early warning, To a certain extent, it is possible to accurately predict the integrated financial score E of the input enterprise. Its accuracy is mainly determined by studying the selection of sample Feimian ESP. The closer the Estack F is to the actual value of the sample, the higher the early warning accuracy rate will be significantly improved; at the same time, Obtaining E value with positive and negative correlation is very important to the financial early warning accuracy of the model. Using the methods of factor analysis and arithmetic sum of positive and negative correlation financial indexes, the input Fermi distribution model of the obtained E value is studied respectively. The results show that the E value obtained by factor analysis method is too complex because of the excessive financial indexes considered. The early warning accuracy of the model built by factor analysis method and Fermi distribution model is disturbed to a certain extent. By contrast, the arithmetic and E value of positive and negative correlation financial indexes can effectively improve the accuracy of binary early warning of Fermi distribution model.
【作者單位】： 哈爾濱理工大學(xué)經(jīng)濟學(xué)院;
【分類號】：F719;F715.5
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本文編號：1977888