چکیده:
ﻣﻄﺎﻟﻌﺎت ﭘﻴﺸﻴﻦ ﻧﺸﺎن دادهاﻧﺪ ﻛﻪ ﭘﻴﺶﺑﻴﻨﻲ ﻣﻮﻓﻘﻴﺖ ﻳﺎ ﻋﺪم ﻣﻮﻓﻘﻴﺖ ﻣﺎﻟﻲ ﺷﺮﻛﺖ ﻫـﺎﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﻧﺴﺒﺖ ﻫﺎی ﻣﺎﻟﻲ1 آﻧﻬﺎ اﻣﻜﺎن ﭘﺬﻳﺮ اﺳﺖ و اﻟﮕـﻮﻫـﺎی رﮔﺮﺳـﻴﻮﻧﻲ ﺑـﻪ ﻋﻨـﻮاناﺑﺰارﻫﺎی ﺗﺨﻤﻴﻦ، ﻛﺎرآﻣﺪی ﺧﻮد را اﺛﺒﺎت ﻛﺮدهاﻧﺪ. وﻟﻲ اﻳﻨﻜﻪ ﻛﺪام اﻟﮕﻮ و روش ﺗﺨﻤـﻴﻦدر ﺷﺮاﻳﻂ ﻣﺨﺘﻠﻒ ﭘﺎﺳﺨﮕﻮ اﺳﺖ ﺑﻪ ﻋﻨﻮان ﻣﻮﺿﻮع اﻳـﻦ ﭘـﮋوﻫﺶ، ﻣـﻮرد ﺑﺮرﺳـﻲ ﻗـﺮار ﮔﺮﻓﺘﻪ اﺳﺖ. 2ﻫﺪف اﻳﻦ ﺗﺤﻘﻴﻖ ﺑﺮرﺳﻲ ﻛﺎراﻳﻲ دو اﻟﮕـﻮی ﺗﺤﻠﻴـﻞ رﮔﺮﺳـﻴﻮن ﻟﻮﺟﻴـﺖ و ﺗﺤﻠﻴـﻞ * اﺳﺘﺎدﻳﺎر داﻧﺸﮕﺎه آزاداﺳﻼﻣﻲ، واﺣﺪ ﺗﻬﺮان ﻣﺮﻛﺰی، ﻧﻮﻳﺴﻨﺪه اﺻﻠﻲ و ﻣﺴﺌﻮل ﻣﻜﺎﺗﺒﺎت. ** اﺳﺘﺎدﻳﺎر داﻧﺸﮕﺎه آزاد اﺳﻼﻣﻲ، واﺣﺪ ﺗﻬﺮان ﻣﺮﻛﺰی. *** ﻛﺎرﺷﻨﺎس ارﺷﺪ ﺣﺴﺎﺑﺪاری ﺗﻬﺮان ﻣﺮﻛﺰی.1. Financial Ratio2. Logit Analysis Regression69 ................................................................................. ﭘﮋوﻫﺸﻨﺎﻣﻪ ﺣﺴﺎﺑﺪاری ﻣﺎﻟﻲ و ﺣﺴﺎﺑﺮﺳﻲﻣﻤﻴﺰی ﭼﻨﺪ ﻣﺘﻐﻴﺮه1 ﺟﻬﺖ ﭘﻴﺶﺑﻴﻨﻲ ﻣﻮﻓﻘﻴﺖ ﻳﺎ ﻋﺪم ﻣﻮﻓﻘﻴﺖ ﺷﺮﻛﺖ ﻫﺎ اﺳﺖ. ﺑﺎ ﺗﻮﺟـﻪﺑﻪ ﻫﺪف ﺑﻴﺎن ﺷﺪه ﺑﻪ دﻧﺒﺎل آزﻣﻮن ﻓﺮﺿﻴﻪ » ﻛﺎراﻳﻲ دو روش رﮔﺮﺳﻴﻮن ﻟﻮﺟﻴﺖ و ﺗﺤﻠﻴﻞﻣﻤﻴﺰی در ﺗﺸﺨﻴﺺ ﺗﻮاﻧﻤﻨﺪی ﻣﺎﻟﻲ ﺷـﺮﻛﺖ ﻫـﺎ ﺗﻔـﺎوت ﻣﻌﻨـﺎداری دارﻧـﺪ و رﮔﺮﺳـﻴﻮن ﻟﻮﺟﻴﺖ ﻛﺎراﺗﺮ و ﺗﻮاﻧﻤﻨﺪﺗﺮ از اﻟﮕﻮی ﺗﺤﻠﻴﻞ ﻣﻤﻴﺰی اﺳﺖ « ﻫﺴﺘﻴﻢ.در اﻳﻦ ﺗﺤﻘﻴﻖ دادهﻫﺎی ﻣﺮﺑﻮط ﺑﻪ 21 ﻧﺴﺒﺖ ﻣﺎﻟﻲ در ﺷﺮﻛﺖ ﻫﺎی ﻧـﺎﻣﻮﻓﻖ )ﺑﺮاﺳـﺎسﻣﺎده 141( و ﺷﺮﻛﺖ ﻫﺎی ﺧﺎرج ﺷﺪه از ﺑﻮرس، ﻫﺮﻛﺪام در ﻣﻘﺎﺑﻞ ﺷﺮﻛﺖ ﻫﺎی ﻣﻮﻓﻖ دراﻟﮕﻮﻫﺎی ﻟﻮﺟﻴﺖ و ﺗﺤﻠﻴﻞ ﻣﻤﻴﺰی ﻗﺮار ﮔﺮﻓﺘﻪ و ﺗﺨﻤﻴﻦ زده ﺷﺪهاﻧﺪ و در ﻧﻬﺎﻳـﺖ ﻧﺘﻴﺠـﻪﮔﺮﻓﺘﻪ ﺷﺪ ﻛﻪ ﺑﺎ دادهﻫﺎی ﻣﺮﺑﻮط ﺑﻪ ﻳﻚ ﺳﺎل ﻗﺒﻞ از ﺳـﺎل ﻣﺒﻨـﺎ، اﻟﮕـﻮی ﺗﺤﻠﻴـﻞ ﻣﻤﻴـﺰیﻛﺎرآﻣﺪﺗﺮ ﻋﻤﻞ ﻣﻲﻛﻨﺪ و ﺑﺎ دادهﻫﺎی دو ﺳﺎل ﻗﺒﻞ از ﺳﺎل ﻣﺒﻨﺎ اﻟﮕـﻮی ﻟﻮﺟﻴـﺖ ﻛﺎرآﻣـﺪﺗﺮ ﻋﻤﻞ ﻣﻲﻛﻨﺪ؛ وﻟﻲ در ﻣﺠﻤﻮع ﺗﻔﺎوت ﻣﻌﻨﺎداری ﺑﻴﻦ اﻳﻦ دو اﻟﮕﻮ وﺟﻮد ﻧﺪارد.
Previous studies have shown that predicting the success or failure companies is possible by deriving financial ratios and regression models as proven effective estimation tools. Thereof defining the accountable model types and estimation methods in different conditions is the subject of this research.
To assess the performance of the Logit and Multi Discriminant analysis to predict the success or failure of companies is the main purpose of this study. With the expressed purpose, we want to test the following hypothesis: "There is no significant difference in the performance of the Logit and Multi Discriminant analysis. However, logit models are more efficient and capable than multi discriminant models”.
In this study, two models (Logit and multi discriminant) were estimated by using 12 calculated financial ratios related to the failure of companies (article 141, omitted from the bourse) and finally, concluded:
The Multi Discriminant model is more efficient than logit with data for one year before the base year. Logit model is, however, more efficient than Multi Discriminant with data for two years before the base year, but in total, there is no significant difference between the two models
خلاصه ماشینی:
ﺟﺪول 4- ﻣﺤﺎﺳﺒﻪ دﻗﺖ اﻟﮕﻮی ﻻﺟﻴﺖ ﺑﺮای ﺷﺮﻛﺖ ﻫﺎی ﻧﺎﻣﻮﻓﻖ ﻣﺎده 141 در ﻣﻘﺎﺑﻞ ﺷﺮﻛﺖ ﻫﺎی ﻣﻮﻓﻖ - ﻳﻚ ﺳﺎل ﻗﺒﻞ از ﺳﺎل ﻣﺒﻨﺎ ﮔﺮوه ﭘﻴﺶﺑﻴﻨﻲ ﺷﺪه ﮔﺮوه ﭘﻴﺶﺑﻴﻨﻲ ﺷﺪه اﻟﮕﻮ ﺑﺎ روش اﻟﮕﻮ ﺑﺎ روش درﺻﺪ دﻗﺖ ﮔﺮوه درﺻﺪ ﺗﻌﺪاد ﭘﻴﺶروﻧﺪه ﭘﻴﺶروﻧﺪه ﻛﻠﻲ اﮔﻮ در ﭘﻴﺶ ﻛﻞ ﻛﻞ ﻧﻤﻮﻧﻪ اﺻﻠﻲ ﻓﺮض درﺻﺪ درﺻﺪ ﺗﻌﺪاد ﺗﻌﺪاد ﻣﻮﻓﻖ ﻧﺎﻣﻮﻓﻖ ﻣﻮﻓﻖ ﻧﺎﻣﻮﻓﻖ 001 3/31 7/68 03 4 62 ﻧﺎﻣﻮﻓﻖ 3/88 001 09 01 03 72 3 ﻣﻮﻓﻖ 06 - ﻣﻨﺒﻊ: ﻳﺎﻓﺘﻪﻫﺎی ﭘﮋوﻫﺸﮕﺮ ﺑﺮرﺳﻲ ﻛﺎراﻳﻲ اﻟﮕﻮ ﻟﻮﺟﻴﺖ و ﺗﺤﻠﻴﻞ ﺗﻤﺎﻳﺰی ﭼﻨﺪ ﻣﺘﻐﻴﺮه در ﭘﻴﺶﺑﻴﻨﻲ وﺿﻌﻴﺖ ...
ﭘﮋوﻫﺸﻨﺎﻣﻪ ﺣﺴﺎﺑﺪاری ﻣﺎﻟﻲ و ﺣﺴﺎﺑﺮﺳﻲ ﺟﺪول 6- ﻣﺤﺎﺳﺒﻪ دﻗﺖ اﻟﮕﻮی ﻻﺟﻴﺖ ﺑﺮای ﺷﺮﻛﺖ ﻫﺎی ﻧﺎﻣﻮﻓﻖ ﻣﺎده 141 در ﻣﻘﺎﺑﻞ ﺷﺮﻛﺖ ﻫﺎی ﻣﻮﻓﻖ - دو ﺳﺎل ﻗﺒﻞ از ﺳﺎل ﻣﺒﻨﺎ ﮔﺮوه ﭘﻴﺶﺑﻴﻨﻲ ﺷﺪه ﮔﺮوه ﭘﻴﺶﺑﻴﻨﻲ ﺷﺪه اﻟﮕﻮ ﺑﺎ روش اﻟﮕﻮ ﺑﺎ روش درﺻﺪ دﻗﺖ ﮔﺮوه درﺻﺪ ﭘﻴﺶروﻧﺪه ﭘﻴﺶروﻧﺪه ﻛﻠﻲ اﮔﻮ در ﺗﻌﺪاد ﻛﻞ ﭘﻴﺶ ﻛﻞ ﻧﻤﻮﻧﻪ اﺻﻠﻲ ﻓﺮض درﺻﺪ درﺻﺪ ﺗﻌﺪاد ﺗﻌﺪاد ﻣﻮﻓﻖ ﻧﺎﻣﻮﻓﻖ ﻣﻮﻓﻖ ﻧﺎﻣﻮﻓﻖ 001 3/3 7/69 03 1 92 ﻧﺎﻣﻮﻓﻖ 7/69 001 7/69 3/3 03 92 1 ﻣﻮﻓﻖ 06 - ﻣﻨﺒﻊ: ﻳﺎﻓﺘﻪﻫﺎی ﭘﮋوﻫﺸﮕﺮ ﺟﺪول 6 ﻧﺸﺎن ﻣﻲدﻫﺪ ﻛﻪ ﻳﻚ ﺷﺮﻛﺖ ﻧﺎﻣﻮﻓﻖ ﺗﻮﺳﻂ اﻟﮕﻮ ﺑﻪ ﻋﻨـﻮان ﺷـﺮﻛﺖ ﻣﻮﻓـﻖ ﻃﺒﻘﻪﺑﻨﺪی ﺷﺪه اﺳﺖ ﻛﻪ ﻧﺸﺎن ﻣﻲدﻫﺪ ﺧﻄﺎی ﻧﻮع اول اﻟﮕﻮ ﻣﻌﺎدل 3/3 درﺻﺪ و ﺧﻄـﺎی ﻧﻮع دوم اﻟﮕﻮ 3/3 درﺻﺪ اﺳﺖ.