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    Abstract
2012 (Vol. 4, Issue: 22)
Article Information:

A study on Relation Between Profit and Loss Items with Predictive Ability of Accrual Models for Companies in Tehran Stock Exchange

Reza Imani Mahvar, Mohammad Reza Asgari, Kamran Mahamadi and Roya Darabi
Corresponding Author:  Reza Imani Mahvar 

Key words:  Future cash flow, profit and loss items, volatility of operation profits, volatility of sale, volatility of the rate of inventory at the end of period to next year sale, ,
Vol. 4 , (22): 4711-4717
Submitted Accepted Published
March 30, 2012 April 17, 2012 November 15, 2012
Abstract:

Prediction is an important element in decision making process. As it reflects what is going to happen in future. Financial prediction is of great importance for economic decision making. Necessity for cash flow prediction is undeniable for different economic decision making, as it is a basis for Dividend, interest, liability payment, etc. The present study is aimed to survey the relation between profit and loss items and predictive ability of accrual models. Statistic society is comprised of companies in Tehran Stock Exchange between 2002-2009. Using Cochran formula and presumptions for choosing the participating companies in the study, 88 companies were adopted randomly. First, correlation of models’ errors was calculated using Durbin-Watson test, afterward correlation coefficient and test ‘F’ were applied. In doing so, effects of volatility of the rate of inventory at the end of period to next year sale, along with sale and operation profit volatility were surveyed as an index of changes in business environment on predictive ability of accrual model. Results showed that volatility of the rate of inventory at the end of period to next year sale, sales and operation profits are effective on predictive ability of models and The more volatility, less predictive power.
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  Cite this Reference:
Reza Imani Mahvar, Mohammad Reza Asgari, Kamran Mahamadi and Roya Darabi, 2012. A study on Relation Between Profit and Loss Items with Predictive Ability of Accrual Models for Companies in Tehran Stock Exchange.  Research Journal of Applied Sciences, Engineering and Technology, 4(22): 4711-4717.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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