British Journal of Economics, Finance and Management Sciences 37 October 2011, Vol. 2 (1) © 2011 British Journals ISSN 2048-125X Hybrid Financial Analysis Model for Predicting Bankruptcy Gholamreza Jandaghi, Ph.D. Professor, University of Tehran, Iran Reza Tehrani, Ph.D. Associate Professor, University of Tehran, Iran Parvaneh Pirani, M.Sc. University of Tehran, Qom College, Iran Ali Mokhles, M.Sc. University of Shahid Bahonar, Kerman, Iran Abstract The incidence of important bankruptcy cases has led to a growing interest in developing bankruptcy prediction models. Bankruptcy is a defective process and incurs costs on different stakeholders. By this time, several methods have been developed for predicting bankruptcy, including statistical and artificial intelligence techniques. Hybrid models have proven be a promising approach for classification system for predicting bankruptcy. This paper proposes a hybrid financial analysis model including static and trend analysis models to construct and train a back-propagation neural network (BPN) model.BPN model was applied to classify bankrupt and non-bankrupt Iranian firms listed in Tehran stock exchange (TSE) which provides a high predication rate. Sensitivity analysis determines that leverage financial ratio play important role in predicting bankruptcy. Keywords: Financial distress, Hybrid financial analysis, artificial neural network Introduction Prediction and analysis of corporate financial performance is a crucial phenomenon in a developing country like Iran. The health and success of the firms are of widespread concern to policy makers, industry participants, investors, and managers. (O‟Leary, 1998) The prediction of bankruptcy is one of the major activities to audit enterprise risks and/or uncertainties. Business failure can be defined as a situation that a firm cannot pay lenders, preferred stock shareholders, and suppliers, a bill is overdraw, or the law makes the firm go bankruptcy (Dimitras, Zanakis, & Zopounidis, 1996). Bankruptcy is a defective process which disturbs utilization of investment opportunity and waste resources. Bankruptcy incurs costs on beneficiary as investing bank, stakeholders, debtors, and business partner and company staff. Bankruptcy is not an impulsive outcome and it grows constantly in stages. Thus, the development of financial analysis models to predict business failures can be thought of as „early warning systems‟, which proves to be very helpful for managers, and relevant authorities who can prevent the occurrence of failures. (Atiya, 2001) In addition, these models are able to assist the decision-makers of financial institutions to evaluate, assess and select the firms to collaborate with or invest in (Ahn,Cho, & Kim, 2000; Balcaen & Ooghe, 2006, Etemaid,et.al 2009)