BANKRUPTCY PREDICTION OF THE ELECTRICAL FIRMS WITHIN IRANIAN ELECTRICITY EXCHANGE: EMPIRICAL EVIDENCE FROM TEHRAN STOCK EXCHANGE

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MAZHARI S.M.; FEREIDUNIAN A.R.; LESANI H.

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Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2013 | Volume:4 | Issue:1 Page(s): 9-24

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Title

BANKRUPTCY PREDICTION OF THE ELECTRICAL FIRMS WITHIN IRANIAN ELECTRICITY EXCHANGE: EMPIRICAL EVIDENCE FROM TEHRAN STOCK EXCHANGE

Author(s)

MAZHARI S.M. | FEREIDUNIAN A.R. | LESANI H. | Issue Writer Certificate

Keywords

STOCK EXCHANGEQ2

INSOLVENCYQ2

FIRMS RELATED TO ELECTRICITY INDUSTRYQ2

ANNUAL FINANCIAL RECORDQ2

Abstract

Electricity exchange is known as the trajectory of power industry restructuring which facilitates achieving a direct fair market and accomplishing the privatization. However, little knowledge about market participants and their decisions may increase the investment risk and affect the economic boom cycle. As the Iranian electricity stock has started working in 2011 and the subscription has been made, it will start its services in near future; so, it would be very helpful to inform the investors about what may happen, and how to direct their portfolio into the satisfactory corridor. One way to arrive capital investment security is to predict INSOLVENCY of a business unit. Predicting the possibility of a company’s INSOLVENCY not only can prevent losing the principle and capital interest of investing, but also facilitates the most important decision makings. This paper proposes a new model for INSOLVENCY prediction of the Iranian electrical firms within future electricity exchange via an artificial bee colony algorithm. To do so, 118 firms among the electrical and energy industrial firms listed in Tehran STOCK EXCHANGE (TSE) are assumed; they are used as training data to find a suitable linear classifier. The introduced algorithm is conducted on 40 test firms and obtained results are discussed in several scenarios.

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APA: Copy

MAZHARI, S.M., FEREIDUNIAN, A.R., & LESANI, H.. (2013). BANKRUPTCY PREDICTION OF THE ELECTRICAL FIRMS WITHIN IRANIAN ELECTRICITY EXCHANGE: EMPIRICAL EVIDENCE FROM TEHRAN STOCK EXCHANGE. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 4(1), 9-24. SID. https://sid.ir/paper/202938/en

Vancouver: Copy

MAZHARI S.M., FEREIDUNIAN A.R., LESANI H.. BANKRUPTCY PREDICTION OF THE ELECTRICAL FIRMS WITHIN IRANIAN ELECTRICITY EXCHANGE: EMPIRICAL EVIDENCE FROM TEHRAN STOCK EXCHANGE. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2013;4(1):9-24. Available from: https://sid.ir/paper/202938/en

IEEE: Copy

S.M. MAZHARI, A.R. FEREIDUNIAN, and H. LESANI, “BANKRUPTCY PREDICTION OF THE ELECTRICAL FIRMS WITHIN IRANIAN ELECTRICITY EXCHANGE: EMPIRICAL EVIDENCE FROM TEHRAN STOCK EXCHANGE,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 4, no. 1, pp. 9–24, 2013, [Online]. Available: https://sid.ir/paper/202938/en

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