scholarly journals Risk Management and Airline Sector by Using Financial Ratios - An Application

2017 ◽  
Author(s):  
Burcu Sakız
Keyword(s):  
Airline Industry ◽  
Financial Risk ◽  
Evaluation Model ◽  
Financial Ratios ◽  
Financial Status ◽  
Intense Competition ◽  
Airline Passenger ◽  
Cargo Transportation ◽  
International Airlines ◽  
Risk Evaluation Model

The growing airline transportation in the world and Turkey in recent years has increased the importance of airline passenger and cargo transportation operations and has brought intense competition in the domestic and international airlines market. Under intense competition, it is of utmost importance to capture the sustainable success of an ever-evolving and growing market by accurately assessing the financial performance and risks of businesses. In addition to the financial ratios generally used in all sectors, a number of indicators specific to the airline industry are used to assess the financial status of companies operating in the airline industry. These ratios and indicators will be calculated to compare for past periods and years, to assess risks for the future, to make forecasts, to report, to be able to see the financial status of the business concerned and to plan and make decisions in a more healthy and accurately. In this paper, after literature review, one of the most important financial risk evaluation model Altman Z’’ score is examined and an application with Turkish Airlines’ quarterly last 3 years financial data is evaluated.

A NOVEL FIVE-CATEGORY LOAN-RISK EVALUATION MODEL USING MULTICLASS LS-SVM BY PSO

2012 ◽  
Vol 11 (04) ◽  
pp. 857-874 ◽  
Author(s):  
JIE CAO ◽  
HONGKE LU ◽  
WEIWEI WANG ◽  
JIAN WANG
Keyword(s):  
Financial Regulation ◽  
Evaluation Model ◽  
Least Square ◽  
Support Vector ◽  
Accuracy Rate ◽  
Rural Credit ◽  
Proposed Model ◽  
Loan Risk ◽  
Regulation Approach ◽  
Risk Evaluation Model

Five-category loan classification (FCLC) is an international financial regulation approach. Recently, the application and implementation of FCLC in the Chinese microfinance bank has mostly relied on subjective judgment, and it is difficult to control and lower loan risk. In view of this, this paper is dedicated to researching and solving this problem by constructing the FCLC model based on improved particle-swarm optimization (PSO) and the multiclass, least-square, support-vector machine (LS-SVM). First, LS-SVM is the extension of SVM, which is proposed to achieve multiclass classification. Then, improved PSO is employed to determine the parameters of multiclass LS-SVM for improving classification accuracy. Finally, some experiments are carried out based on rural credit cooperative data to demonstrate the performance of our proposed model. The results show that the proposed model makes a distinct improvement in the accuracy rate compared with one-vs.-one (1-v-1) LS-SVM, one-vs.-rest (1-v-r) LS-SVM, 1-v-1 SVM, and 1-v-r SVM. In addition, it is an effective tool in solving the problem of loan-risk rating.

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