An empirical investigation on ranking financial risk factors using AHP method

Article history: Received December 28, 2013 Accepted 10 April 2014 Available online April 14 2014 This paper determines and ranks financial risk factors in Iranian corporations, using analytical hierarchy process (AHP). The present research includes one main question and four subquestions. Its universe population includes managers, production and financial personnel of great corporations activating in Tehran Stock Exchange, who were selected to explain importance and weight of economic risks indices. The source of great corporations recognition is the Companies Registration Organization in Tehran Province, and according to this, there are 120 corporations. The results have indicated that financing risk maintains the highest priority followed by credit risk, liquidity risk, inflation risk and exchange risk. In terms of different risks associated with financing risk, risk of profit per share has been the number one priority followed by the risk of divisional profit per share, the risk of recessionary or boom and the risk of increasing partial pay profit rate. In terms of credit risk, the risk of loan has been number one priority followed by the risk of inability of loan payment and interest payment. Liquidity risk is another risk factor where demand has been the most important factor followed by rules and regulations and inflation risk. In terms of inflation, producers price risk has been the most important factor followed by consumer price risk, gross domestic product and producers price risk. Finally, in terms of different factors influencing exchange risk, export related issues are considered as the most important factors. © 2014 Growing Science Ltd. All rights reserved.


Introduction
One of the primary concerns on business development is to reduce any possible risk factors on big firms whose shares are also listed on stock exchange (Short, 1984;Christoffersen & Gonçalves, 2004).There are literally various studies concentrated on risk assessment.Some newly established information technology based firms are heavily influenced by various risk factors (Licht & Nerlinger, 1998).Pongsakdi et al. (2006), for instance, studied the financial risk aspects associated with the purchase of crude oil.They determined how to purchase and decide on the production level of various products given forecasts of demands and they examined their model using data from the Refinery owned by the Bangchak Petroleum Public Company Limited, Thailand.Many risk assessment methods are involved with multiple criteria decision making techniques (Wang & Lee, 2007;Shih et al., 2007) such as analytical hierarchy process (AHP) (Saaty, 2004), analytical network process (ANP) (Saaty, 2004), etc. Lee et al. (2008) proposed an approach based on the fuzzy AHP (FAHP) and balanced scorecard (BSC) for assessing an information technology (IT) department in the manufacturing industry in Taiwan.The BSC concept was implemented to describe the hierarchy with four major BSC perspectives, namely financial, customer, internal business process, and learning and growth.They also used FAHP to handle vagueness and ambiguity of information.Stoneburner et al. (2002) also provided a comprehensive method for assessing different risk components on the market.Belk and Edelshain (1997) investigated the existing evidence from empirical surveys of foreign exchange risk and its management to confirm or to reject theoretical predictions and the truth of some paradox, and suggested a rationale for its existence.Raz and Michael (2001) identified some tools, which are most widely applied and those that are associated with successful project management in general, and with project risk management.Using a questionnaire the study tried to find which tools are more likely to be applied in those organizations that report better project management performance and in those that value the contribution of risk management processes.Cooper et al. (2014) proposed a mathematical tool to assess relative risk tolerance using Data Envelopment Analysis (DEA).Using a questionnaire in four groups including propensity, attitude, capacity, and knowledge, they surveyed over 180 individuals their responses were analyzed using the Slacks-based measure type of DEA efficiency model.They reported that the multidimensionality of risk must be taken into account for complete assessment of risk tolerance.This approach also provided some insight into the relationship between risk, its elements and other variables.Specifically, the perception of risk changes by gender as men were generally less risk averse than women.Risk attitude and knowledge scores were consistently lower for women, while there was no statistical difference in their risk capacity and propensity compared to men.The tool can also serve as a "risk calculator" for an appropriate and defensible method to reach legal compliance requirements, known as the "Know Your Client" rule, that exist for Canadian financial institutions and their advisors.

The proposed method
In this research, a fuzzy model was used, so its results is not generalizable.Therefore, random sampling was not used and the research concluding is descriptive.Our data were gathered based on expert interviewing, therefore this research plan is survey.Based on the descriptive method the aim of this research is to response following questions: Main Question: What are the important financial risk factors and their ranks on Iranian corporations?Sub-questions: 1. What are the financial risk factors on Iranian corporations?2. What is the importance degree of each financial risk factors? 3. What is the rank of each risk factors Rank based on AHP results?
The statistical universe of this research includes financial and production managers as well as selected employees who work for firms operating in stock exchange.They are selected to measure the relative importance of various economic risk factors.The survey was limited to firms, which were active in city of Tehran, Iran.The sample size is calculated as follows, where N is the population size, represents the yes/no categories, 2 /  z is CDF of normal distribution and finally  is the error term.Since we have 96 and N=120, the number of sample size is calculated as n=92.The survey has distributed 120 questionnaires and managed to collect 92 properly filled ones.The questionnaire includes 48 multiple-choice, close-ended questions where 43 questions were associated with subordinate indices and 5 questions were related to main indices.All questions were in Likert scale where 1 demonstrates the least degree of importance and 9 demonstrates the degrees of importance.The participants were asked about some demographic information and their feedback were used to rank various factors.Fig. 1 shows the hierarchy of the proposed study.The risk of profit per share The risk of loaner situation The risk of inability in interest payment The risk of inability in loan payment The risk of investment revenue

Inflation risk
The risk of tax expenses The risk of bad paper debt expenses The risk of benefit /loss before tax discount The risk of disability to perform short-term obligations The risk of disability in short-term financing The risk of difference in order receiving The risk of specified rules The risk of low demand for goods or services

Consumer price risk
Producers price risk

Gross domestic product risk
Exchange rate risk The proposed study of this paper uses analytical hierarchy process (AHP) to rank different factors (Chang, 1996;Saaty, 2004).First, we describe the statistical community and questions responses and then we rank risk priorities based on AHP method.Fig. 2 demonstrates the summary of our statistics on people, who participated in our survey,

Fig. 2. Personal characteristics of the participants
After reviewing global literature and extracting economic risk indices in big corporations, a questionnaire was distributed among experts for making a comment and final selection, which includes the most important economic risk indices.The statistical community was divided based on their responsibilities on different groups.Fig. 3 and Fig. 4 demonstrate the summary of participants' gender and educational backgrounds.

Level of education
Field of education

Fig. 3. Personal characteristics of the participants
As we can observe from the figures, the most frequency is related to financial and production personnel.In our survey, 95 percent of participants were male 5 percent of them were female.In addition, most people had at least five years of job experiences and maintained a good university background.In The risk factors were evaluated based on expert interviewing.Each factor was evaluated with a question that responded with 1-9 as factor important or effect.Table 1 demonstrates the summary of some basic statistics associated with 48 questions of the survey.

Table 1
The summary of some basic statistics As we can observe from the results of Table 1, most items maintain a mean of well above 5.Table 2 shows the propriety of five main risk factors.As we can observe from the results of Table 2, financing risk maintains the highest priority followed by credit risk, liquidity risk, inflation risk and exchange risk.Table 3 shows details of our investigation on ranking risks associated with financing expenses.As we can observe from the results of Table 3, risk of profit per share is number one priority followed by the risk of divisional profit per share, the risk of recessionary or boom and the risk of increasing partial pay profit rate.Credit risk is another component and Table 4 demonstrates the summary of our ranking.

Table 4
The summary of credit risk Priority Description of risk factor 0.325 The risk of inability in loan payment 0.154 The risk of inability in interest payment 0.494 The risk of loan situation Based on the results of Table 4, the risk of loan is number one priority followed by the risk of inability of loan payment and interest payment.The next risk factor is associated with liquidity risk and Table 5 shows details of our ranking using AHP method.The results of Table 6 specify that producers price risk is the most important factor followed by consumer price risk, gross domestic product and producers price risk.Finally, exchange rate risk is the last component survey and Table 7 shows details of our survey.In terms of different factors influencing exchange risk, export related issues are considered as the most important factors.In addition, factors associated with employment, and agency's capability in production is other important factor.

Conclusion
In this paper, we have presented an empirical investigation to rank various risk factors including financing risk, credit risk, liquidity risk, inflation risk and exchange risk using AHP method.The results have indicated that financing risk maintains the highest priority followed by credit risk, liquidity risk, inflation risk and exchange risk.In terms of different risks associated with financing risk, risk of profit per share has been the number one priority followed by the risk of divisional profit per share, the risk of recessionary or boom and the risk of increasing partial pay profit rate.In terms of credit risk, the risk of loan has been number one priority followed by the risk of inability of loan payment and interest payment.Liquidity risk is another risk factor where demand has been the most important factor followed by rules and regulations and inflation risk.In terms of inflation, producers price risk has been the most important factor followed by consumer price risk, gross domestic product and producers price risk.Finally, in terms of different factors influencing exchange risk, export related issues are considered as the most important factors.

Table 2
The summary of priority of the main five risk factors

Table 3
The summary of risk associated with financing expenses

Table 5
The summary of liquidity riskAccording to the results of Table5, demand is the most important factor followed by rules and regulations and inflation risk.Inflation is another risk component with four sub-component, which are summarized in Table6as follows,

Table 6
The summary of risk factors associated with inflation

Table 7
The summary of risk factors associated with exchange rate