The Value Relevance of Financial Distress Risk in the Case of RASDAQ Companies

Robu, Ioan-Bogdan; Robu, Mihaela-Alina; Mironiuc, Marilena; Balu, Florentina Olivia Article The Value Relevance of Financial Distress Risk in the Case of RASDAQ Companies Journal of Accounting and Management Information Systems (JAMIS) Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Robu, Ioan-Bogdan; Robu, Mihaela-Alina; Mironiuc, Marilena; Balu, Florentina Olivia (2014) : The Value Relevance of Financial Distress Risk in the Case of RASDAQ Companies, Journal of Accounting and Management Information Systems (JAMIS), ISSN 2559-6004, Bucharest University of Economic Studies, Bucharest, Vol. 13, Iss. 4, pp. 623-642 This Version is available at: https://hdl.handle.net/10419/310570 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Accounting and Management Information Systems Vol. 13, No. 4, pp. 623–642, 2014 The value relevance of financial distress risk in the case of RASDAQ companies Ioan-Bogdan Robua, Mihaela-Alina Robua, Marilena Mironiuc a and Florentina Olivia Bălub,1 a Alexandru Ioan Cuza University of Iasi, Romania, b University of Geneva, Switzerland Abstract: The financial distress risk concept has been referred as follow: negative net assets, insolvency, bond default, overdraft, unpaid dividends for the preferred stocks, bankruptcy etc. From all the stakeholders, investors are interested in the financial position and performance of a company and its ability to continue as a going concern, without knowing the appearance of financial distress status. The purpose of this study aims to test the value relevance of the appearance of distress risk on investors’ decisions on the purchase or sale of stock, with impact on stock return, for the Romanian listed companies in RASDAQ section. In order to reach the objective, the study was carried on upon a sample of 70 Bucharest Stock Exchange (BSE) listed companies, between 2008 and 2014, using statistical methods like analysis of variance (ANOVA), simple linear regression and ANCOVA models. Through the obtained results, it was demonstrated the difference between financial distressed companies and performant companies and the influence of belonging to a company in the high risk category on the stock return. Keywords: value relevance, distress risk, financial ratios, ANOVA, ANCOVA, RASDAQ JEL codes: B23, C58, G14, G33, M41 1 Corresponding authors: Ioan-Bogdan Robu, Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, Romania, email addresses: bogdan.r[email protected].ro, [email protected]o, marile[email protected]o; Faculty of Economics and Social Sciences, University of Geneva, Switzerland, email address: [email protected]. Accounting and Management Information Systems Vol. 13, No. 4 624 1. Introduction Starting with 2007, alongside with the show up of the global financial crisis, the number of companies, both listed and unlisted, with financial difficulties or even bankrupt has grown significantly. This situation has generated shifting the focus of financial statement users to the companies’ ability to continue as a going concern in a predictable future. On a capital market, a category of users that are interested in the development of distress risk is represented by investors. Investors want to know information regarding the companies’ financial position and performance based on the financial statements, in order to make the most adequate investment decisions. Information provided by the investors through the stock price regarding the anticipation of future cash flows can be used in order to determine how early the market players recognize the appearance of distress risk of the company and its financial defacement (Aharony et al., 1980). Within the decision making process, investors must take into account the macroeconomic information such as the general economic situation, the monetary policy, the price levels and international activity (Tangjitprom, 2012), and especially the factors that are specific for each country, mainly reflected by the financial statements. These represent the main communication way between companies and actual or potential investors (Vijitha & Nimalathasan, 2014). The financial information gathered from the financial statements issued according to the rules in force can be considered a credible information source on which investors can trust in the decision making process (Ragab & Omran, 2006). The main objective of the financial reporting is providing useful information to the financial statements users regarding the financial position and performance of a company (IASB, 2013). The purpose of this study aims to test the value relevance of the appearance of distress risk on investors’ decisions, with impact on stock return, for the Romanian listed companies in RASDAQ section. Stock return is quantified by the relative variation of stock prices from one period to another. In order to reach the objective, the study was carried on upon a sample of 70 Bucharest Stock Exchange (BSE) listed companies, between 2008 and 2014, using statistical methods like analysis of variance (ANOVA), simple linear regression and ANCOVA. Through the obtained results, it was demonstrated the difference between financial distressed companies and performant companies and the influence a company belonging to a high risk category on the stock return. The value relevance of financial distress risk in the case of RASDAQ companies Vol. 13, No. 4 625 2. Literature review and hypothesis development Alongside with Ball’s and Brown’s (1968), respectively Beaver’s (1968) studies, the concept of value relevance of the financial statements has been developed, though it barely appeared in 1993 (Barth et al., 2001). According to Beisland (2009) and El-Sayed Ebaid (2012), by analyzing the relevance of financial information, it is studied the relation between the information and the market, representing the ability of the financial information to influence the stock price or stock return, as a result, the decision making process. Although the value relevance concept focuses on the information provided by financial reporting, the development of the concept implies alongside with the analysis of the information, the analysis of the influence of other non-financial factors that regard the financial statement or not, such as: the affiliation to a certain activity field (Lin & Jin, 2006; Chou et al., 2012), the application of certain accounting standards (Dumontier & Raffournier, 2002; Barth et al., 2008; Barth et al., 2012), the existence of corporate governance (Lacker et al., 2011), the report issuance and the audit opinion issuance (Gómez-Guillmón, 2008; Lee & Lee, 2013), the existence of risk and especially of the financial distress risk and bankruptcy (Katz et al., 1985; Griffin & Lemmon, 2002). Regarding the Romanian stock market, as an emerging one that offers higher growth rates and profitability (Albu & Albu, 2012), the literature is based on identifying the relevant financial information for investors in terms of earnings (Filip & Raffournier, 2010), the impact of applying IFRS on the value relevance of earnings (Filip, 2010). These studies are considered, according with Holthausen and Watts (2001), relative association studies and incremental association studies, identifying, on one side, the explanatory power of the financial information through the R2 coefficient and, on the other side the most relevant information through regression coefficients. Studying the same problem of the influence of the financial information on stock market, Turdor (2012) and Jaba et al. (2013) applied event study through panel analysis, identifying a strong link between earnings and stock market. All these studies focus on the financial information, not taking into consideration other factors which can influence the decisions of investors. 2.1 The concept of financial distress risk and how it is measured The financial distress risk concept has been referred to as various concepts. Karels and Prakas (1987) make a synthesis of several definitions of this concept according to different empirical studies from Beaver (1966) and Altman (1968) to Taffler and Tisshaw (1982): negative net assets, insolvency, bond default, overdraft, unpaid dividends for the preferred stocks, bankruptcy etc. Turetsky and McEwen (2001) also start from a series of previous studies, focusing on the meaning of economic concept characterized by various continuous inauspicious financial statuses, Accounting and Management Information Systems Vol. 13, No. 4 626 respectively on the moment when the assets of a company are not sufficient in order to cover its debts. Moreover, they consider that a decreasing of the cash flow corresponding to operational activities represents a signal from the beginning of the financial distress risk, subsequently characterized by dividends payment decrease, loan non-payment or debts reorganization (Turetsky & McEwen, 2001). The specialized literature has most frequently stopped, in the analysis of the financial/business failure on the insolvency or bankruptcy meaning (Beaver, 1966; Altman, 1968; Deakin, 1972; Ohlson, 1980). In the past, statistical methods have been mainly used by deciders in order to evaluate the insolvency and bankruptcy risk, such as: discriminant analysis (Altman, 1968; Deakin, 1972), the logistic regression analysis (Ohlson, 1980; Zavgren, 1985), the probabilistic regression analysis (Zmijewski, 1984; Theodossiou, 1991) and the surviving analysis (Lane et al., 1986; Luoma & Laitinen, 1991). From the econometric approach, Aziz and Dar (2006) consider that the specialized literature is dominated by the discriminant analysis and the logistical regression analysis. Alongside these methods, other methods based on artificially intelligence have been recently added: artificial neural networks, decision trees and genetic algorithms (Olson et al., 2012). These methods can be used by all financial statements users, inclusively by auditors, in order to test the going concern (Robu et al., 2012). As for Romania, the main models which have been elaborated are C. Mânecuţă and M. Nicolae model in 1996, Băileşteanu in 1998 and Ivonciu in 1998, or Anghel model in 2002 (Mironiuc, 2006) and Robu-Mironiuc model (ZRM) in 20012 using multiple discriminant analysis (Robu et al., 2012). 2.2 Market Reactions to financial distress risk Most times, the financial distress risk was seen through the insolvency and the bankruptcy state. Companies that reach the insolvency or bankruptcy state are characterized by decreasing total assets, revenues and net accounting shares value and growing debts and financial expenditures (Barniv et al., 2002; Mironiuc, 2006). Regarding the influence of bankruptcy appearance probability on the market, Aharony et al. (1980) have emphasized a clear phenomenon, the fact that stock price significantly decreases around the moment of the announcement of the bankruptcy status. Zavgren et al. (1988) see bankruptcy as “bad news”, and, as a result, the decrease of the stock prices is to be expected. Though, capital market actors have useful means to anticipate bankruptcy by evaluating the information corresponding to the previous period to its emergence. Chen and Church (1996) assume that the market reacts less to the announcements regarding bankruptcy The value relevance of financial distress risk in the case of RASDAQ companies Vol. 13, No. 4 627 emergence when the auditor has previously issued an opinion regarding the company’s activity continuity. Barniv et al. (2002) suggests that investors of the companies that are heading for financial business failure loose significant values on the market sixty days before the emergence of the phenomenon. This situation is caused by the previous evaluation of the market regarding the probability of each company to become bankrupt (Green & Dawkins, 2000). Altman (1971) has, in turn, proved the emergence of an investor afferent loss of approximately 26% in a month before and after the occurrence of bankruptcy. From the reorganization process perspective, the investors of the purchased companies or of the ones that have merged have reported significant positive yields from the emergence to the ending of the phenomenon, while investors of the liquidated companies have had significant negative yields (Green & Dawkins, 2000; Barniv et al.,2002). Opinions regarding the existing relation between the probability of financial distress emergence and the capital market do not just hint at the opposite relation between them. For example, Vassalou and Xing (2004) consider that companies with a high risk of financial failure determine growing profitableness just in the case of small enterprises characterized by growing book-to-market ratio. This situation is explained by the shareholders’ negotiating power (Apergis et al., 2011). 2.3 Research hypotheses Starting from the specialized literature regarding the influence of the financial distress risk emergence on the capital market investors’ reaction, reflected through stock return, the present study aims at testing the following work hypotheses: H1: For the Romanian listed companies in RASDAQ, there are significant differences between the mean values of the financial ratios afferent to the performant and the financial distress companies. H2: For the Romanian listed companies in RASDAQ, there are significant differences between the mean values of stock return depending on the influence of the distress risk, estimated based on the financial data. H3: For the Romanian listed companies in RASDAQ, the financial distress risk, estimated based on financial data, has a significant influence on the investors’ reaction (calculated based on the stock return), classified in performance and company’s risk group affiliation categories. 3. Research methodology The study aims at analysing the influence of the financial distress risk on the investors’ decision, expressed by the stock return, quantified through the relative variation of stock price from a reporting period to another. In order to reach this objective, a positivist logical research approach is proposed, by using a deductive- Accounting and Management Information Systems Vol. 13, No. 4 628 inductive intercession in formulating, testing and validating the work hypotheses (Smith, 2003). 3.1 Target population and analysed sample The target population is represented by the BSE listed companies between 2008 and 2014. A sample of RASDAQ listed companies is extracted from this population in order to be analysed, according to the principle of rational chose (Jaba, 2002). The main activity field of these companies is the industrial one. The sample is divided in two different sub samples. The first sample includes those companies that have been initiated in the insolvency procedure (preliminary stage of bankruptcy). Out of the 123 identified companies for which the insolvency procedure has begun since 2008, 24 companies were eliminated, companies for which information provided by the financial statements have not been identified and 53 companies for which there is no information regarding the stock price in the analysed period. The number of the implied insolvent companies for the analysis is 46. The second sub sample includes performant companies. These companies were selected from the list of the Major Companies in Romania study, 2013 edition, Top 300 most important companies, study that has been carried out by using an Ernst & Young developed methodology, that also takes into account the companies’ performances. Out of the 33 performant RASDAQ listed companies from the field of industry, 9 companies were excluded final number of performant companies remaining at 24. The final sample is made of 46 insolvent companies and 24 performant companies. 3.2 Analysed variables and data source The variables chosen in order to assess the objective of the research are the financial ratios that were used in the Robu-Mironiuc model (Robu et al., 2012). Financial ratios can be used in order to draw conclusions on the current status of the companies (Istrate, 2007), and those that were included in Robu-Mironiuc model model are specific to the analysis of bankruptcy risk for the Romanian quoted companies and has the following form: ZRM = 0.333 -0.012FL +0.525RAF +0.027ROE -0.425DR -0.126NM +3.573ROA -0.663ITR +0.022 CFR (1) For this model, the ranges for the bankruptcy risk categories are: high bankruptcy risk 0) 5;(∈ZRM , moderate bankruptcy risk 0.6) ;0[∈ZRM and low bankruptcy risk 2.5] [0.6;∈ZRM . Variables in this model are presented in table 1 together with the formula for each variable. The value relevance of financial distress risk in the case of RASDAQ companies Vol. 13, No. 4 629 Table 1. Numerical variables implicated in the analysis, taken from the ZRM model Numerical Variables Formula X1=Financial Leverage Ratio (FL) Total Debt / Shareholders Equity X2=The Financial Autonomy Ratio (FAR) Shareholders Equity / Total Assets X3=Return on Equity (ROE) Net Income /Shareholders Equity X 4 =Debt Ratio (DR) Total Debt / Total Assets X 5 =Net Margin (NM) Net Income / Turnover X6=Return on Assets (ROA) Operating Income / Total Assets X7=Interest to Turnover Ratio (ITR) Total interest / Turnover X 8 =Cash Ratio (CFR) Cash / Current debts A model of bankruptcy risk prediction was chosen on the grounds that, bankruptcy is a situation of financial distress and follow the insolvency of a company. Robu- Mironiuc model selection is primarily determined by the timeliness of this model and the specific companies that were the basis for obtaining it, to the detriment of C. Mânecuţă and M. Nicolae, Băileşteanu, Ivonciu or Altman. The information from the financial statements of these companies is for the period of crisis, period selected for study. Whatever the time when models were obtained for predicting the state of financial distress, it is necessary to review and improve them to be permanently viable. Secondly, Robu-Mironiuc model was chosen mainly due to the homogeneity of the sample (companies in the industry). Regarding Anghel model, this is characterized by diversity of activity fields of the companies analysed. Smith and Liou (2007) points out, activity fields can have sub-domains in their structure, activities of national economy characterized by differences in legislation, operating system and product life cycles with significant influence on financial conditions. In order to test the relevance of the information regarding the distress risk, gathered based on the Robu-Mironiuc model, table 2 presents the numerical variables that were included in the analysis. Table 2. Numerical variables implicated in the analysis, taken from The Robu-Mironiuc model Numerical Variables Formula ZRM Calculated with formula (1) CGY= Capital Gains Yield (Price 1 - Price 0 )/Price 0 * *where P0 = represents the stock price, after five month from the moment of the financial statements issuance previous the year the companies were initiate in insolvency; Accounting and Management Information Systems Vol. 13, No. 4 630 P1 = represents the stock price at the time of opening insolvency proceedings for companies in financial distress, after one year of registration P0, for companies considered performant. In order to evaluate the bankruptcy risk influence, on different risk categories calculated based on the Robu-Mironiuc model, as well as the influence of the company status on the investors’ reaction, table 3 displays the main variables that have been used in the relevance analysis model. Table 3. Categorical variables included in the relevance analysis of Robu-Mironiuc model on investors Categorical Variables Categories Status 1: Distress; 2: Performante Interval_ZRM 1: high distress risk 0) 5;(∈ZRM : HDR 2: moderate distress risk 0.6) ;0[∈ZRM : MDR 3: low distress risk 2.5] [0.6;∈ZRM : LDR The data needed to calculate the financial ratios for each company were obtained from the annual financial statements presented on the BSE website - www.bvb.ro. The data necessary to compute the CGY were selected from the website – www.kmarket.ro. 3.3 Methods for data analysis and proposed models In order to obtain the research results, the study proposes the use of Analysis of variance (ANOVA), as well as the use of simple linear regression models or ANCOVA. ANOVA is a statistical analysis procedure of a quantitative variable variation, result type, in comparison to one or more explanatory categorical variable (Jaba, 2002). In order to verify if one factor type variable (X), taken into consideration in the study, has a significant influence on the variable variation (Y), a test is carried out to see if there are significant differences between the estimated Y means for each group (category) defined based on the X factor (Jaba et al., 2012). Testing the existence of significant differences between the estimated means within each group can be carried out by using multiple post hoc comparisons, based on Bonferroni, Tukeytests and LSD tests (Jaba et al., 2012). Use of LSD test is proposed in this study. The value relevance of financial distress risk in the case of RASDAQ companies Vol. 13, No. 4 637 Table 11. Estimations of the regression parameters for model 3 Model 3 * β t test Sig. Intercept - 13.959 -0.887 0.378 ZRM 19.928 2.891 0.005 Dummy HDR 13.986 0.664 0.509 Dummy MDR 20.981 0.741 0.461 DummyHDR·ZRM - 19.865 -2.702 0.009 DummyMDR·ZRM - 25.375 -0.443 0.659 *CGY = dependent variable In this case, for the companies that present no financial distress risk (affiliated to the LDR category), one may notice that the information provided to the investors based on the ZRM score calculation are relevant and lead to a growth the profitableness of RASDAQ listed shares (evaluated by using CGY). In the case of companies that show a medium distress risk emergence, information that is provided to the investors that were calculated based on the ZRM do not indicate any relevance within RASDAQ. But, for the companies with a high degree reaching the failure status, one can appreciate that the calculated ZRM score determines a significant decrease in the share profitableness of the RASDAQ listed companies. Thus, we can appreciate that the calculated values of the ZRM model are relevant for the investors only in the case of companies that present a high or very low probability to reach the failure status. 5. Conclusions After processing the data using analysis of variance (ANOVA), simple linear regression and ANCOVA, the results led to the validation of the proposed working hypothesis regarding the existence of significant differences between the mean values of financial ratios of the performant companies and insolvent, and according to the influence of the distress risk estimated based on financial data (computed on the stock return basis). Validation of these assumptions determine to achieve the goal proposed of testing the relevance of information on the distress risk on the investors decisions, regarding the purchase or sale of shares, with impact on stock return, for Romanian listed companies on RASDAQ. The results are consistent with the views expressed by Aharony et al. (1980) and Zavgren et al. (1988) that considers the phenomenon of financial distress as a “bad sign”, which act in reverse. Although adverse event is the occurrence of insolvency, which can be completed either by reorganizing companies, either through bankruptcy and liquidation, investors who act on the Romanian capital Accounting and Management Information Systems Vol. 13, No. 4 638 market, notes rather the unfavourable state of insolvency often followed by bankruptcy. From the variables presented in Robu-Mironiuc model, the variables analysed differ from the point of view of performant companies and financial distress companies, as well as from the point of view of the three risk categories. These results again validate the model Robu-Mironiuc. Regarding the econometric models obtained, ZRM score and membership of a company in the high risk category influence CGY and therefore investors' decisions CGY, result considered to be somewhat expected. No investor, no matter how rational is, will accept the possibility of disappearance of the company. The necessity of such a study is determined by the existence in the Romanian literature, especially statistical models that can be applied to determine the state of difficulty, without taking into account their impact on stock return. For a potential investor, knowing the probability distress risk, characterized by insolvency, bankruptcy or significant losses is important, always reflecting their decisions. The limits of this study relate mainly to the size and nature of the sample which contains 46 companies with financial difficulties, from industry, in the period 2008-2014. At the same time, the study was focused only on the analysis of the influence of financial factors on investors’ decisions without taking into question a number of non-financial factors as control variables. However, future research directions aimed precisely at reducing or eliminating these limitations, focusing on the influence of audit opinion on going concern. Acknowledgements This work was co-financed from the European Social Fund through Sectoral Operational Programme Human Resources Development 2007-2013, project number POSDRU/159/1.5/S/142115 „Performance and excellence in doctoral and postdoctoral research in Romanian economics science domain” and through the grant POSDRU/159/1.5/S/133652, and it was presented on the 9th edition of the International Conference on Accounting and Management Information Systems which was held at the Bucharest University of Economic Studies, on June 11-12, 2014. The authors would like to thank to the Editor Nadia Albu for their comments on the paper, to Robert Faff and Allan Hodgson for their precious recommendations and to the anonymous reviewers. References Aharony, J., Jones, C. 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