Predicting financial distress using corporate efficiency and corporate governance measures

Credit models are essential to control credit risk and accurately predicting bankruptcy and financial distress is even more necessary after the recent global financial crisis. Although accounting and financial information have been the main variables in corporate credit models for decades, academics continue searching for new attributes to model the probability of default. This thesis investigates the use of corporate efficiency and corporate governance measures in standard statistical credit models using cross-sectional and hazard models. Relative efficiency as calculated by Data Envelopment Analysis (DEA) can be used in prediction but most previous literature that has used such variables has failed to follow the assumptions of Variable Returns to Scale and sample homogeneity and hence the efficiency may not be correctly measured. This research has built industry specific models to successfully incorporate DEA efficiency scores for different industries and it is the first to decompose overall Technical Efficiency into Pure Technical Efficiency and Scale Efficiency in the context of modelling financial distress. It has been found that efficiency measures can improve the predictive accuracy and Scale Efficiency is a more important measure of efficiency than others. Furthermore, as no literature has attempted a panel analysis of DEA scores to predict distress, this research has extended the cross sectional analysis to a survival analysis by using Malmquist DEA and discrete hazard models. Results show that dynamic efficiency scores calculated with reference to the global efficiency frontier have the best discriminant power to classify distressed and non-distressed companies. Four groups of corporate governance measures, board composition, ownership structure, management compensation and director and manager characteristics, are incorporated in the hazard models to predict financial distress. It has been found that state control, institutional ownership, salaries to independent directors, the Chair’s age, the CEO’s education, the work location of independent directors and the concurrent position of the CEO have significant associations with the risk of financial distress. The best predictive accuracy is made from the model of governance measures, financial ratios and macroeconomic variables. Policy implications are advised to the regulatory commission

Proposing a Sampling Method to Build Effective Bankruptcy Prediction Models for North American Companies

Bankruptcy prediction is a widely researched topic. However, few studies focus on dealing with the imbalance problem. This paper proposes a new technique that applies a bagging undersampling procedure to balance the data and compares it to random undersampling and five oversampling techniques. The performance of the algorithm is evaluated by a random forest’s balanced accuracy, sensitivity, and specificity. The results show that models trained after applying the oversampling techniques are prone to overfitting, and the model trained after applying the proposed method had the highest balanced accuracy without overfitting

Determinants of financial distress among manufacturing companies in Malaysia

This study is conducted to evaluate the relationship between liquidity (WCTA, CACL), leverage (TDTA, CLNW), profitability (EBTA, ROE, ROA), BTMV, sales growth, and cash flow (CFFTL, CFITL, CFOTL) and the corporate financial distress among listed manufacturing firms in Malaysia. This study uses a sample from 2001 to 2014. Logistic regression is used to evaluate the relationship between the variables in three models. In model 1, the result shows that the WCTA, TDTA, EBTA, ROA, BTMV, and CFOTL have significant relationship with corporate financial distress. In model 2 when only cash flows variables are included, the results show that CFITL and CFOTL are negatively significant with financial distressed. In model 3 when all variables are included in the analysis, the results remain similar as in model 1. In model 4 when the stepwise logit regression is used, the results similar as in model

Voluntary disclosure of intellectual capital in Chinese (mainland) companies

This research examines the extent, quality, and determinants of intellectual capital (IC) disclosure in Chinese companies in order to obtain a comprehensive understanding with regard to the current status of IC disclosure in China, and further to provide some recommendations for IC reporting guidelines. A mixed methods approach, combining both qualitative and quantitative elements, was used. Specifically, the research evolved in three stages. Firstly, an IC disclosure index was developed as an instrument for content analysis through a questionnaire survey and consultation with a panel of twenty Chinese IC experts. Secondly, two years annual reports of 100 top A-share Chinese firms were coded for data collection using a coding framework developed from the disclosure index. The collected data were then quantified and analyzed so as to determine the extent and quality of IC disclosure by Chinese firms. Finally, a series of hypothesis regarding the correlations between IC disclosure practices of Chinese firms and nine impact factors (or determinants) were deduced on the basis of prior literature and some relevant theories. Then the hypotheses were tested employing the empirical evidence obtained from the second stage through some statistical techniques, such as univariate analysis and multiple regression analysis. Inconsistent with prior research, the results in this study indicate that the current level of IC disclosure in China was quite high in both extent and quality, and there was no significant information gap between the expectation of Chinese stakeholders and the actual practices of Chinese firms. It is contended that there are three factors motivating Chinese firms to report their IC actively: to reduce information asymmetry between the management of a company and various stakeholder groups; to discharge accountability to various stakeholders; and to signal organizational legitimacy and excellence to the market. It was also found that all the impact factors other than ownership structure had a significant effect on the level of IC disclosure of Chinese firms in univariate analysis, while four out of nine factors comprising firm size, ownership concentration, board independence and stand-alone sustainability report had a significant impact on the level of IC disclosure in multiple regression analysis. It is believed that the findings in this research could have a number of implications for academics, investors, managers, regulators and policy makers

The IPO underpricing in the chinese STAR market: an examination of the effects of the new market-oriented regulations

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Disclosure and Compliance Practices and Associated Corporate Characteristics - A Study of Listed Companies in India

The present study empirically investigates the level of compliance by listed Indian firms with disclosure requirements of Indian Accounting Standards. India’s Accounting Standards have been gradually converging with the International Financial Reporting Standards (IFRS) since 2001. India currently stands on the verge of adopting the International standards. Indian companies are working fervently towards adopting IFRS. This provides an extraordinary research environment to assess the level of compliance during this transitional time as well as lending an opportunity for a post adoption study. This study addresses two research questions developed to review annual reports of 156 listed Indian firms to determine (1) their current level of compliance with selected disclosure requirements of Indian Accounting Standards, and (2) key corporate characteristics that affect their level of compliance. The data used for the study pertains to the financial year 2009-2010 and utilizes disclosure and compliance index methodology to calculate the level of disclosure. Overall, the findings of this study indicate none of the companies in the sample was fully compliant with the mandatory requirements of the Indian Accounting Standards. On average, level of disclosure made by Indian companies based on selected mandatory disclosures is 70.91%. Nevertheless, the disclosure levels were on an average comparable to results from similar studies conducted in other developing countries. Moreover, results indicated a strong and positive association between level of disclosure and the size, profitability and timeliness of reporting of the sample companies

KARAKTERISTIK PERUSAHAAN, GEJOLAK EKONOMI DAN CORPORATE DISTRESS PADA PERUSAHAAN JASA NON KEUANGAN DI INDONESIA (1998 - 2019

Penelitian ini bertujuan untuk menganalisis dan mengetahui karakteristik perusahaan yang dapat mempengaruhi prediksi corporate distress dan juga mengethaui dampak gejolak ekonomi terhadap prediksi corporate distress pada perusahaan jasa non keuangan di Indonesia dari tahun 1998 – 2019. Jenis penelitian yang dilakukan adalah penelitian kuantitatif dimana objek penelitian adalah perusahaan jasa non keuangan di Indonesia dengan jumlah populasi sebanyak 326 perusahaan yang terdaftar per Februari 2020. Tekhnik pengambilan sampel dengan purposive sampling yang memiliki kriteria (1) Perusahaan terdaftar di Bursa Efek Indonesian dari tahun 1998 – 2019, (2) Memiliki laporan keuangan dan tahunan yang lengkap dari tahun 1998 -2019 dan (3) Perusahaan aktif memperdagangkan sahamnya selama periode 1998-2019,perusahaan tidak pernah delisting dari bursa dalam peride 1998-2019. dari kriteria tersebut didapatkan sampel sebanyak 66 perusahaan. penelitian menggunakan data panel dengan analisis regresi data panel dan analisis komperatif non parametrik. Temuan penelitian ini mengungkapkan bahwa dalam memprediksi corporate distress dengan model Zmijewsky di dapat selama tahun 1998 sampai tahun 2019 terjadi fluktuasi perusahaan yang mengalami corporate distress dan dengan estimasi data panel didapat variabel Pengalaman perusahaan yang di proksi dengan umur berpengaruh secara signifikan terhadap corporate distress, serta gejolak ekonomi yang di proksi dengan pertumbuhan ekonomi dalam penelitian ini juga berpengaruh secara signifikan terhadap prediksi corporae distress. Terdapat perbedaan karakteristik pada setiap masa gejolak ekonomi dari hasil yang didapat bahwa pada masa-masa ekonomi mengalami penurunan karaktersistik yang berpengaruh adalah jumlah tenaga kerja, sedangkan pada saat ekonomi bertumbuh atau recovery karakteristik perusahan yang berpengaruh Pengalaman perusahaan dan ukuran perusahaan Kata Kunci : Karakteristik Perusahaan, Model X-Score, Corporate distress, gejolak ekonomi

Predicting Forced Financial Restatement: Evidence from the Malaysian Capital Market

Historical precedent shows that forced financial restatements can have serious implications for the firm affected, investor confidence in financial markets and a country’s economic development more generally. The purpose of this study is to explore factors which affect the likelihood of forced financial restatements. This issue is particularly pertinent in the Malaysian context, as, despite repeated efforts by the government to improve the corporate governance of listed companies, weak regulatory enforcement and the influence of family groups and politicians give rise to continued concerns about financial reporting quality. This study uses the multivariate logit model to analyse firm characteristics which relate to forced financial restatement. The analysis was performed on the Malaysian listed companies from 2002 to 2012. Findings indicate that the likelihood of forced restatements was related to aggressive accounting practices. In addition, the presence of politically-connected shareholders or top executives, the proportion of independent directors on the board, firms’ decreasing level of internal fund and share price volatility were also related to an increased likelihood of forced restatement. More detail tests on the attributes of the different types of restatement show that the likelihood of income-increasing and zero-effect forced restatement event were affected by opportunistic earnings management practices. This contradicts with the results shown for forced income decreasing restatement as they do not imply aggressive accounting, but are more likely to result from mistakes or technical accounting matters, such as change in accounting policy. This study contributes to our understanding by examining a much wider range of financial and non-financial factors as possible determinants of forced restatements. Moreover, compared to prior research, this study explores forced income-decreasing, income-increasing, as well as zero-effect restatements to distinguish between earnings restatements that arise from related to opportunistic behaviour and those linked to accounting errors. Methodologically, this study further contributes by applying the penalised likelihood logit and structural equation modelling approach which are scarcely examined in accounting research, to determine factors affecting the likelihood of forced restatements. It was not possible to develop a valid predictive model for forced financial restatements which is recognised as a limitation to the study. However, the findings in this study do provide some insights into factors which relate to the likelihood of forced restatements, which should be useful for investors, analysts, auditors, and regulators

An empirical study on credit evaluation of SMEs based on detailed loan data

Small and micro-sized Enterprises (SMEs) are an important part of Chinese economic system.The establishment of credit evaluating model of SMEs can effectively help financial intermediaries to reveal credit risk of enterprises and reduce the cost of enterprises information acquisition. Besides it can also serve as a guide to investors which also helps companies with good credit. This thesis conducts an empirical study based on loan data from a Chinese bank of loans granted to SMEs. The study aims to develop a data-driven model that can accurately predict if a given loan has an acceptable risk from the bank’s perspective, or not. Furthermore, we test different methods to deal with the problem of unbalanced class and uncredible sample. Lastly, the importance of variables is analyzed. Remaining Unpaid Principal, Floating Interest Rate, Time Until Maturity Date, Real Interest Rate, Amount of Loan all have significant effects on the final result of the prediction.The main contribution of this study is to build a credit evaluation model of small and micro enterprises, which not only helps commercial banks accurately identify the credit risk of small and micro enterprises, but also helps to overcome creditdifficulties of small and micro enterprises.As pequenas e microempresas constituem uma parte importante do sistema económico chinês. A definição de um modelo de avaliação de crédito para estas empresas pode ajudar os intermediários financeiros a revelarem o risco de crédito das empresas e a reduzirem o custo de aquisição de informação das empresas. Além disso, pode igualmente servir como guia para os investidores, auxiliando também empresas com bom crédito. Na presente tese apresenta-se um estudo empírico baseado em dados de um banco chinês relativos a empréstimos concedidos a pequenas e microempresas. O estudo visa desenvolver um modelo empírico que possa prever com precisão se um determinado empréstimo tem um risco aceitável do ponto de vista do banco, ou não. Além disso, são efetuados testes com diferentes métodos que permitem lidar com os problemas de classes de dados não balanceadas e de amostras que não refletem o problema real a modelar. Finalmente, é analisada a importância relativa das variáveis. O montante da dívida por pagar, a taxa de juro variável, o prazo até a data de vencimento, a taxa de juro real, o montante do empréstimo, todas têm efeitos significativos no resultado final da previsão. O principal contributo deste estudo é, assim, a construção de um modelo de avaliação de crédito que permite apoiar os bancos comerciais a identificarem com precisão o risco de crédito das pequenas e micro empresas e ajudar também estas empresas a superarem as suas dificuldades de crédito