Financial distress and bankruptcy prediction an appropriate models for listed firms in vietnam

UNIVERSITY OF ECONOMICS ERASMUS UNIVERSITY ROTTERDAM HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS FINANCIAL DISTRE

UNIVERSITY OF ECONOMICS ERASMUS UNIVERSITY ROTTERDAM

HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES

VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

FINANCIAL DISTRESS AND BANKRUPTCY PREDICTION:

AN APPROPRIATE MODEL FOR LISTED FIRMS IN

VIETNAM

BY

PHAM VO NINH BINH

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, DECEMBER 2017

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

FINANCIAL DISTRESS AND BANKRUPTCY PREDICTION:

AN APPROPRIATE MODEL FOR LISTED FIRMS IN

VIETNAM

A thesis submitted in partial fulfillment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

DECLARATION

I declare that the thesis report entitled, “The financial distress and bankruptcy prediction: An

appropriate model for listed firms in Vietnam” composed and submitted by myself in

fulfillment of the requirements for the degree of Master of Art in Development Economics to the Vietnam – Netherlands Programme This is my basic work and conclusions drawn are based on the material collected by my own

I confirm that this work has not previously been submitted to any other university for the award

of any other degree, diploma or equivalent course

HCMC, December 2017

Phạm Võ Ninh Bình

ACKNOWLEDGEMENTS

First and foremost, I am so appreciative and grateful to all the people who supported in some way

to the work made in this thesis I would like to express the immeasurable appreciation and deepest gratitude to my academic supervisor – Dr Võ Hồng Đức, for his contribution of time, invaluable guidance, encouragement, and enthusiasm It is really my privilege to work with him

Moreover, I wish to acknowledge all of the teachers and staves at Vietnam – The Netherlands Programme for their useful knowledge, advice, and suggestions while I learned at University Special thanks to Prof Nguyễn Trọng Hoài, Dr Phạm Khánh Nam and Dr Trương Đăng Thụy inspiring me to write my thesis as well as their believability play a key role in the success of my study

I would like also to thank my friends at class 22 for their friendship and constant support Finally, I would like to thank my parents and an older sister who is always siding by side me in the difficult and happy time

Phạm Võ Ninh Bình

ABBREVIATIONS

AFC: Asian Financial Crisis

ASEAN: Association of Southeast Asian Nations

AUC: Area under the Receiver Operating Characteristics Curve BSM: Black–Scholes–Merton

CPV: Communist Party of Vietnam

DD: Distance to Default model

EDF: Expected default frequently

EMS: Emerging market score model

GFC: Global financial crisis

HOSE: Ho Chi Minh City Stock Exchange

HNX: Hanoi stock exchange

M&A: Merger and Acquisition

MDA: Multivariate discriminant analysis

ROC: Receiver Operating Characteristics Curve

TPP: Trans-Pacific Partnership

In this fast-changing world, it is likely that potential exposures are present in all economic sectors In the emerging markets such as Vietnam, financial stability is always an important topic

to attract attention from academics, practitioners, and policymakers The Global Financial Crisis

in 2008/2009 was the most recent event in which financial stability of countries has been tested During or even after the crisis, many nations have been still facing macroeconomic problems in relation to unemployment, a reduction of output, firms’ bankruptcy and a sharp increase of firms’ default risk which all lead to a serious instability Although Vietnam is the country with the second highest economic growth rate in Asia and one of a few new emerging markets in the world, the economy has also been suffered to the financial risk

This study is conducted to obtain the following three objectives First, this study is to identify

early warning indicators of corporate financial distress (or the financial risk) using the

accounting-based and market-accounting-based models Second, the study is to build an appropriate bankruptcy prediction model, one of its first kind in Vietnam, using market data for listed firms in Vietnam Third, the

above bankruptcy prediction model is then extended by incorporating macroeconomic factors which are widely considered as key factors affecting the financial distress and bankruptcy of firms,

to be named “a comprehensive model of bankruptcy prediction” for Vietnam

A key objective of this study is to develop a comprehensive model, which is the first of its kind in Vietnam, for the purpose of financial distress and bankruptcy prediction for listed firms Using a sample of more than 800 Vietnamese listed firms on the Vietnam’s stock exchanges in the period from 2003-2016, which is then sub-divided into the pre-global financial crisis (GFC) period (2003-2009) and the post-GFC period (2010-2016) to consider the financial distress likelihood in different scenarios The Emerging Market Score Model (EMS) and the Distance to Default model (DD) are used to identify early the signal of financial distress A new model is then proposed by incorporating various factors including (i) Accounting factors obtained from the EMS model; (ii) Market factors from the DD model; and (iii) Two macroeconomic indicators, the inflation and short-term interest rate which are widely used in the empirical analysis of the topic The Area Under the Receiver Operating Characteristics (ROC) Curve (the AUC) is utilized to compare the usefulness of various default prediction models

Empirical findings from this study present evidence to support the view that factors derived from the accounting variables, market variables, and typical macroeconomic fundamental factors

have all contributed effect to the financial distress of the Vietnamese listed firms for the research period when they are considered in isolation However, when a comprehensive model is

developed, the effect of accounting factors appear to be stronger in comparison with the market

factors Findings from this study also confirm that the model of default prediction including (i)

accounting factors and (ii) macroeconomic indicators appear to be performing much better than the model including market factors and macroeconomic fundamentals In addition, market variables are less likely to affect the financial distress than accounting and macroeconomic factors

in both pre- and post-crisis periods

When the attention is on the sectors of the economy, findings from this study present evidence to support the view that Vietnam’s sectors have faced a high degree of financial risk

Among various industries, the largest exposure belongs to Consumer Staples sector whereas

Health & Education sector is relatively safe in terms of financial risk

Findings from this study shed lights to meaningful policies from the Government in relation

to the financial distress of firms in order to achieve a financial stability for the nation as a whole Listed firms are also advised that their accounting indicators have also provided reliable indicators

to minimize financial distresses and appropriate policies at the firms’ level should be considered

Keywords: Financial Distress, Bankruptcy, Distance to Default, Macroeconomic

Fundamentals, Vietnam

JEL Classification: F62, F65, G01, G31, G33, G34

TABLE OF CONTENTS

DECLARATION i

ACKNOWLEDGEMENTS ii

ABBREVIATIONS iii

ABSTRACT iv

LIST OF TABLES viii

LIST OF FIGURES ix

Chapter 1: INTRODUCTION 1

1.1 Problem statement 1

1.2 Research Objectives 3

1.3 Research questions 3

1.4 Structure of the thesis 4

Chapter 2: BACKGROUND AND LITERATURE REVIEW 5

2.1 Why Vietnam? 5

2.2 Background to the Global Financial Crises 8

2.3 Literature review on credit models 11

2.3.1 Background to corporate financial distress models 11

2.3.2 Comparison of accounting-based and market-based models 18

2.3.3 Studies on financial distress in the context of Asia and Vietnam 20

Chapter 3: RESEARCH METHODOLOGY 23

3.1 Data 23

3.2 Analytical framework 24

3.3 Estimating financial distress 25

3.3.1 Emerging market scoring model (EMS) 25

3.3.2 Distance to default model (DD) 27

3.4 Variable selection 32

3.4.1 Dependent variables 32

3.4.2 Independent variables 32

3.4.3 A Comprehensive model 35

3.5 Logit model 40

3.6 Comparing Emerging market score model (EMS) and Distance to Default (DD) models 42 Chapter 4: EMPIRICAL RESULTS AND ANALYSIS 44

4.1 Data descriptions and Signal of financial distress 44

4.2 Factors affect the financial distress 49

4.3 Financial distress in various scenarios 54

Chapter 5: CONCLUSIONS AND IMPLICATIONS 60

5.1 Conclusions 60

5.2 Policy implications 62

5.2.1 For academics 62

5.2.2 For the Vietnamese Government 63

5.2.3 For practitioners and investors 64

5.3 Limitation and further research 65

REFERENCE 66

APPENDIX 73

LIST OF TABLES

Table 1: EMS score and equivalent rating 27

Table 2: Mapping of S&P rating 31

Table 3: Theoretical prediction of the effect of the accounting, market and macroeconomic variables on the default probability 39

Table 4 : Description statistics of the dependent variable 44

Table 5: Summary of statistics for independent variables 45

Table 6: Correlation matrix and multicollinearity diagnostic statistics 46

Table 7: The relationship between the default probability and EMS, DD 47

Table 8: Credit rating of EMS model 47

Table 9: Credit rating of Z-score model 47

Table 10: Credit rating of Distance to default (DD) model 48

Table 11: Financial distress of Vietnam’s listed firms: various models 50

Table 12: Marginal effect 52

Table 13: A measurement of model performance 53

Table 14: Financial distress of Vietnam’s listed firms: various models in pre-crisis period (2003-2009) 55

Table 15: Model performance measure in the pre-crisis period (2003-2009) 56

Table 16: Financial distress of Vietnam’s listed firms: various models in post-crisis period (2010-2016) 57

Table 17: A measurement of model performance in the post-crisis period (2010-2016) 58

Table 18: Overall Distance to default results for sectors 58

LIST OF FIGURES

Figure 1: Vietnam GDP annual growth rate from 2000 to 2015 9

Figure 2: Vietnam’s Inflation from 2000 to 2015 10

Figure 3: Analytical framework 24

Figure 4: Receiver Operating Characteristics Curve (ROC Curve) 43

In Vietnam, according to the Ministry of Planning and Investment, new business establishment were 68,350 firms whereas a number of firms stopped doing business or went bankrupt were over 7,000 firms In addition, a record of 47,600 firms had faced substantially financial difficulties to warrant for the decision to stop operating temporarily These numbers of firms continued rising considerably in the first six months of 2016 In 2016, 18,916 firms went bankrupt and this figure represents an increase of 4.2 percent compared to the same period of the previous year 2015 Some cases are worth considering in details The IDICO Join-stock company (PXL) incurred losses in three consecutive years and the company was forced to be delisted from the Ho Chi Minh City Stock Exchange (HOSE) in 2016 In the same fate, Vien Dong Medicine Company (DVD) also filed for bankruptcy in the same year In the area of international trade sector, the Phu Phong Joint-stock Company (PPG) had to be dissolved because their products produced from the obsolete technology could not meet the high-quality demand from the European market Moreover, various merger and acquisition (M&A) activities were also taking place with smaller companies being acquired by a much larger corporation operating in the same area of business A notional example can be devoted to the M&A activities where Thanh Cong (TTC) acquired smaller businesses including the Ninh Hoa Sugar (NHS) and Gia Lai Nhiet Dien (SEC) Likewise, a substantial number of foreign firms wanted to expand the market in Vietnam as well by conducting various M&A activities In particular, Masan Group (MSN) was merged by Singha Asia Holding by the end of 2015 The Big C Retail System and the Central Group Thailand came into the same branch

in April 2016 or the TCC Holding Corporation used 711 million dollars to take over the Metro group in January 2016

The synergies of these M&A activities are well beyond the scope of this study However, being taken over by larger corporations in the market is something senior management would like

to avoid In addition, from the macro economy-wide view, too many M&A activities may lead to

a concentration of the market power into a few large players who in turn control the market at the expense of consumers Together with the observed phenomenon that many firms had filed for bankruptcy in the last 6 years or so in Vietnam, credit risk has become a key risk for serious considerations from both company management as well as policymakers

This study is conducted to consider, examine, and quantify the financial distress for listed firms in Vietnam The choice of Vietnam in this study is interesting Vietnam has been achieving the second highest economic growth rates in the region and also in the world in recent years For the last almost 10 years or so, most countries in the Asian region faced financial difficulties arising from the global financial economic (GFC) Vietnam escaped from the GFC and achieved the high level of economic growth Vietnam has been generally considered rising stars in the stable economic growth and development in the world

Interestingly, the long-awaited Trans-Pacific Partnership is now officially dead in the water

by the new administration in the United States of America Even though Australia, Canada, and other members have been thinking of the TPP without the America, the future of this short-life trade agreement is in great doubt to come into force Australia has sent the signal of forming another trade partnership with the 10 ASEAN nations with the US being replaced by China This story has a long way to go since there are no concrete and serious discussions among nations Vietnam has also sent the clear signal that Vietnam has put every single effort to develop the national economy and integrate it with the world economy regardless of the establishment of the TPP or not Nevertheless, understanding and comparing credit risk of listed firms in Vietnam is indeed in an urgent need given the speed of regional integration Credit risks at industry levels are

a key consideration from this study

Standard approaches to measuring credit risks for listed firms in Vietnam and other countries include the accounting based approach and the market-based approach In this regard, the accounting-based models (such as the Altman Z-score and the EMS models) and the market-

based models (such as the Merton models) are employed to estimating the default probability of listed firms in the country of interest

This study departs from the current practice It is the intention of this study to develop a new model in which the three pillars of credit risks are considered: (i) factors from the market-based models; (ii) factors derived from the accounting-based models; and (iii) selected macroeconomic factors which are landed on a strong theoretical ground This approach is expected to provide a comprehensive evidence in relation to financial distress and bankruptcy of listed firms in Vietnam Our intensive literature review indicates that this study is the first of this kind in Vietnam and probably one of the first few studies in the region

1.2 Research Objectives

The key objectives of this study are as follows

 First, this study is conducted to identify early warning indicators of corporate financial

distress

 Second, the study is also conducted to build an appropriate bankruptcy prediction model

using market data for listed firms in Vietnam

 Third, selected macroeconomic factors affecting the financial distress and bankruptcy of

firms are considered and included in the so-called comprehensive model of bankruptcy prediction for Vietnam

 Fourth, a consideration of difference, if any, between different prediction models of financial distress and bankruptcy for listed firms before and after the Global Financial

Crisis

1.3 Research questions

In order to achieve the above research objectives, the following research questions have been raised:

 What are the fundamental indicators using accounting data (the Altman model) which can

be used to measure financial distress and bankruptcy for listed firms in Vietnam?

 What are the most relevant indicators using market data (the Distance to Default model) for measuring financial distress and bankruptcy for listed firms in Vietnam?

 What are typical macroeconomic factors which can be included in the comprehensive prediction model to measure financial distress and bankruptcy for listed firms in Vietnam?

 Do the prediction capacity of the multivariate discriminant analysis (MDA), the Distance

to Default (DD) and the comprehensive model change between crisis and non-crisis periods?

1.4 Structure of the thesis

The rest of this research is structured as follows Following this Introduction, chapter 2 presents the background and literature review of the related issues Data description, selection models, theoretical and empirical model are discussed in chapter 3 Chapter 4 details the results and discussion Several major conclusions and policy implications are concluded in chapter 5

Chapter 2 BACKGROUND AND LITERATURE REVIEW

This chapter includes three sections The first section presents the major cause of choosing Vietnam by analyzing Vietnam economy from the past to present Moreover, the effect of the global financial crisis (GFC) on Vietnam economy would be examined thoroughly in the second section The last section represents an important concept with reference to the financial distress likelihood in various approaches, comparison among default-risk models as well as some reviews

of default prediction in Asia nations

2.1 Why Vietnam?

Vietnam is the developing nation in the Asia having the high speed of economic growth This nation experienced the wartime difficulties a thousand years ago On 2 September 1945, Nguyen Ai Quoc announced the birth of Democratic Republic of Vietnam after a century had been fallen the unstable politics Unfortunately, the peaceful time no longer existed for a long time, the French colonialist and then the America invaded the nation again Afterward, North army under the leadership of the Vo Nguyen Giap General won the French military in Dien Bien Phu Battle This result led to the contract of the Geneva agreement dividing Vietnam into two regions The North Vietnam was the Democratic Republic of Vietnam under the control of the Viet Nam Worker’s Party while the South Viet Nam was the Republic of Vietnam under the leadership of French and later in America Finally, the North Vietnam has unified the South Vietnam on 30 April 1975 and then the independent country was born in 1976 in the Socialist Republic of Vietnam

Because of the long wars and civil wars, Vietnam suffered from the outdated technology and slow economic growth compared with developed countries After the war finished in 1975, the Communist Party took the government and then they built the economy of both nations following the socialist orientation Thanks to the great support from the So Viet Union, Vietnam had a large step of building and developing the nation The Soviet Model was applied successfully in Vietnam

by the Five-Year Plans As in Vo, D H (2008)’ research, the first Five-year plan was employed

in the period from 1976 to 1980 During the post-war reconstruction, this plan emphasized the

transformation from small-scale to large-scale production as well as the development of the heavy industry and agriculture sector Then all these industries had impressive growth with two fingers per year Nevertheless, the country’ difficult scenario had not improved after the liberation GDP rose only 0.4 percent per annum, meanwhile, the price level increased considerably around 20 percent and population rate jumped rapidly approximately 2.3 percent annually Therefore, this circumstance was also called in “the failure of command economy” In the period from 1981 to

1985, Vietnam had a multi-component economy in this stage The North Vietnam had three economic components including the individuals, collective and state-run, whereas, the South was the private capitalist as well as North’s three-plus joint state-private as discussed by Riedel, J., & Turley, W S (1999) There was a large difference between the Northern and Southern, it means that the unification ambitions of the two economies were met the great challenge So, the second Five-Year Plan was approved by the Party Congress to deal with economic problems in the previous period and set up the new “family economy” Following Vo, D H (2008), the major objectives of this plan were: (i) the application of advances in science and technology into the production line; (ii) the productive capacity is reorganized and developed in the modern fashion; (iii) improving the circulation and distribution of goods; and (iv) enhancing the standard of living Although national income had improved obviously in the initial period, the inflation rate increased sharply as 50 percent in the 1980s and even reached the galloping inflation with a peak of 588 percent in 1985 Consequently, almost of remarkable achievements from this plan were fallen as well as the living standard of human was still not improved In front of the difficult circumstances

of the nation, the demand for a comprehensive innovation was a priority mission The Communist Party of Vietnam (CPV) recognized the importance of the market economy and then launched the extensive economic programs called in the “Doi Moi” transition

Since 1986, Vietnam has shifted from a centrally - planned to a market-oriented economy This overall innovation was officially through the CPV’s Sixth National Congress In the first step

of the renovation process, the “entrepreneurial policy-makers” in the period from 1986 to 1994, the new Foreign Investment Law published in 1987 After that Vietnam welcomed a huge amount

of Foreign Direct Investments (FDI) entered almost economic sectors and the wave of FDI reached

10 percent of GDP in 1994 as discussed in the World Bank (1999) Moreover, the Corporate and Private Enterprise Law was modified to encourage the development of private business Vietnam was a food shortage to become the third rice exporter in the world Therefore, the living standard

was improved obviously as well as the inflation was controlled to motivate the economic growth The average GDP rose 8.2 percent per year in period 1990 - 1994, this finger was double compared

to the previous period In order to innovate more strongly, Vietnam has ignored the past conflict with the USA by normalizing relations with them This political innovation opened the great chance to corporate to developed nations, international organizations and multilateral donors as ADB as well as World Bank in the period from 1995 to 1999 or “Economic integration and adoption of market economy” However, the risk of losing national politics to other parties was high The CPV would like to develop a national economy without any political threats To balance the interests, CPV has continued its “Doi Moi” program with three major targets (i) Political stability is the top priority and the country has a unique party; (ii) Opening the foreign trade as well as an investment; (iii) The innovation process must be gradual in every scenario All of these objectives have been implemented by the CPV as well as government’s socio-economic and foreign policies The wave of FDI played the key role in economic growth because the FDI might create a million jobs for the labor market In 1996, over 10 billion dollars of FDI and a billion dollars came from the ADB as well as World Bank flowed into the nation Therefore, the Vietnam’ GDP increased considerably in 9.5 percent and 9.3 percent annually in 1995 and 1996 This is the highest rate recorded after Doi Moi period

Following the previous achievements, Vietnam entered a new stage of development or the economic boom and emerging cultural value in the period from 2000 to 2006 The financial market

is extended rapidly in economic terms but the scale of Vietnam stock market’s capitalization was insignificant, approximately 1 percent of GDP in 2000 However, this finger increased sharply in 22.7 percent at the end of 2006 and Vietnam Index was also risen 150 percent The stock market was a “fertile land” for financial investors According to General Statistics Office of Vietnam, the economy was ranked at 58th the largest economy in the world in 2006 and the GDP increased an average of 7.5 percent in period 2000 to 2005 A combination of high economic growth rate, low inflation, privatization of State-Owen Enterprises (SOEs) and a large amount of FDI assisted Vietnam to obtain the century goal or reducing poverty rate from 28.9 percent to 15.5 percent in

2006

In more recent, in the period from 2007 to present, despite having suffered from the impact

of the economic crisis in 2008.Vietnam has integrated deeply with the world and has acquired a great number of economic achievements Viet Nam was a member of many organizations such as

the World Trade Organization (WTO), ASIAN economic community (AEC), Asia-Pacific Economic Cooperation (APEC), International Monetary Fund (IMF) and World Bank (WB) Regarding Word Bank (2016), the GDP growth of Vietnam is 6.7 percent in 2015 and this number helps Vietnam stay in the high growth countries in the world Furthermore, the living standards are constantly being improved over the years with the GDP per capita obtained 2,107 dollars in

2015 as well as this income is five times higher than in 2000 Therefore, Vietnam is one of emerging market attracting the large foreign investment in the world as well as Vietnam has been looking a little tiger economy in Southeast Asia

2.2 Background to the Global Financial Crises

The liberalization of financial has been rising dramatically in recent decades The foreign investments (FDI), diversified risk, and international trade were stimulated strongly among nations Several countries have obtained the high economic growth and low unemployment rate

On the contrary, some nations have fallen considerable economic volatility and financial crises It

is the absolute truth that there are two large financial crises The first crisis is the Asian Financial Crisis (AFC) It began in Thailand in 1997, which spread to other developing regions in Asia and Eastern Europe during 1997 - 1998 The second crisis took into account this study is the Global Financial Crisis (GFC) - started in the US in 2008 and it expanded rapidly in the whole world with

a domino effect during 2008 – 2009

There is no doubt that the United State is center and starting point of the GFC in 2008 The real estate bubble was broken in late 2005 and then the considerable loans of investment and financial institution were difficult to refunding on time and some of them cannot even loss of ability to pay their liability This crisis affected strongly in the financial sector and it reached a peak in October 2008 when the series of huge banks in the USA were fallen the bankruptcy or merger The bankruptcy of Lehman Brothers pulled the default of US banks such as Morgan Stanley, Citigroup, and AIG by the bank run” or domino effect Due to joining the American real estate, Western nations as England, Spain, Iceland, and Ireland were sunk crisis in 2008 The stock market in New York, London and Paris decreased the lowest score in history One year later, the crisis spread in Asia area Although Japan has the strong financial systems, the third largest economy still was affected by the GFC The Nikkei Index in 2009 dropped sharply the lowest point around thirty years in Japan Similarity, China is the second largest economy in the world, this

nation was also negatively impacted of the GFC in 2009 after the economic growth miracle obtains always two fingers Under the impact of the GFC, the banking system of Vietnam also faced a great number of the risks The negative macroeconomic components from the GFC may enhance significantly the credit risk and bankrupt probability

Sharma and Mayanka (2013) argued that the demolishment of the US stock market in 2008 led to the bankruptcy of numerous large US banks and companies Afterward spreading rapidly in the whole world, most of Asia nations and Vietnam might be severely affected in 2009 -2010 According to the schedule of Viet Nam Government in 2008, the GDP growth was expected to be from 8.5 to 9 percent Due to the instability of macroeconomic, the National Assembly had adjusted the growth objective to 7 percent in 2008 Unfortunately, the GDP growth of Viet Nam

in 2008 reached only 5.7 percent or lower than 3.3 percent compared with the beginning growth target

Figure 1: Vietnam GDP annual growth rate from 2000 to 2015

Source: World Bank (2016)

A glance at the graph 1 provided reveals the GDP growth rates of Viet Nam during the period from 2000 to 2015 It is evident that Vietnam experienced considerable fluctuation in economic growth rate It fluctuated at somewhere between 6.2 and 7.5 percent prior to 2007, before dropping sharply to 5.4 percent in 2009 Viet Nam was heavily influenced by the GFC in 2008 such as the export decline, the stock markets faced difficulties and investors met disadvantages

whereas the real estate was frozen Thus, the GFC is a major cause of the dramatic decrease in the GDP growth rate in 2008-2009 In this hard time, the Viet Nam government employed five groups

of policies including the policies to stimulating production, business, and export; the policy for demand-stimulus of investment and consumption; the expanding fiscal and monetary policy; improving the Social Welfares Ensuring policies; and enhancing the management and organization policies These policies promptly and properly put Viet Nam out of the crisis rapidly The following a year saw a rapid climb in GDP growth rate, to somewhere in the vicinity of 6.4 percent

in 2010 When the stimulus package was no longer works, the global financial crisis affected continuously the economy and the GDP growth rate was decreased exponentially in the bottom of 5.2 percent in 2012, followed by a steady increase 0.2 percent in 2013 before having the considerable growth in 2015 with 6.7 percent Therefore, the Vietnam economy has returned to pre-crisis growth and was expected to be stronger growth in the future

Figure 2: Vietnam’s Inflation from 2000 to 2015

Source: World Bank (2016

Vietnam not only met the decline of growth, but also this nation faced the high inflation in the period 2008 – 2012 Increasing from approximately -1.7 percent in 2000 to 7.8 percent in 2004, the inflation rate then reached a peak of 23.1 percent in 2008 The expansionary fiscal and monetary policy released a large currency in the economy from 2000 - 2007, as well as the increase

in the oil price in 2007- 2008, were a major reason for the high inflation After that, it falls

significantly in 7.1 percent in 2009 because of a combination of fiscal and monetary policies However, this low rate existed only in a year The inflation rate increased rapidly 18.7 percent in

2011 when the consuming stimulation budget may not affect positively on the economy This followed by the period of exponential decline, with the inflation rate in the country plunged to a low of just 0.9 percent in 2015 This figure is the lowest in around fifteen years as well as demonstrates a good signal to rehabilitate the economy after immersing the stagnancy in a long period

Consequently, Vietnam’ economy experienced two stages The first state is pre-2009 with the positive economic scenario such as high growth, low inflation, low financial exposure and low default probability The second stage is post-2009 with the negative economic circumstance as low growth, high inflation, high credit risk and high bankrupt probability

2.3 Literature review on credit models

2.3.1 Background to corporate financial distress models

It is well known that there are five stages of the corporate bankruptcy The initial step is an incubation that the financial situation of the firm is developing Then, the manager realizes the financial distress condition of the firm is called the financial embarrassment The next is the financial insolvency state It means that the company is likely to not enough funds to meet its financial obligation This problem leads to the physical assets lower than the debt and it is called the total insolvency Finally, the confirmed insolvency is reached The firm is official bankrupted

by the decision of the courts as well as all of its assets must be sold to pay the creditors or debtors, which is proposed by Poston, Harmon, and Gramlich (1994) The financial distress is, therefore, different from the bankruptcy regarding the level In particular, the financial distress is the status where the firms may not cover the financial obligations from their creditors due to a loss in firm’s business operating, illiquid assets, high fixed cost, too much financial expense while the bankruptcy is a final state to stop doing business or dissolve the company because businesses cannot solve thoroughly the debtor’s loans in the financial distress state In some cases, the financial distress is likely to be detected before the company falls in the insolvency, and even this negative stage may be improved by the appropriate policies from the board director Thus, the bankruptcy risk is disappeared later while almost bankruptcy cases passing the financial distress

It is the absolute truth that all businesses have to wait for a period of time to asset liquidation or

dissolve the firm Theodossiou & Lee (1993)’ study indicated that almost USA businesses frequently lose the ability to pay loan approximately two years before proceeding bankruptcy Regarding Basel Committee on Banking Supervision (2016), the firm falls in the default state when they may not repay bank debt more than approximately 90 days Consequently, the default

is a quality proxy for bankruptcy or credit risk

In addition, Tinoco and Wilson (2013) recognized financial distress creates costly to debtors

so they took actions to avoid and decline that cost Some researchers construct a model to predict and measure the probabilities financial distress They built this model by combining factors can affect the firm’s financial distress include accounting variables, market variables, and macroeconomic variable Gilson (1997) studied the transaction costs and capital structure in case

of financial distress firms and he found that high leveraged lead high financial distress state due to high financial expenses and high financial obligations Moreover, the financial distress would happen rapidly when the cash flow could not compensate completely financial obligation afterward the old shareholders could lose the right to run the company in the hand of creditors, as discussed by Wruck (1990) When the loss of capability payment leads the financial expense more than the asset, the bankruptcy risk may rise significantly On the other hand, Foster (1986) demonstrated that the financial distress is not a hard problem and liquidity issue It could be solved completely by restructuring the large level of the business activities

Another special consideration, in this case, is that the numerous research projects have been done to predicting the corporate financial distress early in the world Since the first accounting-ratio-based model and, a great number of the bankrupt literature, the prognosis has been built by the Beaver (1966)' s study It has inspired and spread rapidly in the commercial and academic world In his research, he employed the dichotomous classification test to recognize the financial ratios for the bankruptcy prediction In particular, the best discriminant component is working capital/debt ratio estimating 90 percent accurately of the company that may one year before bankruptcy happens and the second best discriminant factor is the net income/total assets ratio, which correctly identified 88 percent Nevertheless, this research only predicts univariate for each financial ratio and do not associate to all financial ratios as well as market indexes to failure prediction The multivariate statistical model discriminating the failed firms from non-failed is developed by the first researcher E I Altman (1968) He revealed 22 financial ratios that may affect the bankruptcy and then they were classified into five categories including the profitability,

activity, liquidity, solvency, and leverage After that, the model was measured by employing the multivariate discriminant analysis (MDA) taken the linear association among five ratios With this Z-score number accounted accurately from the model, he divided the sample into two groups including 33 firms for each one (failed or non-failed firms) Consequently, the result could predict correctly 95 percent at one year prior to the bankruptcy, but this percentage drops sharply when the time rises two, three or four years and Z-score model focuses on the publicly traded firm model

as well as the adjustment is not valid

E I Altman, Haldeman, and Narayanan (1977)’ s study explored a new financial distress model (ZETA) The data included 53 failed firms and 58 non-failed firms concentrating in manufacture and retail firms from 1969 to 1975 Through the adjustment the financial ratios of the old model in 1968, the seven new ratios re-estimated successfully the new model by replacing book value to market value Therefore, the result might correctly identify 95% the firms one year prior to bankruptcy, and especially, 70% with five years prior to failure However, this research only was applied in a narrow area (manufacturer and retailer firm) or because of lacking the private firm's data, he did not test the model on the secondary sample E I Altman (2000) improved some disadvantages in the model in 1968 and 1977 by revealing the Z’’-score model that may only have four financial ratios after dropping out an X5 variable (Sales/Total assets) It could measure the financial distress prediction better than his two old models Alternatively, Z’’-score model has to

a considerable number of assumptions for independent variables, so, this model is like to be difficult to apply in the reality On the other hand, the Altman’s Z-score was tested directly in some papers such as Zmijewski (1984), Holmen (1988), and Begley, Ming, and Watts (1996) Namely, Begley’s research in 1996 employed the Z-score model to predicting 1365 firms in the period 1800-1890 with 78% accuracy rate The final version of Z-score model was the emerging score market model (EMS) EMS model included the typical characters of the emerging market ESM seemed appropriate to estimate the default probability for developing countries and ranking the firms by the specific score Namely, there were three important components impacting strongly on the EMS model (i) The currency depreciation (ii) its industry integration (iii) the competition in the industry EMS model was applied to the Mexican firms before the crisis in 1994 by E I Altman (2005) The specific model is that:

𝑍" = 6.56𝑋1+ 3.26𝑋2+ 6.72𝑋3 + 1.05𝑋4+ 3.25 (1)

Where:

𝑋1: Working capital/total assets

𝑋2: Retained earnings/total assets

𝑋3: Earnings before interest and taxes (EBIT)/total assets

𝑋4: Book value of equity/book value of total liabilities

The Z-score standard of the probability insolvency:

 Z" > 2.6: Safe zone, the firms have healthy finance or no risk of bankruptcy

 1.1 ≤ Z" ≤ 2.6: Grey zone, warning zone The financial exposure in a low level or the potential bankruptcy

 Z" < 1.1: Bankruptcy zone, dangerous zone The default probability in a high level

However, Ohlson (1980) showed that almost seminal studies may not reflect exactly timing issue and there are several limitations of Z-score model In his study, he employed the logit model

to bankruptcy prediction He took the data of 105 failure and 2058 non-failure firms from 1970 to

1976 in U.S He used the log of total assets over GNP price level index to denote the size of company, total liabilities over total assets to denote the financial structure which highly affects to the interest expenses, working capital to total assets and current liabilities to current assets to denote the current liquidity, net income to total assets denote the performance, funds provided by operations to total liabilities, the binary one if exceed the total liabilities and the total assets positive the another binary one if net income is negative, the disparity net income over consecutive year Zmijewski (1984) was one of the researchers utilizing accounting variables to measure the

proportion of financial distress, with different ratios: (i) net income to total assets, (ii) total debts

to total assets, (iii) current assets to total liabilities, under random exogenous sampling and the

Probit regression Whereas almost the bankruptcy assumed that the macroeconomics components may not impact on their accounting-based model, the controversial happened in the reality The interest rate and inflation factors affect strongly on the financial distress model Mensah (1984)' s study reevaluated the corporate bankruptcy model He created four models for four periods of time 1972-1973, 1974-1975, 1976-1977 and 1978-1979 to cover the change of the economic environment The outcome indicates that the new model predicted exactly over the four economic stages

In the Greece, Theodossiou (1991) used both Logit and Probit model with from 1975 to 1986 for identifying early warning indicators of financial distress The result suggested that the Logit is likely better than the Probit model Another research in Turkey, Ugurlu, and Aksoy (2006) employed the multivariate discriminant analysis (MDA) and Logit model in their study with 27 failed and 27 non-failed firms on Istanbul stock market from 1996 to 2003 There were 11 variables

in Logit model and 10 variables in MDA model The outcome was that the Logit model is better than multivariate discriminant analysis (MDA) model In a recent paper, Stanisic, Mizdrakovic, and Knezevic (2013) built the bankruptcy prediction model in the Republic Serbia They applied three methods involving the Logistic Regression, Decision Trees, and Artificial Neural Networks

on the training sample with 130 firms and then compared a new model with Z-score model of Altman professor The results demonstrated that only one model employed the Artificial Neural Networks method is better than the Altman’s Z-score Alternatively, the accounting-based approach is likely criticism on some controversial viewpoints such as it is not informative enough

to reflect the future trend

One thing which is equally important is that the decline of the asset value or the fall in the liquidity, in particular, the decrease in the capability of raising the capital is the major causes of the insolvency There are three components of the default business The first is a value of the asset, the second is the asset value of the uncertain risk and the third is the financial leverage If the valuable asset is lower than the book value of the liability, the firm may fall in the default stage Furthermore, the value asset was a powerful indicator of the bankruptcy prediction because it reflected directly the current status of the firm by Black & Cox (1976) and H E Leland (1994)

In this regard, the option based approach has been appealing and spilling into the commercial world Black & Scholes (1973) and Merton (1974) invented the call option theory that is a fundamental theory of a market-based approach Their contingent claimed approach may motivate

to employing the option theory on the corporate default prediction Namely, in the option based approach, the equity of firm has the equity claim on the assets after the company pays all its financial obligations The call option is regarded the market value of asset and face value of debt

is strike price In the maturity of the debt, the holder of the call option will do exercise their option when the value of the asset is higher than the face value of the liabilities Otherwise, if the value

of the assets is likely, not sufficient to pay the firm debt, the strike price will not exercise or the

holder of the call option may leave the company to the debtors The Metron model, furthermore, became the fundamental analysis of the Distance-to-Default model (DD)

In the previous works, Vasicek (1984)’ study compared the value of assets with the level of liability of the firm’s capital structure to determine the probability of corporate default Afterward,

in the empirical researchers, Delianedis & Geske (2003) and H Leland (2002)’ study, the measured size of the structural model or the theoretical probability was a powerful predictor on the credit rating and credit transition Several papers illustrated the usefulness of the structural model as well as the development of the option-based model The Crosbie and Bohn (2003) demonstrated that the probability of the bankruptcy is one of the most powerful predictors to managing the credit portfolio The Distance-to-default (DD) was calculated similarly to the option-based model The determination of the default probability included estimate the asset value and volatility, calculate the distance-to-default as well as calculate the probability of default Moreover, the structural model of the Moody enhanced the reliability of the Merton model by using the global database to measure the expected default frequently (EDF) Stein (2005) indicated that amount of evidence about the necessity of adjusting the option-based model If the failure and the non-failure group were classified perfectly by the additional information, the traditional Merton model that is not modification would not have reduced the accuracy

In some recent researchers employed the structural model to measure the default risk and then, the examination of the correlation between default risk and other variables The Vassalou and Xing (2004) applied the Merton model to estimate the default likelihood indicator (DLI) for individual companies as well as exam the relationship between the default risk and the return equity The Friewald, Wagner, and Zechner (2014) illustrated the close relationship between the firm’s stock return and credit risk by using the option-based model Therefore, the structural model had become the underpinning theory of a great number bankruptcy prediction researchers Patel & Vlamis (2006) depended on BSM- Prob model with contingent claim approach and KVM corporation framework as well as the dataset of 121 real estate firm in the period 1980-2001 to measuring exactly the distance-to-default and the “risk neutral” bankruptcy probability The outcome divided the bankruptcy and non-bankruptcy group into two errors The type I error was the KVM model fail to predict the bankruptcy but it did occur while the type II error was the KVM model predict default but it did not occur The result indicated that the type I error does not appear

in our estimation whereas there are 10 over 121 firms fall in the type II error The high asset volatility and the high leverage were two driving forces of default

In addition, the Bystrưm (2006) explored three assumptions to adjust the Merton to-default to appropriate for the emerging market and volatility of environment Similar to the Merton DD, the asset volatility and firm leverage ratios played a major role in the default The Bharath and Shumway (2008) examined the precision and combination of the option-based model This structural model was compared with the “nạve” alternative that did not employ the default probability in solving the model The alternative model outperformed in the hazard model as well

Distance-as out-of-sample forecDistance-ast than the Merton model They found that the structural model is not sufficiency statistic enough for the probability of default whereas its functional forms were appropriate to the prediction default In a seminal work, the Koutsomanoli-Filippaki and Mamatzakis (2009) calculated the Merton-type bank risk and utilized the penal VAR analysis to examine the relationship between the efficiency and risk The impact of one standard deviation shocks to the DD on inefficiency was negative and substantial Huang and He (2010)’ research calculated the new distance-to-default point of KVM to establish a new structural model The new model was likely to appropriate to the seven major Chinese banks in the period before the global financial crisis (2008) 2004-2007

Similarly, D E Allen and Powell (2012) incorporated the market value of assets to examine the corporate default of the Australia banks by the option-based model or KVM-Merton model The Australia default risk was likely to be higher in the GFC stage because of the volatility of the asset value Generally, the bank field had a lower the level of equity than other sectors The Charitou, Dionysiou, Lambertides, and Trigeorgis (2013) estimated the predictive accuracy of the Black–Scholes–Merton (BSM) bankruptcy model after that BSM model was expanded by adding directly market-observable returns on company value The outcome sheds new light on the simple model having the direct market-observable performs more strongly than the complicated model

In the most recent paper, the Agrawal, Maheshwari, Khilji, and Swinkels (2016) employed the logistic regression and the multiple discriminant analysis (MDA) with the Merton Distance-to-Default (DD) to matching the bankruptcy and non-bankruptcy group and predicting the default of the listed India firms Similar to the seminal study, the DD variable was statistically significant in prognosis the default as well as negatively related to the probability of the bankruptcy Although the Z-score was added to the model, the Distance-to-default was still significant

2.3.2 Comparison of accounting-based and market-based models

It should be borne in mind that the market-based has been appealing on several grounds: (i) the timeliness of the corporate bankruptcy prediction may be risen exponentially by the combination of the market-based variables (ii) The volatility of the market-based variables is calculated directly by the market index to enhancing dramatically the powerful indicator of the default risk The fluctuation plays a key role in the default prediction The higher volatility led to greater the probability of the default was proposed by the Beaver, McNichols, and Rhie (2005) (iii) The information from the financial statement and others do not belong to accounting statement are reflected generally by the market price (iv) The market price is likely to be more suitable to the default prediction due to it reflects the forward-looking information or the future expectation

of the cash flow whereas the accounting-based only reveals the backward-looking or past performance Moreover, the Hillegeist, Keating, Cram, and Lundstedt (2004) indicated that the stock market contains almost the kind of the financial information including the accounting statement and the information from the stock market regards the alternative source in some cases With the forward-looking information, the market price was likely to be appropriate for corporate default prediction If the researchers only applied the accounting statement variable on their corporate bankruptcy prediction, it means that all of the forward-looking and other financial information or the relevant failure is exploited on the annual account while the financial statement only reflected backward-looking side instead of all relevant information and the market-based may cover the disadvantages of the accounting-based perfectly

Another stream of the default prediction literature focuses on the market-based prediction model, a substantial number of the empirical studies has illustrated the inferiority of the accounting-based model over the market-based model and vice versa Unfortunately, the outcomes acquired from those researchers have been unobvious because of numerous suppositions as well

as without the solid base of the theory In a previous paper, the Hillegeist et al (2004) revealed that not only the Altman’ Z-score and O-score model may not outperform the Black-Scholes-Merton model about the information of the probability bankruptcy but also the study employing the market-based model is the best representative of the probability default Furthermore, Gharghori, Chan, and Faff (2006) attempted to compare three kinds of the default risk models including option-based model, path-dependent barrier option model, and Z-score model The result demonstrated that the option-based model outperforms other models and should be employed to

ranking firms by bankruptcy probability Likewise, the W Miller (2009) performed two corporate default prediction models including the Altman’ Z-score applies researcher and the Distance-to-Default model employs the practitioners The manufacturing firms and non-manufacturing firms were tested in the research The outcome indicated that the Distance-to-Default model outperforms the Z-score model and the DD is more durable than the accounting-based model

Nevertheless, the reverse is also the case, the option-based model requires a considerable number of suppositions For instance, L Allen and Saunders (2002) revealed that the highlight theoretical model demands the supposition of normality of stock returns It assumed that the model only has a kind of debt instead of existing numerous of the debt in reality Moreover, the company only has a single coupon loan and the value of assets as well as the asset volatility which are unobservable must be estimated perfectly Campbell, Hilscher, and Szilagyi (2006)’s study demonstrated that if the several variables are controlled completely, the accounting-based model will have pretty predictive power Obviously, in the Reisz and Perlich (2007)’ study, the predictive capability of the Z-score model might outperform the Merton model in a year period In a recent paper, the Agarwal and Taffler (2008) illustrated that the market-based model is not superior accounting-based model depends on the financial ratio According to the capable prediction, the existence of a pretty difference between two models

Even if the one model may be superior to others, it does not mean that the superior model is likely to be abandoned altogether Therefore, the combination of two kinds of the model into the general model is possible more powerful prediction than one approach either the traditional accounting-ratio-based or the market-ratio-based model In particular, Y Wu, Gaunt, and Gray (2010)’ s research collected the dataset of the company bankruptcies from New Generation Research (www.bankruptcydata.com), Compustat and CRSP in the period 1980-2006 testing the five kinds of the corporate default models including ((E I Altman, 1968) – MDA model based on accounting variables, Ohlson (1980) – logit model with accounting ratios, Zmijewski (1984) – probit model using accounting data, Shumway (2001) – hazard model with both accounting and market variables; and Hillegeist et al (2004) – BSM-Prob model based on both accounting and market variables According to the tests, the key variables were classified thoroughly to build the comprehensive model that reflect accounting information, market data, and firm characteristics Consequently, the new comprehensive model capturing diversify sides of the bankrupt probability outperformed other model and was seemingly the most reliable model to predict the future default

Furthermore, Li and Miu (2010) employed a binary quantile regression approach to building successful hybrid bankruptcy prediction model linking the accounting-based and, the market-based model The default and non-default group were classified clearly from Compustat database

in the period 1996-2006 The result demonstrated that the z-core driven from accounting-based approach is statistically significant in explaining those companies having the good credit quality while the Distance-to-Default (DD) variables taken from the market-based model are statistically significant in interpreting those companies having the poor credit quality The Tinoco and Wilson (2013) employed the sample of 23218 UK firms in the period 1980-2011 and Neutral network (MLP) technique to establish the default prediction model Especially, a new model is the combination of the accounting, market, and macroeconomic data In more recent work, Trujillo-Ponce, Samaniego-Medina, and Cardone-Riportella (2014) illustrated that the comprehensive model including market-based and accounting-based is the most reliable model for predicting financial distress either z-core or KVM-Merton model By utilizing the 2186 credit default swap

in the European market in the period 2002-2009, the comprehensive model might forecast exactly the default probability in the volatile period

There is a number of the bankruptcy researches about China or the second largest nation The Fan, Huang, and Zhu (2008) also emphasized the impact of institutional background It is argued that institutional background considerably distorts the decision of those That is, distressed firms’ behavior mostly depends on its characteristics and less influenced by outside factors like bankruptcy law and creditors For in-depth analysis, the researcher has demonstrated that ownership structure is one of the firm characteristics produces a significant influence on firms’ behavior during their financial distressed For example, Stated-owned Enterprises (SOEs), which are recorded less sensitive to financial distressed than their counterparts: non-SOEs, probably adjusted slowly to financial difficulty in the post-distress period which reflected by relatively higher leverage, a higher fraction of long-term liabilities and a higher level of external investment Furthermore, the hypothesis of institutional background does not only explain the cross-section differences in firm behavior but also explain how firms adapt their decisions in distress, the research utilized the different definition of distress, different criteria for distress, different specification, different regression method For those robustness tests, the hypothesis performance remains unchanged

Depending on the original Z-score’ Altman, L Zhang, Altman, and Yen (2010)’ the research developed into the China Z-score Namely, the form of the new model was similar to the Z-Score emerging market model (EMS) From fifteen financial ratios, the author classified into only four major variables by the discriminant analysis and the working capital over total asset variable was one of four variables that are identical to EMS model The new Z-score model was applied to a considerable number of the china listed firms taken from Tinysoft Finance Analysis Database as well as Shenzhen GuoTaiAn Information technology in the period 1998–2008 Surprisingly, while the original Z-score model only forecasts accurately a year in advance, the China Z-score model predicts three years in advance with 80 percent accuracy Moreover, in the Wang & Campbell (2010)’ study, the Ohlson model was re-estimated to predicting the financial distress with numerous China publicly listed firms in the period 1998-2008 The outcome indicated that if the total liability is higher than the total asset or the net income is negative two years continuously, the firms may fall in the bankrupt state In more recent, Paolone and Rangone (2015), the emerging market model (EMS) was applied to forecasting the effect of the global crisis on the bankruptcy

in China In particular, the accounting data of the 3220 Chinese publicly traded firms during the global crisis period (2008-2014) was collected to calculating the EMS score for each state and in the whole period The result indicated that 71.93 percent do not have the bankrupt probability and only 6.18 percent have bankrupt probability in the crisis period

Low & Yatim (2001) examined the efficiency of predicting the default probability of two famous factors as profitability and liquidity in Malaysia The research data included approximately

176 Malaysian companies divided into nine industries and the logistic regression was also employed in this study Surprisingly, almost financial ratios representing profitability and liquidity were useless to measuring the financial distress or the firms who have high profitability and liquidity unsure to capture their financial obligations The level of cash position was the most critical ratio and affected directly the financial distress likelihood The higher the cash position lead to lower the probability of insolvency and the predictive accuracy could achieve over 80 percent In Thailand, Meeampol & Noonoi, R (2014) used Z-score model and emerging market score model (EMS) to predicting the financial distress of the listed companies on the Thailand stock exchange Two kinds of models could forecast exactly the probability of default but the accuracy level of the Z-score model was likely to be pretty higher than EMS model

In fact, there are only a few several bankruptcy studies in Vietnam Almost Vietnamese researchers employed the famous technique such as the Z-score and Merton model to predict the financial distress Canh (2013)’ research was a typical example He employed the Z-score’ Altman for five state banks and twenty commercial banks in Vietnam The long period dataset (2002-2012) may assist him to exam the effect of the global financial crisis on the bank system The outcome revealed clearly that the default risk in the post-crisis seems more serious than the pre-crisis and the bankruptcy of the state bank is higher than the commercial bank in Vietnam If Canh (2013)’ study followed the accounting-based approach, Chi and Anh (2013) applied the market-based model or Merton model to predict the default probability of 6598 customers at the Joint Stock Commercial Bank for Foreign Trade of Vietnam (Vietcombank) in the period 2008-2013 The result indicated that the default probability of the whole portfolio is somewhere in the vicinity of 2.6% or VND 6319 billion Surprisingly, almost large-size firms had higher the default probability than the small-size companies and the classification among the economic sectors Namely, the highest bankrupt probability was the production, seafood processing industry and, electricity while the lowest default probability was the road transport and inland waterways

Chapter 3 RESEARCH METHODOLOGY

This chapter concentrates in the data source and research method The financial distress likelihood is carefully estimated by the accounting-based and market-based approach Not only a large number of variables is collected to build the new model including the accounting, market and macroeconomic variables, but also the theory of logistic regression and a special technique of comparing among models would be presented completely in two last sections

3.1 Data

This study is conducted on a dataset which covers more than 800 listed firms in Hanoi stock exchange (HNX) and Ho Chi Minh stock exchange (HOSE) for the period from 2003 to 2016 All data are collected from Bloomberg for all 11 different sectors Almost the accounting data comes from the financial statement while the stock price plays a major part of market data Macroeconomic data is collected from the World Bank website Especially, the model will predict corporate bankruptcy and compare each other through the GFC stage including the pre- and post- the GFC

3.2 Analytical framework

The below analytical framework is developed for the purpose of this study

Figure 3: Analytical framework

Where:

EMS: Emerging Market Score DD: Distance to default Comparison among models: the model fit standard as the Pseudo R2 and Receiver Operating Characteristics area (ROC)

Each model would estimate default probability in pre-crisis, during crisis, post-crisis and the whole period

In terms of valuable information from previous studies, the methodology is adapted to analytical framework above In particular, the financial risk is estimated by accounting-based or EMS model and market-based approaches or DD model In order to cover almost factors affecting

to businesses, the comprehensive model including the accounting, market as well as macroeconomic variables is established completely and logistic regression is employed to measuring the financial distress Not only the Pseudo R2 and Receiver Operating Characteristics

Accounting-based model (EMS)

Market-based model (DD)

Default Probability Macroeconomic variables

T MODE

L

area (ROC) are used for comparing among models but also the likelihood of insolvency is examed seriously in different scenarios as pre and post-crisis stages

3.3 Estimating financial distress

No one can deny that the multiple discriminant analysis (MDA) is one of the best ways to predict the default probability when the dependent variable is qualitative form This statistical technique is acquainted with classifying observations into one of some prior groups having the private characteristic In this study, the bankrupt and non-bankrupt group is determined efficiently

by the MDA technique The score that is calculated from the discriminant function is used for classifying the default and non-default group

The discriminant function is presented as below:

Z = 𝛼 + 𝛽1𝑋1+ 𝛽2𝑋2+ 𝛽3𝑋3 + …… + 𝛽𝑛𝑋𝑛 (2)

Where:

Z: Overall Index

𝛼: Constant of the function

𝛽: Coefficient of the independent variables

𝑋𝑖: Independent variables

𝑛: Number of independent variables

Not only the E I Altman (1968)’ research explores the discriminant technique but also, he constructs a model to predict financial distress with the financial and, economic ratios The fundamental function is built by the essential traditional discriminant model and then, it is developed the multiple discriminant analysis (MDA) After testing a considerable number of financial variables, the five following variables: (i) working capitals over total assets (X1), (ii) retained earnings over total assets (X2), (iii) earnings before interest and taxes over total assets (productivity of assets), (iv) market value of equity over book value of total debt (X3) and (v) sales

over total assets (X4) Each indicator measure liquidity, profitability, the productivity of assets, solvency prevailed and sales generating ability of assets respectively

Depending on the Z-score’ Altman in 1968 that only estimate manufacturing publicly traded firms, E Altman (1983) modified the Z-score model to Z’-score model that is used to the private manufacturing firms or unpublished companies In particular, the market value of equity was replaced by the book value of equity For he would like to estimate more type of firms, the Z’’-score model is invented by himself E I Altman (2000) The Sales over the total asset (X5) is dropped out the model because of minimizing the potential industry effect

In this research, the emerging market scoring model (EMS) for rating emerging market credits of the E I Altman (2005) is employed to estimate the default probability A number of factors may account for this choice is that the EMS model depends on the basic financial review taken from a qualitative risk model and, the EMS model is a final modified rating of the assessment

of the specific credit risks, as well as the modified EMS model, has specific characteristics of the emerging market or it is well designed for developing nations as Vietnam Moreover, the EMS model is generated by capturing the advantages as well as improving the disadvantages of previous models including Z, Z’ and Z’’-score model All of the coefficients of four variable from X1 to X4 is similar to the Z’’-score model and EMS score are added the constant term of +3.25

The emerging market scoring model (EMS) is presented as below:

𝐸𝑀𝑆 − 𝑆𝑐𝑜𝑟𝑒 = 6.56𝑋1+ 3.26𝑋2+ 6.72𝑋3 + 1.05𝑋4+ 3.25 (3)

Where:

𝑋1: Working capital over total assets (WC/TA)

𝑋2: Retained earnings over total assets (RE/TA)

𝑋3: Earnings before interest and taxes (operating profit) over total assets (EBIT/TA)

𝑋4: Book value of equity over total liabilities (BVE/TL)

The EMS score standard for the probability insolvency:

- EMS − Score > 5.85: Safe zone, the firms have healthy finance or no risk of bankruptcy

- 4.15 ≤ EMS − Score ≤ 5.85: Grey zone, warning zone The financial exposure in a low level or the potential bankruptcy

- EMS − Score < 4.15: Bankruptcy zone, dangerous zone The default probability in

a high level

Table 1: EMS score and equivalent rating

Different from the accounting-based approach or Z-score model applying almost components from the financial statement to analyzing the default probability, whereas, the option-based approach or the Distance-to-default model (DD) employs the market value of equity and trading price to measuring the financial distress In particular, the KVM-Merton model was explored in 1974 by the Merton (1974)’ s study depending on the option theory of the Black and Scholes (1973)’s research The KVM firm developed the option theory to become the distance-to-default model that might estimate the failure of the company The DD model illustrated that the number of the standard deviations that the firm value is from the default point The low value of the distance-to-default means the business is closer the default point or the company has a high

probability of bankruptcy Crosbie and Bohn (2003) and Vassalou and Xing (2004) illustrated two essential assumptions of the DD model The first supposition was that the market value of the firm

is discriminated by the geometric Brownian motion (GBM):

𝑑𝑉 = 𝜇𝑉𝑑𝑡 + 𝜎𝑣𝑉𝑑𝑊 (1)

Where:

V: Total value of the firm,

μ: Expected continuously compounded return on V

𝜎𝑣: Volatility of firm value

dW: Standard Wiener process

The second assumption of the model presents that the firm has issued only one single coupon bond maturing in T periods (one year) Several assumptions added in the DD model as the firms may not have any financial support and renegotiation of the company’s debt obligations; default boundary is constant, and liquidation of the firm is costless Therefore, the relationship between the market value of equity and the market value of assets are expressed as below:

E: Market value of the firm’s equity

V: Market value of the firm’s assets

F: Face value of the firm’s debt

r: Risk-free rate

T: Time to maturity of the firm’s debt

N: Cumulative standard normal distribution function

σE: Volatility of the firm’s equity

σv : Volatility of the firm’s value

The relation between the equity volatility and volatility of the firm’s value are expressed following:

𝜎𝐸 = (𝑉

𝐸)N(𝑑1) 𝜎𝑣 (5) Solving the above two non-linear equations gives the firm’s value, V, and its volatility,

𝜎𝑣.and the face value of the debt (F) The Distance-to-Default is established following expression:

DD Merton = 𝑙𝑛(

𝑉

𝐹 )+(𝜇− 0.5 𝜎 𝑣 2)𝑇

𝜎𝑣√𝑇 (6) Due to the constant debt of the Merton model’ s assumption does not have empirical support, the Distance-to-default model was adjusted to improve this disadvantage and more focus on the default such as the firm leverage ratio as well as equity volatility in this research In particular, the modified version of the DD model advocating a constant leverage ratio is likely more realistic and dynamic than the traditional Merton model Consequently, the new DD model may estimate the default probability for many kinds of firms Especially, the modified version might measure effectively the financial distress in the emerging markets or the volatile markets as Vietnam and China (Byström, 2006)

The Byström (2006) explored the simple version of DD model that only employs three components or observable parameters to estimate default probability such as the book value of the firm liability, the market value and the volatility of equity The simplification depends on three assumptions (i) In reality, the drift term ( (μ − 0.5 σv 2)T) is revealed relatively small and it seems hard to measuring the drift rate of stocks and other assets Thus, we assume that the drift term is small or to be zero (ii) The second assumption is that, in the extreme case, the market value of the asset (V) is close to the book value of the liability and the highlight asset volatility is relatively high and is N(d1) significantly different from 1 Therefore, the N(d1) is supposed to be one (iii) Due to the book value of liability must be paid back or is not calculated by the market value So, the book value of debt is employed to accounting leverage ratio

Depending on the first assumption, the drift term equals zero or the maturity of liability is a year The traditional Merton model is reduced as follows: