A Three Variable Model on the Risk Level of Viet Nam Wholesale and Retail Industry During and After the Global Crisis Download PDF

Journal Name : SunText Review of Economics & Business

DOI : 10.51737/2766-4775.2020.011

Article Type : Research Article

Authors : Dinh Tran Ngoc Huy

Keywords : Risk management; Asset beta; Financial crisis; Corporate tax; Leverage; Competitive firm size

Abstract

Over recent years, wholesale and retail industry in Viet Nam has reached a lot of achievements. Under the volatility of stock price, and changes in macro factors such as inflation and interest rates, the well-established wholesale and retail market in Viet Nam has many efforts to recover and grow from the crisis 2008. This study analyses the impacts of 3 factors: competitor size, tax rate policy and leverage on market risk for the listed firms in the wholesale and retail industry as it becomes necessary. First, by using quantitative and analytical methods to estimate asset and equity beta of total 9 listed companies in Viet Nam wholesale and retail industry with a proper traditional model, we found out that the beta values, in general, for many companies are acceptable. Second, under 3 different scenarios of changing tax rates (20%, 25% and 28%), we recognized that there is the largest dispersion in equity beta value (0, 22), if tax rate is up to 28%, leverage up to 30% and doubling size competitors. Third, by changing tax rates in 3 scenarios (25%, 20% and 28%), this study identified that the risk dispersion level in this sample study could be minimized in case the competitor size slightly smaller, tax rate up to 28% and financial leverage up to 30% (measured by asset beta var of 0,022). Finally, this paper provides some outcomes that could provide companies and government more evidence in establishing their policies in governance.


Introduction

Throughout many recent years, Viet Nam wholesale and retail market is evaluated as one of active markets, which has certain positive effect for the economy. There are many components which affect the risk level of these firms including, but not limit to, external factors (tax rates, interest rates, competitors…) and internal factors (management, leverage, technology, strategy,…), in the context of most global stock markets including Vietnam stock market experienced a downturn in the year 2009 (see exhibit 1). The scope of this paperwork covers the influence of 3 factors on the market risk of these listed companies, including: tax rates, financial leverage or external financing, and the competitive firm size. The organization of paper contents is as following. As our previous series of paper, the research issues and literature review will be covered in next sessions 2.1 and 2.2, for a short summary. Then, methodology and conceptual theories are introduced in session 2.3 and 2.4. Session 3.1 describes the data in empirical analysis. Session 3.2 presents empirical results and findings. Then, session 4 will conclude with some policy suggestions. This paper also supports readers with references, exhibits and relevant web sources.


Preliminary Notes

Research issues

Among the research areas of the paperwork are:

Issue 1: Whether the risk level of wholesale and retail firms under the different changing scenarios of tax rates increase or decrease so much?

Issue 2: Because Viet Nam is an emerging and immature financial market and the stock market still in the starting stage, whether the dispersed distribution of beta values become large in the different changing scenarios of leverage estimated in the wholesale and retail industry.

Issue 3: Whether the risk level of wholesale and retail firms under the different changing scenarios of competitive firm size increase or decrease so much?


Literature Review

The Merton model (1980) mentions the market equity premium is a positive function of the market risk which can be measured by the variance of premium. Regarding to researches on financial crisis, risk and cost of capital, financial crises are results from bubbles in real estate industry. And during crisis the borrowing amount against various collateral types can vary significantly [1].

The three factor model that “value” and “size” are significant components which can affect stock returns [2]. They also mentioned that a stock’s return not only depends on a market beta, but also on market capitalization beta. The market beta is used in the three factor model, developed by Fama and French, which is the successor to the CAPM model by Sharpe, Treynor and Lintner. Then implies the challenge is building a risk management strategy while market participants know all the assumptions behind market risk models and measures [3]. Findings on market risk of real estate can be useful for practitioners achieving a more accurate portfolio risk management [4]. On the other hand, mentions a two-rate tax system where land is taxed at a higher rate than structures in his research on two-rate property tax effects on land development. Mentions in Chicago, properties located in a designated TIF (tax increment financing) district will exhibit higher rates of appreciation after the area is designated a qualifying TIF district when compared to those properties selling outside TIF districts, and when compared to properties that sell within TIF district boundaries prior to designation. Recognized that the user cost tax elasticities are relatively small while the expected house price inflation elasticity is substantially larger and therefore plays a greater role in affecting housing market demand. Transaction taxes have no impact on house price growth. And their findings suggest that capital gain taxes on real estate are not suitable measures to prevent excessive house price growth.

Then, also indicated that business property values are more responsive to changes in tax rates as compared to residential property [5]. Next, said liquid markets can enable investment in long-term investment projects while at the same time allowing investors to have access to their savings at short-term notice. Stated financial institutions and markets allow cross-sectional diversification across projects, allowing risky innovative activity. Mentions equity volatility increases proportionally with the level of financial leverage, the variation of which is dictated by managerial decisions on a company’s capital structure based on economic conditions [6]. And for a company with a fixed amount of debt, its financial leverage increases when the market price of its stock declines. Pointed the history of finance is full of boom-and-bust cycles, bank failures, and systemic bank and currency crises. Company can also proactively vary its financial leverage based on variations on market conditions. Stated that safer assets must offer higher risk-adjusted returns than riskier assets and that consuming the high risk-adjusted returns of safer assets require leverage, creating an opportunity for investors to apply leverage. Also mentioned using financial leverage increases the total risk of the firm by increasing the volatility of a corporation’s net income and return on equity.

Last but not least, showed that the impact of Basel III on the regulator’s welfare depends on the regulator’s strength, and the implementation of an identical leverage ratio across countries would decrease the welfare of regulators with strong powers [7]. Next, identified a safe regime, in which excessive leverage does not result in an increase of systemic risk, and a risky regime, in which excessive leverage cannot be mitigated leading to an increased systemic risk [8]. And revealed that in different industries in Sri Lanka, the degree of financial leverage has a significant positive correlation with financial risk.

Beside, found out the intensity of product market competition increases, principals unambiguously provide stronger incentives to their agents to reduce costs, and hence agents work harder [9]. At the same time, more intense competition also leads to a higher volatility of both firm-level profits and manager’s compensation. Group constructed the market shares of insured competitor banks for any given bank, and analyse the impact of this variable on banks' margins and risk-taking behaviour, using a large sample of banks from OECD countries. Their results suggest that government guarantees to some banks strongly increase the risk-taking of the competitor banks not protected by such guarantees. In this paperwork, the total combined effect of three (3) factors: tax rates, financial leverage, and competitor size on market risk of listed whole sale and retail companies will be estimated [10-12].

Conceptual theories

The impact of competition or the size of competitor, leverage and tax rates on the economy and business. The central bank and government or Ministry of Finance could use two tools: fiscal and monetary policies to perform macro-economic goals [13,14]. Tax rate is one of fiscal policies, either expansion or contraction, can affect quickly the aggregate demand and good market and industry growth. Beside, on the one hand, using leverage with a decrease or increase in certain periods could affect tax obligations, revenues, profit after tax and technology innovation and compensation and jobs of the industry. On the other hand, using financial leverage and changing capital structure offers firms better economic conditions. Firms can vary the capital structure with leverage and change the structure of fixed costs and variable costs. Although leverage can help a firm to increase return, the firm will prefer to increase debt up to a point to be not so nervous about risk because of too much debt financing. During the firm life, leverage can contribute to its performance and growth. Furthermore, Porter’s theory shows us the basic unit of analysis for understanding competition is the industry. And Porter stated that the industry is the arena in which the competitive advantage is won or lost [15]. Beside, competition can help to raise the value of a company by eliminating or reducing monopoly. Sources of competition include, but not limit to, training. Increasing training can help competition raising productivity [16,17].


Methodology

We use the data from the stock exchange market in Viet Nam (HOSE and HNX) during the 2007-2011 period to estimate systemic risk results. In this study, analytical research method and specially, tax rate scenario analysis method is used. Analytical data is from the situation of listed wholesale and retail firms in VN stock exchange and current tax rate is 25%. Finally, we use the results to suggest policy for both these enterprises, relevant organizations and government.


Main Results

General data analysis

The research sample has 9 listed firms in the wholesale and retail market with the live date from the stock exchange. Firstly, we estimate equity beta values of these firms and use financial leverage to estimate asset beta values of them, and the results are estimated under effects of another variable: competitive firm size (changed from approximate size to doubling size and slightly smaller). Secondly, we change the tax rate from 25% to 28% and 20% to see the sensitivity of beta values. In 3 cases (rate = 20%, 25%, and 28%), with current debt financing, asset beta mean is estimated at 0.35, 0.34 and 0.32. Also in 3 scenarios, we find out var of asset beta estimated at 0,031, 0,032 and 0,032 (almost the same). Tax rate changes almost have no effect on asset beta var under financial leverage.

Empirical research findings and discussion

In the below section, data used are from total 9 listed wholesale and retail industry companies on VN stock exchange (HOSE and HNX mainly). In the scenario 1, current tax rate is kept as 25% then changed from 20% to 30%. Then, three (3) FL scenarios are changed up to 30% and down to 20%, compared to the current FL degree. In short, the below table 1 shows three scenarios used for analysing the risk level of these listed firms (Table 1).Table 1: Analyzing market risk under three scenarios.

Table 2: Market risk of listed companies on VN wholesale and retail industry market under a 3 factors model (case 1) (source: VN stock exchange 2012).

 

Tax rate as current (25%)

Tax rate up to 30%

Tax rate down  to 20%

Leverage as current

Competitor size as current, double and slightly smaller

Competitor size as current, double and slightly smaller

Competitor size as current, double and slightly smaller

Leverage up 30%

Leverage down 20%

 

Scenario 1

Scenario 2

Scenario 3

Order No.

Company stock code

Equity beta

Asset beta

Competitor as current

Double

Slightly smaller

Competitor as current

Double

Slightly smaller

1

HHS (current FL)

0,728

0,295

0,383

0,479

0,194

0,252

 

HHS (Fl up)

0,632

0,256

0,309

0,351

0,142

0,171

 

HHS (Fl down)

0,789

0,319

0,434

0,573

0,232

0,315

2

IMT

0,399

1,080

0,399

0,386

1,044

0,386

 

IMT (FL up)

0,396

1,072

0,396

0,379

1,025

0,379

 

IMT (FL down)

0,401

1,086

0,401

0,390

1,057

0,390

3

TH1

0,409

0,409

0,409

0,160

0,160

0,160

 

TH1 (Fl up)

0,409

0,409

0,409

0,086

0,086

0,086

 

TH1 (Fl down)

0,409

0,409

0,409

0,210

0,210

0,210

4

BSC

0,420

0,238

0,204

0,342

0,193

0,166

 

BSC (Fl up)

0,291

0,140

0,193

0,220

0,106

0,146

 

BSC (FL down)

0,319

0,303

0,211

0,271

0,257

0,180

5

PET

1,273

1,273

1,273

0,351

0,351

0,351

 

PET (FL up)

1,273

1,273

1,273

0,074

0,074

0,074

 

PET (FL down)

1,273

1,273

1,273

0,535

0,535

0,535

6

BTT

0,829

0,335

0,532

0,640

0,259

0,411

 

BTT (FL up)

0,769

0,311

0,494

0,541

0,219

0,348

 

BTT (FL down)

0,867

0,351

0,557

0,709

0,287

0,455

7

CMV

0,391

0,158

0,391

0,126

0,051

0,126

 

CMV (FL up)

0,153

0,062

0,153

0,018

0,007

0,018

 

CMV (FL down)

0,535

0,216

0,535

0,244

0,099

0,244

8

PIT

1,012

1,012

1,012

0,514

0,514

0,514

 

PIT (FL up)

1,012

1,012

1,012

0,364

0,364

0,364

 

PIT (FL down)

1,012

1,012

1,012

0,613

0,613

0,613

9

VT1

0,411

0,279

0,101

0,175

0,118

0,043

 

VT1 (FL up)

0,239

0,174

0,060

0,060

0,044

0,015

 

VT1 (FL down)

0,529

0,343

0,129

0,286

0,185

0,070

Table 3:  Market risks of listed wholesale and retail industry firms under a 3 factors model (case 2) (source: VN stock exchange 2012).

Order No.

Company stock code

Equity beta

Asset beta

Competitor as current

Double

Slightly smaller

Competitor as current

Double

Slightly smaller

1

HHS (current FL)

0,736

0,298

0,390

0,485

0,196

0,257

 

HHS (Fl up)

0,642

0,260

0,316

0,357

0,144

0,176

 

HHS (Fl down)

0,796

0,322

0,441

0,578

0,234

0,320

2

IMT

0,399

1,081

0,399

0,386

1,045

0,386

 

IMT (FL up)

0,396

1,073

0,396

0,379

1,026

0,379

 

IMT (FL down)

0,401

1,087

0,401

0,391

1,058

0,391

3

TH1

0,409

0,409

0,409

0,160

0,160

0,160

 

TH1 (Fl up)

0,409

0,409

0,409

0,086

0,086

0,086

 

TH1 (Fl down)

0,409

0,409

0,409

0,210

0,210

0,210

4

BSC

0,310

0,244

0,205

0,252

0,198

0,167

 

BSC (Fl up)

0,293

0,146

0,194

0,222

0,110

0,147

 

BSC (FL down)

0,321

0,309

0,212

0,273

0,263

0,181

5

PET

1,273

1,273

1,273

0,351

0,351

0,351

 

PET (FL up)

1,273

1,273

1,273

0,074

0,074

0,074

 

PET (FL down)

1,273

1,273

1,273

0,535

0,535

0,535

6

BTT

0,835

0,338

0,536

0,644

0,261

0,414

 

BTT (FL up)

0,777

0,314

0,499

0,547

0,221

0,351

 

BTT (FL down)

0,872

0,353

0,560

0,713

0,288

0,458

7

CMV

0,401

0,162

0,401

0,129

0,052

0,129

 

CMV (FL up)

0,158

0,064

0,158

0,019

0,008

0,019

 

CMV (FL down)

0,545

0,221

0,545

0,249

0,101

0,249

8

PIT

1,012

1,012

1,012

0,514

0,514

0,514

 

PIT (FL up)

1,012

1,012

1,012

0,364

0,364

0,364

 

PIT (FL down)

1,012

1,012

1,012

0,613

0,613

0,613

9

VT1

0,423

0,284

0,104

0,180

0,121

0,044

 

VT1 (FL up)

0,248

0,179

0,062

0,063

0,045

0,016

 

VT1 (FL down)

0,540

0,348

0,132

0,292

0,188

0,071


      Market risk (beta) under the impact of tax rate, includes: 1) equity beta; and 2) asset beta.

      Scenario 1: current tax rate 25% and leverage kept as current, 20% down and 30% up, under the condition that competitor size kept as current.

      In this case, all beta values of 9 listed firms on VN wholesale and retail industry market as following (Table 2).

      Scenario 2: Tax rate increases up to 28% and leverage kept as current, 20% down and 30% up, under the condition that competitor size kept as current.

      All beta values of total 9 listed firms on VN wholesale and retail industry market as below (Table 3).

      Scenario 3: Tax rate decreases down to 20% and leverage kept as current, 20% down and 30% up, under the condition that competitor size kept as current.

      All beta values of total 9 listed firms on VN wholesale and retail industry market as below (Table 4).

      All three above tables and data show that there are just tiny changes in the values of equity beta and there are bigger fluctuations in the values of asset beta in the three (3) cases.

      Table 4: Market risks of listed wholesale and retail industry firms under a 3 factors model (case 3) (source: VN stock exchange 2012).

      Order No.

      Company stock code

      Equity beta

      Asset beta

      Competitor as current

      Double

      Slightly smaller

      Competitor as current

      Double

      Slightly smaller

      1

      HHS (current FL)

      0,715

      0,289

      0,371

      0,470

      0,190

      0,244

       

      HHS (Fl up)

      0,617

      0,250

      0,296

      0,343

      0,139

      0,165

       

      HHS (Fl down)

      0,778

      0,315

      0,424

      0,565

      0,229

      0,308

      2

      IMT

      0,398

      1,078

      0,398

      0,385

      1,042

      0,385

       

      IMT (FL up)

      0,395

      1,069

      0,395

      0,378

      1,023

      0,378

       

      IMT (FL down)

      0,401

      1,084

      0,401

      0,390

      1,055

      0,390

      3

      TH1

      0,409

      0,409

      0,409

      0,160

      0,160

      0,160

       

      TH1 (Fl up)

      0,409

      0,409

      0,409

      0,086

      0,086

      0,086

       

      TH1 (Fl down)

      0,409

      0,409

      0,409

      0,210

      0,210

      0,210

      4

      BSC

      0,305

      0,228

      0,202

      0,248

      0,185

      0,164

       

      BSC (Fl up)

      0,287

      0,133

      0,190

      0,217

      0,100

      0,144

       

      BSC (FL down)

      0,317

      0,293

      0,210

      0,269

      0,249

      0,178

      5

      PET

      1,273

      1,273

      1,273

      0,351

      0,351

      0,351

       

      PET (FL up)

      1,273

      1,273

      1,273

      0,074

      0,074

      0,074

       

      PET (FL down)

      1,273

      1,273

      1,273

      0,535

      0,535

      0,535

      6

      BTT

      0,819

      0,331

      0,526

      0,632

      0,256

      0,406

       

      BTT (FL up)

      0,757

      0,306

      0,486

      0,533

      0,216

      0,342

       

      BTT (FL down)

      0,859

      0,347

      0,551

      0,702

      0,284

      0,451

      7

      CMV

      0,376

      0,152

      0,376

      0,121

      0,049

      0,121

       

      CMV (FL up)

      0,144

      0,058

      0,144

      0,017

      0,007

      0,017

       

      CMV (FL down)

      0,519

      0,210

      0,519

      0,237

      0,096

      0,237

      8

      PIT

      1,012

      1,012

      1,012

      0,514

      0,514

      0,514

       

      PIT (FL up)

      1,012

      1,012

      1,012

      0,364

      0,364

      0,364

       

      PIT (FL down)

      1,012

      1,012

      1,012

      0,613

      0,613

      0,613

      9

      VT1

      0,393

      0,270

      0,097

      0,167

      0,115

      0,041

       

      VT1 (FL up)

      0,225

      0,167

      0,056

      0,057

      0,042

      0,014

       

      VT1 (FL down)

      0,511

      0,334

      0,125

      0,276

      0,180

      0,067

          

      Comparing statistical results in 3 scenarios of changing leverage

      The above calculated figures generate some following results:

      First of all, Equity beta mean values in all 3 scenarios are acceptable (< 0.7) and asset beta mean values are also small (< 0.5). If competitor size kept as current (approximate size) and Fl down 20%, asset beta max value increases slightly to 0,709 to 0,713 when tax rate is up to 28%. Finally, when leverage decreases down to 20% and competitor size kept as current, asset beta max value decreases to 0,702 in case tax rate down to 20% (Tables 5-7).

      The below Figure 1 and 2 show us: in scenario 1 (current tax rate), when leverage degree decreases down to 20%, with current approximate size competitors, average equity beta value increases maximum (0.68) (Figures 1 and 2). However, equity beta var reaches 0.21 (maximum), in case doubling size competitors and leverage up 30%. Then, in scenario 2 (tax rate up to 28%), when leverage degree decreases down to 20%, with current approximate size competitors, average equity beta value increases maximum (0.69). Similarly, equity beta var reaches 0.21 (maximum), in case doubling size competitors and leverage up 30%. Finally, in scenario 3 (tax rate down 20%), equity beta mean reaches 0.47 (minimum) if leverage up 30% and smaller size competitors. The below Figure 3 and 4 show us: in scenario 1 (current tax rate), asset beta mean reaches 0.43 (maximum) if leverage down 20% and current approximate size competitors (Figures 3 and 4). And asset beta var reaches 0,092 (maximum) in case current leverage and doubling size competitors. Then, in scenario 2 (tax rate up to 28%), asset beta mean also reaches 0.43 (maximum) if leverage down 20% and current approximate size competitors. And asset beta var reaches 0,100 (maximum) in case leverage up 30% and doubling size competitors. Finally, in scenario 3 (tax rate down 20%), asset beta mean reaches 0.18 (minimum) in case FL up 30% and slightly smaller size competitors, whereas asset beta var reaches 0.022 (minimum) in the same conditions.

       

       

      Equity beta

      Asset beta

      Difference

      1. FL as current

      Statistic results

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      MAX

      1,273

      1,273

      1,273

      0,640

      1,044

      0,514

      0,633

      0,229

      0,760

      MIN

      0,391

      0,158

      0,101

      0,126

      0,051

      0,043

      0,266

      0,107

      0,058

      MEAN

      0,653

      0,564

      0,523

      0,352

      0,320

      0,268

      0,300

      0,244

      0,255

      VAR

      0,1069

      0,1839

      0,1434

      0,0307

      0,0921

      0,0243

      0,076

      0,092

      0,119

      2. FL up 30%

      Statistic results

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      MAX

      1,273

      1,273

      1,273

      0,541

      1,025

      0,379

      0,732

      0,248

      0,895

      MIN

      0,153

      0,062

      0,060

      0,018

      0,007

      0,015

      0,135

      0,054

      0,045

      MEAN

      0,575

      0,523

      0,478

      0,233

      0,230

      0,178

      0,342

      0,294

      0,300

      VAR

      0,1439

      0,2141

      0,1650

      0,0338

      0,1003

      0,0220

      0,110

      0,114

      0,143

      3. FL down 20%

      Statistic results

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      MAX

      1,273

      1,273

      1,273

      0,709

      1,057

      0,613

      0,564

      0,216

      0,660

      MIN

      0,319

      0,216

      0,129

      0,210

      0,099

      0,070

      0,109

      0,118

      0,059

      MEAN

      0,682

      0,590

      0,551

      0,426

      0,386

      0,335

      0,256

      0,204

      0,216

      VAR

      0,1043

      0,1672

      0,1355

      0,0342

      0,0910

      0,0317

      0,070

      0,076

      0,104

      Note: Sample size : 9 firms

      Figure 1: Comparing statistical results of equity beta var and mean in three scenarios of changing FL and tax rate and competitor size (source: VN stock exchange 2012).

      Table 5: Statistical results (FL in case 1) (source: VN stock exchange 2012).

       

       

      Equity beta

      Asset beta

      Difference

      1. FL as current

      Statistic results

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      MAX

      1,273

      1,273

      1,273

      0,640

      1,044

      0,514

      0,633

      0,229

      0,760

      MIN

      0,391

      0,158

      0,101

      0,126

      0,051

      0,043

      0,266

      0,107

      0,058

      MEAN

      0,653

      0,564

      0,523

      0,352

      0,320

      0,268

      0,300

      0,244

      0,255

      VAR

      0,1069

      0,1839

      0,1434

      0,0307

      0,0921

      0,0243

      0,076

      0,092

      0,119

      2. FL up 30%

      Statistic results

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      MAX

      1,273

      1,273

      1,273

      0,541

      1,025

      0,379

      0,732

      0,248

      0,895

      MIN

      0,153

      0,062

      0,060

      0,018

      0,007

      0,015

      0,135

      0,054

      0,045

      MEAN

      0,575

      0,523

      0,478

      0,233

      0,230

      0,178

      0,342

      0,294

      0,300

      VAR

      0,1439

      0,2141

      0,1650

      0,0338

      0,1003

      0,0220

      0,110

      0,114

      0,143

      3. FL down 20%

      Statistic results

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      Competitor size as current

      Double

      Slightly smaller

      MAX

      1,273

      1,273

      1,273

      0,709

      1,057

      0,613

      0,564

      0,216

      0,660

      MIN

      0,319

      0,216

      0,129

      0,210

      0,099

      0,070

      0,109

      0,118

      0,059

      MEAN

      0,682

      0,590

      0,551

      0,426

      0,386

      0,335

      0,256

      0,204

      0,216

      VAR

      0,1043

      0,1672

      0,1355

      0,0342

      0,0910

      0,0317

      0,070

      0,076

      0,104

      Note: Sample size : 9 firms


      Conclusion and Policy Suggestion

      In summary, the government has to consider the impacts on the movement of market risk in the markets when it changes the macro policies and the legal system and regulation for developing the wholesale and retail market. The Ministry of Finance continues to increase the effectiveness of fiscal policies and tax policies which are needed to combine with other macro policies at the same time. The State Bank of Viet Nam continues to increase the effectiveness of capital providing channels for wholesale and retail firms as we might note that in this study when leverage is going to increase up to 30%, the risk level decreases to 0,18 if competitor size is slightly smaller (for all 3 cases of various tax rates). Furthermore, the entire efforts among many different government bodies need to be coordinated. Finally, this paper suggests implications for further research and policy suggestion for the Viet Nam government and relevant organizations, economists and investors from current market conditions.


      Acknowledgements

      I would like to take this opportunity to express my warm thanks to Board of Editors and Colleagues at Citibank –HCMC, SCB and BIDV-HCMC, Dr. Chen and Dr. Yu Hai-Chin at Chung Yuan Christian University for class lectures, also Dr Chet Borucki, Dr Jay and my ex-Corporate Governance sensei, Dr. Shingo Takahashi at International University of Japan. My sincere thanks are for the editorial office, for their work during my research. Also, my warm thanks are for Dr. Ngo Huong, Dr. Ho Dieu, Dr. Ly H. Anh, Dr Nguyen V. Phuc and my lecturers at Banking University – HCMC, Viet Nam for their help. Lastly, thank you very much for my family, colleagues, and brother in assisting convenient conditions for my research paper.


      References

      1. Allen F, Gale D. Stock price manipulation. Review Financial Studies. 1992; 5: 503-529.
      2. Smith BC. Tax increment finance investment impacts on localized real estate: Evidence from Chicago’s multifamily markets. SSRN Working Paper. 2004.
      3. Anderson JE. Tax policy and house price dynamics. SSRN Working Paper. 2009.
      4. Bijlsma MJ, Boone J, Zwart G. Competition for traders and risk. CEPR Discussion Paper. 2012.
      5. Mamun, Abdullah AL. Performance evaluation of prime bank limited in terms of capital adequacy. Global J Management Business Res. 2013.
      6. Devraj B, Alexander S. CAPM and time-varying beta: the cross-section of expected returns. SSRN Working paper series. 2007.
      7. Spinassou K. Basel III capital requirements and regulatory power: the impact on bank risk-taking and credit supply. SSRN Working Paper. 2013.
      8. Gunaratha V. The degree of financial leverage as a determinant of financial risk: an empirical study of Colombo stock exchange in Sri Lanka. Second Int Conference Management Economics Paper. 2013.
      9. Raith M. Competition, risk and managerial incentives. SSRN Working Paper. 2001.
      10. Arkadev C, Joseph AJ, Robert AJ. Market manipulation and corporate finance: A new Perspectives. South Western Finance Association. Texas, USA. 2001.
      11. DeGennaro, Ramon P, Sangphill K. The CAPM and beta in an imperfect market. SSRN Working paper series. 2003.
      12. Galagedera DUA. An alternative perspective on the relationship between downside beta and CAPM beta. Emerging Markets Review. 2007.
      13. Dinh TN. Whether the risk level of Vietnam real estate firms under the different changing tax rates increase or decrease so much. Int J Res Business Technol. 2013.
      14. Ijaz KS, Atif M. Unchecked intermediaries: Price manipulation in an emerging stock market. J Financial Eco. 2005; 78: 203-241.
      15. Favere MM. The impact of tax services on auditor’s fraud risk assessments. Advances Accounting.
      16. Ang A, Chen J. CAPM over the long run: 1926-2001. J Empirical Finance. 2007.
      17. ADB and Vietnam fact sheet. 2010.