RISK ASSESSMENT OF VIETNAM TELECOMMUNICATION INDUSTRY UNDER FINANCIAL LEVERAGE, AND ROLE OF NEW ICT

International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN (P): 2249–6890; ISSN (E): 2249–8001 Vol. 10, Issue 3, Jun 2020, 1715-1722 © TJPRC Pvt. Ltd.

RISK ASSESSMENT OF VIETNAM TELECOMMUNICATION INDUSTRY UNDER FINANCIAL LEVERAGE, AND ROLE OF NEW ICT AND CYBERSECURITY AT THE SECTOR CHALLENGES DINH TRAN NGOC HUY1, NGUYEN THU THUY2, NGUYEN THUY DUNG3, SYLWIA GWOŹDZIEWICZ4 & NGUYEN DUY MAU5 1 2

Research Scholar, Banking University HCM, International University of Japan, Japan

Research Scholar, Faculty of Economics, TNU-University of Economics and Business Administration (TUEBA), Thai Nguyen, Vietnam 3

Master, Thai Nguyen University of Information technology and Communications, Vietnam 4

Research Scholar, Jacob of Paradies University in Gorzow Wielkopolski, Poland 5

Research Scholar, DaLat University, Vietnam

ABSTRACT In recent years, many milestones have been achieved in the telecommunication industry in Vietnam. In Viet Nam, an

commodity prices and change in macro-factors like inflation and interest rates. This paper analyzes the effects of external financing on market risk for the listed firms in the Vietnam telecommunication industry, esp. after the financial crisis 2007-2009 as applicable.

First of all, we found that the beta values for 18 listed telecommunication companies in general are appropriate by using quantitative and analytical methods for the estimation of asset and equity beta of 6 coted Vietnamese software companies with a better traditional model.

Original Article

established telecommunication industry has been struggling to rebound from the 2008 crisis under the uncertainty of

Next, we have noted that under three different scenarios of adjustments in leverage (25%, 25% and 28%), risk level decreases (0,320) when leverage increases to 30% and it increases (0,512) if leverage decreases down to 20%.

This paper, hopefully, presents some findings that may provide further proof for businesses and the government to determine its governance policies. When adjustments to tax rates and strategic strategy or leverage could affect risk levels, corporate management and policy makers should consider making appropriate decisions using the findings.An important aspect will be the reference of telecommunications market development analyzes to ICT technological challenges. That is why the role of new ICT and cybersecurity technologies was also analyzed in the development of the telecommunications sector.

KEYWORDS: Telecommunication Industry, Asset Beta, Beta CAPM, Market Risk, Risk Assessment, External Financing, ICT, Cyber Security, 5G Technology JEL CLASSIFICATION: G01, G39, O3, K24

Received: May 22, 2020; Accepted: Jun 12, 2020; Published: Jun 30, 2020; Paper Id.: IJMPERDJUN2020156

INTRODUCTION In the upcoming industrial revolution (4.0 and further), Information Technology and Electronics Telecommunications play an important role. Elements of the digital world in the 4th industrial revolution will be:

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Artificial Intelligence (AI): A field of computer science related to the automation of intelligent behaviors. Big Data and Data Science: includes complex and large data sets that cannot be handled by communication applications. Internet of Things (IoT): The Internet is used as a global network connecting technological equipment, becoming a tool to create advanced services and applications.

Vietnam telecommunication industry in recent years has been growing with increasing revenues growth. Risk vs.

Profit will be two sides of a coin in any industry, so for listed firms in this industry, we will measure risk, estimated by using equity and asset beta which measures the impact of debt financing on the market risk.

Hence, this paper aims to estimate these risk measures for the telecommunication industry and find out the answers for the question how much risk for this industry from investors’ viewpoint.

RESEARCH ISSUES Our main purpose is to identify risk level via Beta CAPM in telecom. Indsutry, to see whether it goes up or down in cases of FL. We also test: Hypothesis 1: FL scenarios definitely affects business risk Hypothesis 2: during the crisis time, dispersion of risk or beta might be large.

LITERATURE REVIEW A model by Fama and French (2004) stated that significant values are value and size, in 3 factor model, so stock return depends on market beta and market cap. Beta.

Then, Tolga et al. (2015) found out in systematic risk estimation, there are measurement errors in periods 19691989.

Also, Hang Bai et al. (2018) mentioned CAPM in a single variable model, has failed to explain the value premium w/o disasters. Then the relation of beta -return “flat”, because of error in beta measure. Next, Shetty and Janet (2019) mentioned that minimizing the systematic risk is always difficult than unsystematic risk Last but not least, Denis et al (2019) stated that leverage impact on correlation between beta and volatility. Result revealed that the bias reduced overall in case stressed financial markets.

Finally, The cost of using capital Ke is calculated according to the following formula: Rf: Risk free rate The risk-free rate is the interest rate at which the risk ratio of an asset is close to zero.

Normally, the risk-free rate will be equal to the interest rate of 10-year government bonds.

Beta is a measure of the volatility of a stock compared to the general market.

Risk premium = Rm - Rf Risk premium is the bonus when you invest in stocks (high risk), compared to holding other assets (low risk).

Rm: Required market return

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Background Information. Implementation and Development of the Internet of Things (IOT) First, financial flexibility and rising capital markets create improved business opportunities for businesses. Organizations should change the equity capital structure to change the fixed cost to variable cost structure. Although borrowing will help an organization improve its competitiveness, the company tends to maximize its debt because the vulnerability is not so anxious due to so much debt financing. Leverage will aid in its success and development over the company's lifetime.

The specificity of the telecommunications sector and its cybersecurity is its close and direct relationship with ICT, among which should be mentioned: the development of 5G networks, IoT, blockchain technology and development of end devices. The most important aspects of new ICT technologies and cybersecurity in the development of the telecommunications sector will be presented below.

The Ericsson company in the "Ericsson Mobility Report" (2018) [14] estimates that by 2024 the number of IoT devices in the world will grow at a rate of 17% per year (cumulative annual growth rate) reaching 22.3 billion devices from the initial 8.6 billion in 2018. The telecommunications industry plays a key role in the implementation and development of the Internet of Things (IoT). According to the 'IoT in the Polish Economy' report (2019) [12], the Polish Ministry of Digitization informs that based on services provided by the telecommunications industry, it is possible to quickly implement the IoT idea on a large scale. Similarly, this was the case earlier in the case of widespread access to the Internet.

From the beginning of telecommunications, technical solutions were mainly focused on meeting the needs of man as an end-user of services. Currently, the telecommunications market is approaching the mass implementation of autonomous systems based on devices that will communicate with each other without human intervention, or with its negligible role.

These devices connected in a network create the Internet of Things, introducing a new type of connections/traffic in telecommunications networks. The traffic performed has different characteristics and different requirements compared to the traffic generated by the user. Currently, IoT systems use in most cases technological solutions that were originally designed for humans. Device developers use standards such as GPRS, UMTS, WiFi, LTE, Ethernet and others to provide wireless or wired connectivity to their devices. However, the telecommunications industry has prepared new communication standards to meet the need to implement mass IoT. Wireless telecommunications standards for IoT play the most important role as "last mile" technologies. Connecting IoT devices to the network is easier and available almost everywhere. International organizations have prepared wireless standards for both licensed and unlicensed bands. These are standards for LPWAN (Low Power Wide Area Network) networks, i.e. long-range wireless low energy networks.

METHODOLOGY We use quantitative method to make risk assessment from live data on Vietnam stock exchange for listed telecom. industry firms in Vietnam with tax rate 25% at that time. After calculating and comparing risk indexes such as beta CAPM we propose suitable policies and include risk management plans.

GENERAL DATA ANALYSIS The study review contains eighteen listed entities on the telecommunication market with live data. Next, we measure these companies ' stock beta valuation and use their capital flexibility to measure their asset beta values. Secondly, to see the strength of the beta values we adjust the leverage from 20% down to 30% up. The average asset beta mean is calculated to

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be 0,431, 0,320 and 0,512 for 3 situations, I.e negative correlation with leverage. We also note that the negative correlation also happen for mean values of beta.

EMPIRICAL RESEARCH FINDINGS AND DISCUSSIONS Within 2 cases of leverage, up and down for total 18 listed telecom firms in Vietnam: 7.1. Case 1: 30% up leverage We estimate values of beta as below:

Figure 1: Measuring Market Risk Via Beta CAPM (Case A).

7.2. Case 2: 20% down leverage We estimate values of beta as below:

Figure 2: Measuring Market Risk Via Beta CAPM (Case B).

Looking at above charts, we recognize beta has fluctuation or dispersion to some extent.

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Comparing Statistical Results in 3 Scenarios of Changing Leverage Table 1: Statistical Results (FL in Case 1) FL up FL down current Equity beta max 1.18 1.18 1.18 Asset beta max 0.733 0.849 0.802 Equity beta mean 0.62 0.73 0.687 Asset beta mean 0.32 0.512 0.431 What we can analyze from the above data and below chart 3 is that: Mean asset beta values and FL has a negative correlation: when leverage up to 30%, beta value declines to 0.62, and up to 0.73 if FL to20% Mean equity beta value and FL also has a negative correlation: up to 0.512 in case leverage declines to 20%, and down to 0.32 in leverage up to 30%.

In addition, the following chart shows equity beta var and FL has a positive correlation (it increases when FL up to 30&) and vice versa.

Asset beta var

0,031 0,038 0,035

Equity beta var

0,053 0,099 0,070

FL 20% down FL 30% up 0,512

Asset beta mean

0,730 0,620 0,687

Equity beta mean 0,000

FL keep as in F.S report

0,320 0,431

0,200

0,400

0,600

0,800

Figure 3: Measuring Beta Var in the above Telecom. Industry (2007-2011).

Development of Telecommunications Sector Equipment 5G Technology Bearing in mind the current standards of development of the telecommunications sector, one of the key issues is its relation to cyber security.

Therefore, the telecommunications sector includes, among other activities in the field of wired, wireless, satellite telecommunications and all activities related to the provision of cybersecurity. A characteristic phenomenon for the telecommunications and cyber security sector is the high susceptibility to the factors of the impact of new ICT technologies, which have a significant impact on the service market in both the group of suppliers and recipients. Its www.tjprc.org

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functioning is determined by the overall economic situation and is strongly linked to the investment potential of enterprises.

DISCUSSIONS Risk ANALYSIS Based on above charts and analysis, when FL increases 30% risk dispersion might increases, so we need risk management plan to control the risk fluctuation in this case.

CONCLUSIONS AND POLICY SUGGESTIONS Looking at exhibit 3, we could see GDP of Viet Nam during the period 2007-2011 in the range of 5%-6.5% (< 7%). And inflation goes down in 2009 then goes up in later years. And comparing to the results of consumer good industry in exhibit 4, we find out the risk dispersion of telecom. industry is higher (shown by asset beta var).

We might note that var of asset beta may increases (looking at the above charts and analysis) so we need risk management solutions then. Besides, companies might consider some innovative solutions going together with risk strategies, and one example shown in the below 12 section.

Implementing Blockchain Technology in the Telecommunications Sector In the case of blockchain technology, there is a much lower risk of server incident, modification or data theft. This does not mean that the technology is completely resistant to any incidents or manipulation attempts. It should be expected that the majority of attacks on this technology will be directed against applications that support blockchain rather than against the platforms themselves. A characteristic cross-border phenomenon in the application of new ICT technologies in the telecommunications sector is the increasing complexity of legal regulations, and above all their contradiction. Legal regulations and jurisdiction may be a barrier to new innovative IoT services or blockchain technology. Legal regulations are focused on the provision of telecommunications services dedicated to interpersonal communication. For this reason, several legal provisions specifically regulate relationships with people that are irrelevant to IoT device communications.

Therefore, it is necessary to adopt legal provisions to the specific conditions of IoT communication. In the case of blockchain technology, often occurring problems are so-called smart contracts.

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ADB and Viet Nam Fact Sheet, 2010

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Anderson. J.E., (2009), Tax Policy and House Price Dynamics, SSRN Working Paper

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Denis, G., Sebastien, V., & Sofiane, A. (2019). The Reactive Beta Model, Journal of Financial Research, 10.1111/jfir.12182, 42, 4, (867-867), (2019).

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Eugene FF, French KR. (2004). The Capital Asset Pricing Model: Theory and Evidence. Journal of Economic Perspectives.

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Flifel, Kaouther., (2012), Financial Markets between Efficiency and Persistence : Empirical Evidence on Daily Data, Asian Journal of Finance and Accounting

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Hang, B., Hou, K., Kung, H., Erica, X.N., & Lu, Z. (2018). The CAPM strikes back? An equilibrium model with disasters, Journal of Financial Economics, 131: 269-298.

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Huy, Dinh T.N., (2013), Estimating Beta of Viet Nam Listed Public Utilities, Natural Gas and Oil Company Groups During and After The Financial Crisis 2007-2011, Economic and Business Review, Vol. 15, No. 1, pp. 57-71

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Huy, Dinh T.N., (2013), Beta of Viet Nam Listed Computer and Electrical Company Groups During and After The Financial Crisis 2007-2011, Asian Journal of Finance & Accounting, Vol. 5, No. 1, pp. 127-139

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Shetty,S., & Janet, J.D.S. (2019). An Empirical Examination of the CAPM on BSE SENSEX Stocks, International Journal of Recent Technology and Engineering (IJRTE),8 (2S10).

10. Tolga C., Nicolas A. P., Jonathan J. R., & Michael S. (2015). Equity Investing with Targeted Constant Volatility Exposure, SSRN Electronic Journal, 10.2139/ssrn.2614828..

11. TYAGI, MANOJ, SHIPRA RAHUL, and ANOOP KUMAR RAI. "BAYESIAN BELIEF NETWORKS (BBN) BASED RISK ASSESSMENT FOR DEPLOYED C4I SYSTEM." International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC) 7.2 (2017):23-32 12. SELVAN, R. TAMIL, NA SIDDQUI, and KANCHAN BAHUKHANDI. "Study of hazard identification techniques adopted by oil and gas industries for risk assessment." BEST: International Journal of Management, Information Technology and Engineering (BEST: IJMITE) 3.10 (2015): 117-126.

13. MALISUWAN, SETTAPONG, and WASSANA KAEWPHANUEKRUNGSI. "DESIGN OF SPECTRUM LICENSING FOR MOBILE TELECOMMUNICATIONS SERVICE IN THAILAND." International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC) 6.1 (2016):7-14

EXHIBIT Exhibit 1: Interest Rates in Banking Industry During Crisis Year Borrowing Interest rates Deposit Rates Note 2011 18%-22% 13%-14% 2010 19%-20% 13%-14% Approximately 2009 9%-12% 9%-10% (2007: required reserves ratio at SBV is changed from 5% to 10%) 2008 19%-21% 15%-16,5% (2009: special supporting interest rate is 4%) 2007 12%-15% 9%-11% (source: Viet Nam commercial banks)

Exhibit 2: Increase/Decrease Risk Level of Listed Telecommunication Industry Firms under Changing Scenarios Of Leverage : In 2011 F.S Reports, 30% Up, 20% Down in the Period 2007-2009 Fl Keep as in F.S Fl 30% Up Fl 20% Down Report Company Order Stock Increase Increase Increase Increase No. Equity Asset Code /Decrease /Decrease /Decrease /Decrease Beta Beta (Equity Beta) (Asset Beta) (Equity Beta) (Asset Beta) 1 ECI 0,471 0,351 -0,124 -0,119 0,086 0,093 2 INN 0,467 0,250 -0,108 -0,108 0,067 0,086 3 PTP 0,425 0,203 -0,125 -0,107 0,078 0,090 4 DHI 0,894 0,660 0,000 -0,070 0,000 0,047 5 IHK 0,593 0,340 -0,115 -0,127 0,072 0,098 6 HTP 1,035 0,802 0,000 -0,070 0,000 0,046 7 TPH 0,924 0,411 0,000 -0,154 0,000 0,103 8 IN4 0,315 0,189 -0,122 -0,097 0,098 0,092 9 ADC 0,513 0,258 -0,136 -0,125 0,085 0,102

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10 11 12 13 14 15 16 17 18

HST SGD DAE HEV ALT EFI EID DAD SED

0,654 1,180 1,013 0,869 0,772 0,447 0,599 0,868 0,319 Average

0,455 0,630 0,399 0,596 0,617 0,422 0,433 0,588 0,147

-0,071 0,000 0,000 0,000 0,000 -0,108 -0,057 -0,104 -0,123 -0,066

-0,103 -0,165 -0,184 -0,082 -0,047 -0,108 -0,086 -0,145 -0,088 -0,110

0,046 0,000 0,000 0,000 0,000 0,069 0,037 0,067 0,086 0,044

0,074 0,110 0,123 0,055 0,031 0,071 0,062 0,105 0,083 0,082

Exhibit 3: VNI Index and Other Stock Market Index During Crisis 2006-2010

Asset beta var

Equity beta var

0,0719 0,072 0,066 0,1795

0,289 0,214

FL 20% down FL 30% up

Asset beta mean

0,428

0,222

FL keep as in F.S report

0,336 0,737 0,630 0,694

Equity beta mean 0,000

0,200

0,400

0,600

0,800

Exhibit 4: Comparing Statistical Results of Three (3) Scenarios Of Changing FL of 121 Listed Firms in the Consumer Good Industry

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