An empirical study on macroeconomic determinants of exchange rate and stree testing application on vietnam non financial corporate sector

AN EMPIRICAL STUDY ON MACROECONOMIC DETERMINANTS OF EXCHANGE RATE AND STRESS TESTING APPLICATION ON VIETNAM NON – FINANCIAL CORPORATE SECTOR In Partial Fulfillment of the Requirements

AN EMPIRICAL STUDY ON MACROECONOMIC DETERMINANTS OF

EXCHANGE RATE AND STRESS TESTING APPLICATION ON VIETNAM

NON – FINANCIAL CORPORATE SECTOR

In Partial Fulfillment of the Requirements of the Degree of

MASTER OF BUSINESS ADMINISTRATION

AN EMPIRICAL STUDY ON MACROECONOMIC DETERMINANTS OF EXCHANGE RATE AND STRESS TESTING APPLICATION ON VIETNAM

NON – FINANCIAL CORPORATE SECTOR

In Partial Fulfillment of the Requirements of the Degree of

MASTER OF BUSINESS ADMINISTRATION

In Finance

by Ms: Le Tran Nguyen Nhung ID: MBA06022 International University - Vietnam National University HCMC

Acknowledge

To complete this thesis, I have been benefited from the following people

Firstly, I would like to express my deepest gratefulness to my advisor, Dr Ho Diep, for choosing me, giving many dedicated and enthusiastic instructions and offering me good opportunity to develop myself during the six – month period of my research I also send my sincere gratitude to the professors and lecturers who teach me valuable knowledge during the MBA course

Secondly, I would like to present my special thanks to Mr Vinh, Mr Linh and

Ms Ai from Vietcombank Fund Management (VCBF) for spending their time to participate in many discussions with Dr Diep and me and helps me gain a great deal of useful information and innovative ideas

Finally, to my family and best friends, thank you for your endless love and constant support which inspires me to overcome any difficulties and discouragement to achieve my MBA degree

Le Tran Nguyen Nhung

Plagiaris m State ments

I would like to declare that, apart from the acknowledged references, this thesis either does not use language, ideas, or other original material from anyone; or has not been previously submitted to any other educational and research programs or institutions I fully understand that any writings in this thesis contradicted to the above statement will automatically lead to the rejection from the MBA program at the International University – Vietnam National University Hochiminh City

Copyright Statement

This copy of the thesis has been supplied on condition that anyone who consults

it is understood to recognize that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without the author’s prior consent

© Le Tran Nguyen Nhung/ MBA06022/ 2014

Table of Contents

1 Introduction 1

1.1 Background 1

1.2 Research Problems 2

1.3 Research Objectives 5

1.4 Research Questions 6

1.5 Research Methodology 6

1.6 Research Scope and Limitation 6

1.7 Implications 7

1.8 Research Structure 7

2 Lite rature Review 9

2.1 Exchange Rate 9

2.2 Exchange Rate Regimes 10

2.3 Approaches to Exchange Rate Determination 12

2.4 Determinants of Exchange Rate 16

2.5 Stress Testing Theory 21

2.6 Value at Risk Model 26

2.7 Theoretical Framework 30

3 Overvie w of Exchange Rate in Vietnam 31

3.1 Vietnam Exchange Rate Regimes 31

3.2 The Development of Exchange Rate 34

3.3 Vietnam’s Exchange Rate Policy in Comparison with Other Asian Countries 45

3.4 The Relationship between Exchange Rate and Its Determinants 49

4 Data Collection and Research Methodology 64

4.1 Data Collection 64

4.2 Research Methodology 64

5 Data Analysis 75

5.1 Descriptive Statistics 75

5.2 Regression Model for Exchange Rate’s Macro Determinants 76

5.3 Macro Stress Testing for Exchange Rate Exposure 88

6 Conclusion and Recomme ndation 98

6.1 Conclusions 98

6.2 Recommendations 102

6.3 Suggestions for Future Research 104

References 105

List of Tables

Table 2.1: The strengths and weaknesses of VaR approaches

Table 3.1: Exchange rate regimes in Vietnam from 1989 to 2013

Table 3.2: Changes in the trading band around the interbank rate

Table 3.3: The SBV’ measures for managing exchange rate in 2012

Table 3.4: The exchange rate regime and monetary policy framework

Table 4.1: Expected signs of independent variables

Table 5.1: Data description

Table 5.2: Autocorrelation test

Table 5.3: Heteroscedasticity test

Table 5.4: ARCH test

Table 5.5: Correlation matrix

Table 5.6: Omitted variables test

Table 5.7: Redundant variables test

Table 5.8: Hausman test

Table 5.9: Regression model

Table 5.10: VaR using the variance – covariance approach

Table 5.11: VaR using the historical simulation approach

Table 5.12: VaR using Monte Carlo simulation

Table 5.13: Predicted EXR under ∆ GDP shock using historical simulation

Table 5.14: VaR under ∆ GDP shock

Table 5.15: Predicted EXR under ∆ CUR shock using historical simulation

Table 5.16: VaR under ∆ CUR shock

Table 5.17: Predicted EXR using historical simulation

Table 5.18: VaR under ∆ GDP and ∆ CUR shock together

List of Figures

Figure 2.1: Stress testing and scenario

Figure 2.2: Framework for stress testing of individual portfolios

Figure 2.3: VaR at 95% confidence level

Figure 2.4: Theoretical framework

Figure 3.1: Official VND/USD rate, 1989 – 2013

Figure 3.2: Monthly fluctuation of VND/USD, 2008 – 2013

Figure 3.3: The volatility of the exchange rate in 2012

Figure 3.4: Nominal exchange rate index of several Asian currencies against USD Figure 3.5: The relationship between exchange rate and GDP growth rate

Figure 3.6: The relationship between exchange rate and inflation rate

Figure 3.7: The relationship between exchange rate and interest rate

Figure 3.8: The relationship between exchange rate and current account

Figure 3.9: The relationship between exchange rate and FDI

Figure 3.10: The relationship between exchange rate and foreign exchange reserves Figure 3.11: The relationship between VND/USD and VND/EUR, VND/JPY

Figure 5.1: Normality test

Figure 5.2: Stability test

Abstract

Due to the fact that the exchange rate fluctuation can affect business performance but Vietnamese firms have not paid much attention to gauging or managing their foreign exchange exposure, this research examines the relationship between the exchange rate and its macroeconomic determinants, and then develops a framework to conduct macro stress testing by combining modern techniques such as Monte Carlo simulation and Value-at-Risk (VaR) approaches to predict the level of the exchange rate variation as well as the expected losses that companies could suffer This provides Vietnamese companies with a systematic way to calculate, and to reserve risk capital for their currency exposures

This thesis proceeded by showing that the exchange rate in Vietnam is negatively impacted by the GDP growth rate and current account balance, and positively influenced

by the exchange rate (t-1) lagged, where t is time Based on the resultant regression model, VaRs of the exchange rate variation and the expected loss are computed by using three different approaches, (i) variance – covariance matrix, (ii) historical simulation and (iii) Monte Carlo simulation; in which the Monte Carlo gives the highest and most conservative loss that companies should reserve for Macro stress testing is applied to create adverse scenarios and VaR is re-calculated in the stressed market conditions In this study, we used a hypothetical case of a Vietnamese company with a short position of USD

1 million (the methodology can be easily adapted to any Vietnamese enterprise), under the more conservative Monte Carlo simulation, the minimum capital reserve for the Vietnamese company to cover the abnormal stressed loss for the next quarter and at 99% confidence is about VND 680 million (or approximately USD 31,000)

Keywords: Exchange rate, macroeconomic determinants, stress testing, value-at-risk,

capital adequacy

CHAPTER 1 INTRODUCTION

This chapter provides an overview of the study by starting with the background and the motivation to conduct this kind of research in Vietnam After that, the research objectives, questions, methodology, scope and limitation are specified together with its significance Finally, the general framework of the study is proposed at the end of this chapter

1.1 Background

Exchange rate is a key element of a country and is managed under each country’s particular context at a specific period Exchange rate policy is always considered as one of the crucial monetary policies, and has unpredictable effect on other different macroeconomic goals For example, in an open economy, real exchange rate affects relative prices between domestic goods and importing products The changes in prices will lead to the changes in product demand, and then affect the country’s inflation Foreign exchange is also one of the most important indicators of a country’s state of economy along with budget deficit, trade deficit, inflation, and interest rate, etc (Atif et al., 2012) It affects significantly level of investment and trade activities in the economy, which are critical factors for every country Therefore, exchange rate is among the most observed, analyzed, and governmentally controlled economic variables (Van Bergen, 2010)

Since Vietnam is in the process of integrating its economy into the global economic activities, the foreign exchange will also be suffered the impact from many factors in both positive and negative ways For example, increasing interest rate can attract more capital from abroad, which in turn will appreciate the Vietnam Dong

(VND) due to the higher interests paid to VND deposits However, because of higher cost of investment capital and debt, the increase in interest rate quite often depresses the stock market and the growth prospective of the economy, which makes the currency depreciated Therefore, it is very challenging to evaluate and analyze the influence of macroeconomic factors on the exchange rate’s fluctuation that policy makers really care about Due to the complicated and diversity of implementing the exchange rate policy, this becomes a problem which is discussed frequently in Vietnam, especially since the uncertainty of the macro economy in 2008 Managing the exchange rate risk needs to be done suitably in order to control the inflation, stabilize the economy, stimulate export and improve trade balance, which creates good business environment for domestic as well as foreign enterprises

1.2 Research Proble ms

The exchange rate in Vietnam has seen significantly volatility in recent years, especially since the financial crisis in 2008 According to UNDP (2013), from 2007 to the first quarter of 2008, the supply of USD had increased considerably, which enriched the foreign exchange reserves of Vietnam and reduced the exchange rate However, due to high inflation and the global economic recession, the exchange rate went up significantly during the last two quarter of 2008 The official exchange rate VND/USD increased 5.6% at the end of 2009 compared to the same period in 2008 The unofficial market of VND/USD continued to increase to such a degree that the State Bank of Vietnam (SBV) had to devaluate VND of 3.3% in 2010 Moreover, SBV announced the highest amount of VND devaluation of 9.3% after a long time holding its value at the beginning of 2011 At the same time, it imposed the ceiling interest rate for foreign currency deposit, and tightened the operations on the unofficial market and the gold market Due to the tightening operations, from 2012 to

2013, the foreign exchange rate became more stable than previous years, with a fixed fluctuation band of 1% as SBV’s commitment

The exchange rate fluctuations can certainly cause a great impact on firm value, especially firms with foreign operations, foreign revenues or foreign denominated debt(s), because the movement in exchange rate may affect a company’s future cash flows, revenues, risk management and investment projects Many studies have examined the relationship between exchange rate volatility and firm value in different markets in the world For example, Choi and Prasad (1995) find that the stock returns

of US firms are significantly influenced by exchange rate movements It also exists a relationship between exchange rate and stock prices in India, Korea, and Pakistan in either the short-run or the long-run (Abdalla and Murinde, 1997)

In Vietnam, there is very little research, which can fully describe the foreign exchange exposure of Vietnamese companies For instance, Huynh and Nguyen (2013) collected monthly data from 2007 to 2012 to study the relationship between exchange rate, interest rate and stock prices Although there were little statistically significant in correlation, the result still indicates that stock prices are negatively impacted by the exchange rate volatility However, the influence of the exchange rate movement o n the Vietnamese firms is not remarkable During a long period of time, although Vietnam had registered a regime of managed floating exchange rate to the International Montary Fund (IMF), in fact, it pursued pegged exchange rate regime with narrow fluctuation band (Nguyen Thi Thu Hang et al., 2010) Therefore, most of the domestic companies do not pay much attention to the exchange rate risk as well as its hedging methods In case of strong volatility of the exchange rate, the firms with borrowings in USD but their revenue in VND tend to be more dangerous than the other ones due to their responsibility for paying debts

Nowadays, global economic integration puts pressure on all countries to change their exchange rate policies so that their currencies can be flexibly converted in either trade activities or investment Since Vietnam has already joined in the World Trade Organisation (WTO) for several years, it has to accept a more flexible exchange rate regime, which means more unstability Moreover, the larger the amount of portfolio investment capital pouring into the domestic market is, the more severe the implicit risks will be that could cause to financial crisis to the country One more thing that needs to be considered, according to the Circular 03/2012/TT-NHNN and Circular 29/2013/TT-NHNN of the SBV about borrowing in foreign currency, companies that

do not have any sources of foreign currency collection can only borrow in VND; and

if they pay for their imported goods, they must buy USD from banks In addition to high interest rate, the biggest risk that the borrowers have to face is the fluctuation of the exchange rate, especially when USD appreciates To be specific, the firms are forced to pay the principal and the interest in VND plus the difference caused by the higher exchange rate at the payment time compared to the one at the time of signing contract

If the exchange rate is guaranteed to be fluctuated withtin a trading band by the central bank as Vietnam has been implementing, the firms might become subjective and dependent on the government, which are also exposed to devaluation risks, and then do not use any risk hedging instruments As a result, if there are any economic shocks happened in the market, these companies would likely be panic and overreact since they do not know exactly how to deal with those circumstances In other words, there is a chance that Vietnam would change into the more flexible exchange rate regime, probably with wider trading band; or loosening the restrictions on borrowing

in a foreign currency At that time, the domestic companies have to struggle with

many adverse shocks beyond their withstanding while they do not prepare for any risk controlling strategies Thus, they need an effective risk – estimated measures to meet capital requirements in order to cope with the foreign exchange exposure

Additionally, stress testing is an important risk management tool used broadly

in the worldwide financial systems It is also required as part of banks’ internal operating analysis model under Basel II and III requirements However, because of its not – too – complicated techniques, stress testing could be considered to apply to non–financial enterprises so that they can protect themselves against severe economic situations Particlarly, in the age of globalisation in all aspects, although the foreign exchange risk has either direct impact on the firm’s revenue or indirect influence through the suppliers and customers, the awareness of market risk administration of Vietnamese companies is still low (Vu Minh, 2013) Hence, stress testing becomes more crucial than ever before

In general, as high volatility and sudden changes in the exchange rate is one of the barriers for a successful macroeconomic policy as well as the companies’ business performance, modeling volatility is a controversial research topic that needs to be solved This research strives to examine the sensitivity of the exchange rate to macroeconomic factors and develop a macro stress testing framework for the foreign exchange exposure of Vietnam domestic enterprises

1.3 Research Objectives

General objectives

This study is to clarify the relationship between macroeconomic variables and the exchange rate (EXR), and then conduct stress testing using value-at-risk (VaR) approaches for the exchange rate exposure to Vietnamese firms

Specific objectives

 To review theories and studies about EXR and describe its policy in Vietnam

 To identify the key determinants as well as analyze their significance to EXR

 To apply stress testing combined with VaR model to Vietnam corporate sector

 To make conclusions and propose recommendations for Vietnam companies about risk management and capital adequacy

1.4 Research Questions

Based on the above objectives, this study is designed to answer some questions:

- What are the significant macroeconomic determinants of the exchange rate?

- How is the exchange rate expected to fluctuate in the next quarter under VaR approaches and macro stress testing?

- What is the expected loss of a companny under normal conditions as well as adverse scenarios?

1.5 Research Methodology

Both qualitative and quantitative methods are used in this research The qualitative measure with visual results like tables and graphs is utilized to assess preliminarily the connection between the exchange rate and its macro indicators Then, the quantitative one is applied to run regression model, statistical tests and calculate VaR in normal as well as stressed markets

1.6 Research Scope and Limitation

This study focuses on analyzing the fluctuation and macro determinants of the exchange rate of VND/USD from the first quarter of 2005 to the first quarter of 2014

It assumes an foreign exchange position of a hypothetical company in order to employ the stress testing technique and calculate VaR by using three different approaches

In terms of the limitation, firstly, the time period of this study is rather short, just cover 37 quarters that may not demonstrate fully the comprehensive relationship between the exchange rate and its determinants Secondly, the research only uses secondary data which could contain errors when collecting and calculating Thirdly, since it is difficult to collect quarterly data during the study period, some variables like government expenditure and money supply are not included in the regression model as macroeconomic determinants of the exchange rate Finally, for its simplicity, this study makes a assumption about a hypothetical firm’s foreign exchange position used to conduct stress testing Data and results do not represent any specific company, but the tools and methodologies can be applied to any firm for managing exchange rate risk in Vietnam

1.7 Implications

This research is strived to identify the key macroeconomic indicators of the exchange rate of VND/USD The stress testing technique is also applied to the foreign exchange risk of the non- financial companies in Vietnam so that we can estimate the minimum capital reserve which in turn will help them survive over the unexpected economic shocks A clear understanding of the capital adequacy for currency exposure could provide a foundation for the companies to manage their reserves efficiently Hopefully, this study can create a suitable framework with significant variables and assumptions, which can be made reference by future research

1.8 Research Structure

The first chapter of Introduction has described the overview of this study about the motivation, the main purposes, the scope and limitation, etc The content of the remaining chapters are presented as follows

Chapter 2 – Literature review: This chapter discusses some relevant theories

about the exchange rate, different kinds of regimes and approaches to exchange rate determination Furthermore, several empirical studies of the exchange rate’s macro determinants as well as the stress testing theories are revised

Chapter 3 – Overview of exchange rate in Vietnam: There are four main

sections included in the chapter that are the regimes of Vietnam exchange rate over time, the development of the exchange rate po licies and its comparison to several Asian countries, and the qualitative measurement of the relationship between the exchange rate and its determinants

Chapter 4 – Data collection and research methodology: The quantitative

approaches are conducted in this chapter, including the regression model to examine the relationship between the exchange rate and its independent variables, the steps for VaR calculation as well as macro stress testing to estimate the exchange rate variation and the exposure

Chapter 5 – Data analysis: Chapter 5 illustrates the empirical results of the

regression model, the value of VaR computed by using three different approaches including variance – covariance method, historical simulation and Monte Carlo simulation, and the application of the macro stress testing in order to measure the abnormal loss

Chapter 6 – Conclusion and recommendation: This chapter summarizes the

findings of this study which meet the initial objectives and answer the three research questions It also makes some recommendations for Vietnam companies in building risk management tools

CHAPTER 2 LITERATURE REVIEW

First, in this chapter, the relevant theories on exchange rate, categories of exchange rate regimes and approaches to exchange rate determination are discussed Next, several studies to detemine the macroeconomic indicators of exchange rate are reviewed, and the stress testing theory is assessed Finally, the theoretical framework

is built which all other parts of the study must be followed

2.1 Exchange Rate

Exchange rate is an important macroeconomic variable, which is used as a parameter for determining international competitiveness of any currency o f any country (Danmola, 2013) Many scholars explain the concept of exchange rate in different dimensions According to Hache (1983), exchange rates are relative prices of national currencies, and under a floating rate regime they may naturally be determined

by the interplay of supply and demand in foreign exchange markets More simply, Kalra (2005) considers exchange rate as a national currency’s quotatio n in respect to foreign ones Similarly, foreign exchange rate is described as the price of one currency expressed in terms of another currency by Eiteman et al (2010)

It is essential to distinguish between two kinds of exchange rate According to Danmola (2013), nominal exchange rate (NER) is a monetary concept which measures the relative price of the two currencies, while real exchange rate (RER) is regarded as real concept that measures the relative price of two tradable goods (exports and imports) in relation to non – tradable goods (domestic trade only) In other ways, Madura (2006) simply defines RER as the actual exchange rate adjusted for inflation effects in the two countries concerned More clearly, RER is clarified as

the nominal exchange rate adjusted by the ratio of the foreign price level (P*) to domestic price level (P) in the long run as the following formula

If changes in the exchange rate just offset the differential inflation rates, the RER index would stay at 100 If the exchange rate strengthened more than is justified by the differential inflation, its index would rise above 100, and then the currency is

considered “overvalued” from a competitive perspective On the other hand, the index value below 100 would suggest an “undervalued” currency (Eiteman et al., 2010)

Additionally, the tendency for an exchange rate to fluctuate is called foreign exchange volatility, which implies that while a spot exchange rate is observable, the future exchange rate for any currency will not be known ahead of time (O’Brien, 2006) Furthermore, the risk that future exchange rate uncertainty poses to companies, which conduct international business and even those that do not, is decided by both foreign exchange volatility and the companies’ foreign exchange exposure, which is the sensitivity of their financial results to foreign exchange rate changes The level and frequency of the exchange rate volatility is influenced by a country’s exc hange rate regime discussed in the next part

2.2 Exchange Rate Regimes

An exchange rate regime is the way an authority manages its currency in relation to other currencies and the foreign exchange market (Wikipedia) A country may choose its currency regime relied on its national priorities of the economy such

as economic growth, inflation, interest rate level, trade balance, etc Hence, the choice between fixed and flexible exchange rates may change over time as the priorities change The International Monetary Fund (IMF) classifies all exchange rate regimes

into eight specific categories, which span the spectrum of exchange rate regimes from rigidly fixed to independently floating (Eiteman et al., 2010, p.56-57)

1 Exchange arrangements with no separate legal tender: The currency of

another country circulates as the sole legal tender or the member belongs to a monetary or currency union in which the same legal tender is s hared by the members of union

2 Currency board arrangement: A monetary regime based on an implicit

legislative commitment to exchange domestic currency for a specified foreign currency at a fixed exchange rate, combined with restrictions on the issuing authority to ensure fulfillment of its legal obligation

3 Other conventional fixed peg arrangements: The country pegs its currency

(formally or de facto) at a fixed rate to a major currency or a basket of currencies (a composite), where the exchange rate fluctuates within a narrow margin or at most ± 1% around a central rate

4 Pegged exchange rates within horizontal bands: The value of the currency is

maintained within margins of fluctuation around a formal or de facto fixed peg that are wider than most ± 1% around a central rate

5 Crawling pegs: The currency is adjusted periodically in small amounts at a

fixed preannounced rate or in response to changes in selective quantitative indicators

6 Exchange rates within crawling pegs (crawling bands): The currency is

maintained within certain fluctuation margins around a central rate that is adjusted periodically at a fixed preannounced rate or in response to changes in selective quantitative indicators

7 Managed floating with no preannounced path for the exchange rate: The

monetary authority influences the movements of the exchange rate through active intervention in the foreign exchange market without specifying, or precommitting to, a preannounced path for the exchange rate

8 Independent floating: The exchange rate is market – determined, with any

foreign exchange intervention aimed at moderating the rate of change and preventing undue fluctuations in the exchange rate, rather than establishing a level for it

Vietnam has officially accepted the “managed floating” regime, while it is claimed that its exchange rate regime is actually a type of “crawling peg” (Nguyen Tran Phuc et al., 2009; Nguyen Thi Thu Hang et al., 2010) Besides, the exchange rate fluctuation is explained in several theoretical approaches presented in the next section

2.3 Approaches to Exchange Rate Determination

An objective of theoretical approaches of exchange rate determination is to provide a clear understanding of the economic mechanisms governing the actual behavior of exchange rate in the real world and of the relationships between exchange rate and other important economic variables (Mussa, 1984) This study just presents three main approaches in determining the exchange rate including purchasing power parity, balance of payment, and asset market approach

2.3.1 Purchasing Power Parity Approach

Purchasing Power Parity (PPP) is the most widely accepted theory of exchange rate determination This concept has been commonly used to measure the equilibrium values of currencies and is also a relationship which underpins other exchange rate approaches (MacDonald, 2007) There are two kinds of PPP:

(1) Absolute PPP indicates that the equilibrium exchange rate is equal to the ratio of the price levels in the two countries The shortcomings of absolute PPP are that not all products made by a country can be traded internationally, the existence of transportation costs and trade barriers, and the internatio nal capital flow is also influence on the exchange rate

(2) Relative PPP holds that the relative change in prices between two countries leads to the proportional change in exchange rate in a certain period of time To be specific, as Eiteman explains, “if the spot exchange rate between two countries starts

in equilibrium, any change in the differential rate of inflation between them tends to

be offset over the long run by an equal but opposite change in the spot exchange rate” (Eiteman et al., 2010, p.167)

Many scholars have tested PPP and they conclude that (i) PPP performs well in the long run but poorly in the short or medium term, and (ii) PPP holds better for countries with high inflation rate and underdeveloped capital markets For example, if

a country experiences inflation rate relative higher than those of its most trading partners, its exports become less competitive with overseas products, and its imports from abroad become more price – competitive with domestic ones These price changes lead to a deficit on current account that causes to the variation of exchange rate unless it is offset by capital and financial inflows (Eiteman et al., 2010)

2.3.2 Balance of Payments Approach

The PPP approach incorporates implicitly through trade, demand and supply factors in the determination of the exchange rate For example, if price in a foreign country is lower than the domestic one, then domestic demand for foreign goods will increase, and the foreign currency will appreciate The balance of payments (BOP) approach can be seen as encompassing the PPP (Rauli Susmel, undated)

The BOP, which consists of all financial flows of a country during a given period, is an important indicator of pressure o n a country’s foreign exchange rate This approach involves the supply and demand for foreign exchange as determined by the flows of currency from international transactions This approach affirms that the equilibrium exchange rate is established by matching the net inflow (outflow) of foreign exchange arising from current account activities and the net outflow (inflow)

of foreign exchange arising from financial account activities (Eiteman et al., 2010) In other words, the flows of currency related to the BOP comprise trade in goods and services, portfolio investment, direct investment, etc Equilibrium exchange rate is set when the BOP is in equilibrium

According to this approach, a current account deficit (surplus) tends to lead to a depreciation (appreciation) of the exchange rate However, as foreigners might be willing to finance the current account imbalance by lending or borrowing, which in turn produces a capital account surplus (deficit), the exchange rate depreciation (appreciation) might not occur in the short run (Rauli Susmel, undated) Thus, the BOP approach only has more precise predictions in the long run because the current account imbalance can not be financed forever The long-run exchange rate would move to balance the current account Another limitation of this approach is that it just focuses on flows of currency and capital rather than stocks of money or financial assets (Eiteman et al., 2010) That means relative stocks of money or financial assets has no contribution in determining exchange rate in this theory

2.3.3 Asset Market Approach

Rather than the traditional view of the exchange rate adjusting to equilibrate international trade in the BOP, an asset market model emphasizes on financial – asset markets This approach states that the exchange rate is determined by the supply and

demand for a wide variety of financial assets Since prices of physical goods adjust slowly compared to prices of financial assets which are traded more frequently every business day, the shifts in the supply a nd demand for different countries’ financial assets will be likely to change the exchange rate Moreover, changes in monetary and fiscal policy alter expected returns and perceived relative risks of financial assets, which in turn alter the exchange rate (Eiteman et al., 2010)

The asset market approach also assumes that whether foreigners are willing to hold domestic assets depends on a set of investment considerations including relative real interest rate, prospects of economic growth and profitability, capital market liquidity, economic and social infrastructure, political safety, corporate governance credibility, contagion, and speculation Thus, the approach can be used to forecast future spot exchange rate There are two basic groups within this model including the monetary approach and the portfolio – balance approach

Monetary Approach

Under this approach, the exchange rate is determined by the supply and demand for national monetary stocks, as well as the expected future levels and growth rates of monetary stocks (Eiteman et al., 2010) Other financial assets like bonds are not considered relevant for exchange rate determination According to Chinn (2013), the monetary model provides two key implications that are (1) higher relative income leads to a higher money demand relative to supply, and hence a stronger currency, and (2) higher relative interest rate causes a lower money demand against money supply which induces a weaker currency The approach includes two versions: (i) flexible – price monetary approach by Frenkel (1976); (ii) sticky – price monetary approach by Dornbrusch (1976) and Frankel (1979) PPP holds in both the long run and short run

in the former approach, while it only holds in the long run in the latter one

Portfolio Approach

This approach claims exchange rate affected by different portfolios of financial assets It assumes that assets denominated in different currencies do not substitute perfectly, which is the main difference from the monetary approach The imperfect substitution of international assets is due to foreign exchange risk perceived by investors According to Crowder (undated), the portfolio approach has risk premiums

in the forward exchange rate that are a function of relative assets supplies As the supply of domestic bonds rises relative to foreign bonds, there will be an increased risk premium on the domestic bonds that will cause the domestic currency to depreciate in the spot market If the spot exchange rate depreciates today, and if the expected future spot rate is unchanged, the expected rate of appreciation (depreciation) over the future increases (decreases)

These above approaches of exchange rate determination has been tested in many studies to find out what are the most important factors affecting a country’s exchange rate The next section discusses the exchange rate’s determinants in previous research

2.4 Determinants of Exchange Rate

According to Kanamori (2006), an exchange rate of a countr y is determined by macroeconomic factors, speculative factors, and economic expectations In other words, factors affecting exchange rate can be economic, political, and psychological

as well as in the short run or long run (Saeed et al., 2012) A study of a cross – section

of 81 countries carried out by Canales-Kriljenko & Habermeier (2004) observes that high inflation and fiscal deficit have a significant correlation with higher volatility, while foreign exchange reserves of a country and current account deficit appeared to

be insignificant This study follows the categorisation by countries studied in order to

evaluate the sensitivity of structural differences among the country groupings The categories include developed and developing countries

2.4.1 Empirical Literature from Developed Countries

McMillin and Koray (1990) examine the effects of the market value of both US and Canadian government debt on the real CAD/USD exchange rate The model indicates significant effects of debt on the exchange rate To be specific, debt shocks lead to a short – lived depreciation of the US Dollar rather than to an appreciation MacDonald (1998) builds a model that features productivity differentials, terms

of trade, fiscal balances, net foreign assets and real interest rate differentials as key determinants of the real exchange rate of the US Dollar, Yen and the Deutschmark

He finds that all the variables have a positive relationship with the real exchange rate

in both the short run and long run

Wilson (2009) examines the effective exchange rate of US Dollar based on the weighted average trading partner of USA Money supply is positively related to the effective exchange rate, which means increase in money causes decline in the value of currency In contrast, interest rate, government expenditure and defic it to GDP are negatively related with the effective exchange rate

Atif et al (2012) demonstrates the relationships between Australian exchange rate and its economic and non-economic determinants It is suggested that Australia’s trade components and macroeconomic indicators like net exports, GDP and money supply play a significant role in determining its exchange rates However, interest rate and inflation appear insignificant in this relationship

2.4.2 Empirical Literature from Developing Countries

The exchange rate’s determinants are also focused on in developing nations

Siddiqui et al (1996) estimates the determinants of real exchange rate for Pakistan The result is that increase in government expenditures leads to depreciation

in real exchange rate, as well as excess domestic credit creation and openness significantly contributes to real exchange rate appreciation Similar to the previous research, Hyder and Mehbood (2005) find that increase of governmental expenditure brings depreciation in the real exchange rate However, they identify that degree of openness and capital account balance also causes the real exchange rate’s depreciation Moreover, Saeed et al (2012) undertakes an analysis of determinants of exchange rate between US Dollar and Pakistani Rupee under the monetary approach from 1982 to

2010 The results confirm that the relative terms of stock of money, total debt, and foreign exchange reserves are significant factors of PKR/USD exchange rate

Aron et al (2000) investigate the short-run and long-run determinants of the real effective exchange rate for South Africa They find that an appreciation of the real exchange rate is led by an increase in terms of trade, price of gold, tariffs, capital inflows, official reserves, government share in GDP, technological progress and domestic credit, while a depreciation of the real exchange rate is produced by an increase in openness and nominal depreciation Furthermore, MacDonald and Ricci (2003) estimate the equilibrium real exchange rate for South Africa using the co-integration estimation procedure from 1970 to 2002 The result shows that the long-run real exchange rate is explained by real interest rate differentials, relative GDP per capita (productivity), real commodity prices (terms of trade), trade openness, fiscal balance and net foreign assets The behavior of South Africa Rand against US Dollar and Euro is also analyzed by Egert (2010) from 2001 to 2007 The empirical results show that changes in gold prices and innovations in exchange ra te of Dollar and Euro are two of four factors affecting South Africa’s exchange rate

Takaendesa (2006) also analyzes the determinants of real exchange rate of South Africa in the period of 1975 to 2005, and finds that the terms of trade, real interest rate differential, domestic credit, openness and technological progress have a long-run relationship with the real exchange rate Among other determinants, the terms of trade explain the largest proportion of the exchange rate’s variation The real exchange rate fluctuations are primarily equilibrium responses to monetary shocks rather than fiscal policy shocks

Bahmani and Kara (2000) examine the exchange rate of Turkish Lira against

US Dollar using monthly data from 1987 to 1998 They find that the negative sign of change in real income indicates the relative growth in the real income in Turkey relative to USA appreciates Lira Interest rate differential and inflation differential have positive signs and are statistically significant

Zhang (2001) adopts equilibrium real exchange rate approach and co-integration techniques to identify that investment, government consumptions, growth rate of exports, and degree of openness of the economy to trade are main explanatory factors for the China’s RMB’s long-term equilibrium path from the mid-1950s to the mid-1990s

Karfakis (2003) tests the monetary model for Romanian Lei and US Dollar exchange rate and concludes that increase in money is the source of depreciation in the domestic currency Real income is negatively related with the value of currency, while inflation has positive connection with the value of Lei against Dollar Moreover, Nucu (2011) explores the relationship between exchange rate of EUR/RON and key macroeconomic indicators including GDP, inflation rate, money supply, interest rate, and balance of payments for Romania The outcome is that GDP has a negative relationship with EUR/RON, whereas inflation and interest rate relate positively with

the exchange rate Both money supply and balance of payments are statistically insignificant

Joyce and Kamas (2003) investigate the factors determining the real exchange rate in Argentina, Colombia and Mexico Its co- integration analysis demonstrates that the exchange rate has an equilibrium relationship with terms o f trade, capital flows, productivity and government share of GDP An increase in all these variables appreciates the exchange rate

Karim et al (2007) uses quarterly data of macroeconomic variables for New Zealand and its trading partners including Australia, Japan, and USA to demonstrate the result that implementation of tight monetary policy causes both nominal and effective exchange rate to appreciate

Hsieh (2009) studies the behavior of Indonesian Rupiah per unit of US Dollar The result shows that a relatively higher domestic interest rate, or a relatively more expected inflation rate causes real depreciation for Indonesia Rupiah Conversely, higher ratio of governmental spending to GDP, or higher stock prices leads to real appreciation in IDR/USD exchange rate

Sinha and Kohli (2013) study the influence of some economic factors on the exchange rate of Indian Rupee against US Dollar over the period of 1990 to 2011 They find that economic variables like inflation differential, lending interest rates, and current account deficit (as a percentage of GDP) have significant effect on the USD/INR exchange rate

2.4.3 Conclusion

Overall, many studies about the relationship between the exchange rate and its macro determinants in both developed and developing countries have shown many

different empirical results regarding to the way of influence of each factors to the exchange rate Nevertheless, it can be seen that there are several main indicators that usually have impact on exchange rate including productivity, interest rate differential, inflation differential, terms of trade, capital inflows, government expenditure, current account, technological progress, official foreign reserves, money supply and degree of openness Thus, GDP, interest rate differential, inflation differential, current account, foreign direct investment (FDI) and foreign exchange reserves are chosen as the key determinants of VND/USD

However, this study adds two additional indicators that are the exchange rate of VND/EUR and VND/JPY to the list to test their correlation with VND/USD If the number of transactions using EUR and JPY increases, Vietnam would have a surplus supply of EUR and JPY that causes to the reduction in the price of VND/EUR and VND/JPY But since VND is a controlled and non- freely tradeable currency, other currencies such as EUR and JPY are converted to VND via USD peg Thus, these two exchange rates are considered to be highly correlated with VND/USD Due to this high correlation, later we will see in the multicollinearity test (section 5.2.4), EUR and JPY will be dropped out of our regresstion model Note that the regression on the above macroeconomic factors is an intermediate step of our analysis, and we will be using the resultant regression model in our Value-at-Risk (VaR) model and Stress Testing analysis

2.5 Stress Testing Theory

The second stage of this study is to conduct stress testing for Vietnamese firms Thus, the subsequent sections will introduce about the concept of stress testing including its definition, conducting framework as well as two main approaches

2.5.1 Definition of Stress Testing

Stress testing is one of the important tools for effective risk management and macro prudential oversight IAA (2013) clarifies a stress test as a projection of the financial condition of a firm or economy under a specific set of severely adverse conditions that may be caused by several risk factors over several time periods with severe consequences that can extend over either months or years as presented in Figure 2.1 On the other hand, a scenario is a possible future environment which involves changes and interactions among many risk factors over time A scenario with significant or unexpected adverse consequences is considered as a stress scenario (IAA, 2013) That means the probability of the scenario underlying a stress test has been referred to as extreme but plausible

Figure 2.1: Stress testing and scenario

Source: Stress Testing and Scenario Analysis, IAA (2013)

According to Blaschke et al (2001), the objective of a stress test is to make risks more transparent by estimating the potential loss on a portfolio in abnormal markets as well as to evaluate the strength or stability of institutions Moreover, stress

tests can be applied for either an individual institution or aggregate portfolios, and most often used to measure market risk – as in our case

There are two kinds of stress testing including micro versus macro stress test Micro stress testing is conducted b y individual institutions as part of their risk management and often ignores behavior of competitors, whereas macro stress testing refers to a range of techniques used to assess the vulnerability of a system to exceptional but plausible macroeconomic shocks (Sorge, 2004)

2.5.2 Framework for Stress Tests

Despite what kind of stress test, a sequence of the different decision elements of

a stress test shown in Figue 2.2 needs to be followed when conducting this test

The type of risks is specified first, and then the appropriate models are considered to use Stress tests can focus on individual risks or encompass multiple risks The most widely used ones are: (1) market risk, which consists of four standard risk factors are interest rate risk, exchange rate risk, equity risk and commodity risk, is defined as the risk of losses on a portfolio arising from movements in market prices; (2) credit risk is the risk of loss associated with debtor’s default of a loan or any other lines of credit principal or interest or both (Chopra, 2009); (3) other forms of risk includes liquidity risk and operational risk We will be focusing solely on market risk (i.e exchange rate risk)

The next element is the range of factors to include, followed by the specification

of scenarios Stress tests can involve estimating the impact of a change in a single risk factor called a sensitivity test, or the effect of a simultaneous move in a group of risk factors named a scenario analysis According to Kalfaoglou (2007), the scenario analysis technique is more demanding in terms of application and requires the use of

sophisticated econometric models In contrast, the sensitivity analysis is not as realistic as the former one because there is definitely more than one risk factor that is affected in times of shock Thus, it is mostly useful for analysis in the short run We will be conducting both sensitivity test and scenario analysis for our study

Figure 2.2: Frame work for stress testing of individual portfolios

Source: Blaschke et al., IMF Working Paper (2001)

Thirdly, the parameters to be shocked are decided The type of shocks are designed to integrate both movements in individual market variables such as prices, interest rates, etc and changes in the underlying relationship between different asset markets represented by their respective volatilities and correlations We will be shocking the changes in the statistically significant macro deteminants

Fourthly, the type of scenario used to conduct the stress tes t is critical to the analysis Stress testing can also be based on historical scenarios, which employ shocks that occurred in the past as a benchmark for future analysis, or based on hypothetical scenarios that are considered as plausible changes in circumstances that have no historical precedent Moreover, Monte Carlo simulations use techniques to look jointly at the sensitivities and probability distributions of various input variables (Chopra, 2009) We will be setting some hypothetical shocks for market parameters and running Monte Carlo simulation as well

Finally, the core assets are to be shocked with what the relevant risks are, how much to stress them and over what time period Once specified, the scenarios are applied to the portfolio to determine the potential change in the present value (Blaschke et al., 2001)

2.5.3 Main Approaches to Macro Stress Testing

Macro stress testing is used to quantify the link between macroeconomic variables and the health of either a single institution or the business secto r as a whole According to Sorge (2004), there are two main methodological approaches to macro stress testing including the piecewise approach and the integrated approach

 A piecewise approach that evaluates the vulnerability of the corporate sector

to single risk factors by forecasting several financial soundness indicators, such as

non-performing loans, capital ratios and exposure to exchange rate or interest rate risks, under various macroeconomic stress scenarios A direct economic relationship

is estimated using historical data between the macroeconomic variables and the various risk measures This approach is commonly used because of its ease in implementation However, it just focuses on the linear relationships between corporate risk and macro fundamentals as well as lacks an ability to characterize the entire loss distribution (Chopra, 2009)

 An integrated approach combines the analysis of the sensitivity of a system

to multiple risk factors into a single estimate of the probability distribution of aggregate losses that could happen under any given stress scenarios Value at risk (VaR), which is a method based on the probability of deviation from anticipated profit (Yildirim, 2012), is the most popularly used summary statistic of this distribution The VaR approach allows the risk parameters to be state or time dependent which helps address concerns of parameter instability It also permits non-linear relationships between macroeconomic shocks and risk measures Nevertheless, the non-additive across portfolios is a problem of the VaR approach As a result, such studies focus on

an aggregate portfolio cannot be likely to taken into account due to the domino effects among individual institutions (Sorge, 2004)

2.6 Value At Risk (VaR) Model

Stress testing is designed to explore the tails of the distribution of losses beyond the threshold used in the VaR analysis According to Blaschke et al (2001), VaR of a portfolio is a statistical measure that summarizes the maximum expected loss that the portfolio most probable to suffer over a specified period of time for a given level of confidence VaR can be used by any entity to measure its potential loss in value of its traded portfolios from adverse market movements, which can then be compared to its

available capital and cash reserves to ensure that the losses can be absorbed without putting the firm at risk (Damodaran, undated) The following figure shows the curve

of a hypothetical profit and loss probability density function with 5% VaR

Figure 2.3: VaR at 95% confidence level

Source: Wikipedia

There are three key elements of VaR including a specified level of loss in value,

a fixed time period over which risk is assessed and a confidence interval In VaR estimation, a confidence level and size of shocks need to be determined in advance The level of confidence is decided by the risk appetite of the firms and the amount of its economic capital, which is the amount of risk capital that a company estimates in order to remain solvent at a given confidence level and time horizon (Yildirim, 2012)

If the objective of estimating VaR is to forecast capital adequacy, the confidence level should be high enough so that there is very little probabiltiy of failure (Gupta and Liang, 2004) Bank for International Settlement (BIS), for example, suggests that market risk computations under VaR models should use 10-day holding period and 99% confidence level in their Basel II and Basel III regulations

Three basic approaches commonly used to compute VaR comprises variance – covariance method, historical simulation and Monte Carlo simulation

 Variance – covariance approach: This approach is based on the assumption

that the underlying market factors have multivariate normal distribution, and hence, the distribution of mark – to – market portfolio profits and losses could be determined

to be normal The potential loss or VaR is calculated from the volatility of the market factors, which can be estimated from the historical market data for the respective ones

as well as their correlations Consequently, VaR can be expressed as a function of the standard deviations of market returns and the covariance between them (Cassidy and Gizycki, 1997)

 Historical simulation: The aim of this simulation is to determine what

profits or losses would be incurred if a market price development from the past were

to occur today (SAP Website) It is a simple approach since it requires no assumption about the statistical distributions of the underlying indicators Instead, this method involves using historical changes in market rates and prices to construct a distribution

of potential portfolio profits and losses, and then come up with VaR as the loss that is exceeded a particular significance level (Linsmeier and Pearson, 1999)

 Monte Carlo simulation: It is the most widely used method among these

three approaches The simulation of returns scenarios is based on the generation of independent and identically random variables (Mina and Xiao, 2001) In other words,

a statistical distribution that effectively captures the possible changes in the market factors could be chosen, and a random number of hypothetical changes in these factors are generated in order to set up the distribution of possible portfolio profits and

losses (Linsmeier and Pearson, 1999)

We will cover all three methods above in this thesis In general, although these approaches for measuring VaR have the same limitation due to the fundamental assumption that is the future risk could be estimated from the historical distribution of returns, they also possess their own strengths and weaknesses which are summarised

in Table 2.1 as below

Table 2.1: The strengths and weaknesses of VaR approaches

Variance – covariance • No need for extensive

historical data, only volatility and correlation matrix are required

• Fast and simple calculation

• Less accurate for nonlinear portfolios or for skewed distributions

• Be used only when the portfolio is less diversified Historical simulation • No need to make

distributional assumptions

• Provides a full distribution

of potential portfolio values

• Faster calculation than Monte Carlo since less scenarios are used

• Requires a significant amount of historical data

• Difficult to scale far in the long horizons

• Coarse at high confidence level (e.g 99% and beyond)

• Incorporates tail risk only

if historical data set includes tail events

Monte Carlo simulation • No need for extensive

historical data

• Permits use of various distributional assumptions

• Provides a full distribution

of potential portfolio values (not just a specific percentile)

• Computionally intensive and time – consuming for revalue the portfolio under each scenarios

• Quantifies fat – tailed risk only if market scenarios are generated from the appropriate distributions

Source: RMG, Risk Management