Khóa luận tốt nghiệp: The relationship between economic policy uncertainty and Vietnamese stock market

VIETNAM NATIONAL UNIVERSITY UNIVERSITY OE ECONOMICS AND BUSINESSFACULTY OF FINANCE AND BANKING Graduation Thesis THE RELATIONSHIP BETWEEN ECONOMIC POLICY UNCERTAINTY AND VIETNAMESE STOCK

VIETNAM NATIONAL UNIVERSITY UNIVERSITY OE ECONOMICS AND BUSINESS

FACULTY OF FINANCE AND BANKING

Graduation Thesis

THE RELATIONSHIP BETWEEN ECONOMIC POLICY

UNCERTAINTY AND VIETNAMESE STOCK MARKET

TEACHER INSTRUCTION: PhD Vu Thi Loan

STUDENT: Nong Thi Huong Ly

CLASS: QH2019E TCNH CLC4 STUDENT CODE: 19050689

Ha Noi, May 2023

wll

I hereby declare that this graduation thesis is my own work, with the support of

my supervisor, and has not copied the work of others This is my own research work The data and secondary information used in the thesis are sourced and clearly cited.

This statement is entirely my responsibility.

Hanoi, May 13th 2023

Thesis author

Nong Thi Huong Ly

This thesis is the result of serious research by the author with my own efforts

However, to complete the thesis, I have received much encouragement and help from manypeople

First of all, I would like to thank the teachers who are lecturers in the VNU

-University of Economics and Business, who have dedicatedly imparted meaningful knowledge

and experiences on economic, financial and banking when I attended class QH-2019-E TCNHCLC 4, Faculty of Finance and Banking, VNU - University of Economics and Business to

confidently complete this graduation thesis

For this result, I would like to express my deep gratitude to the lecturer who guided

my graduation thesis during the last 3 months as a PhD Vu Thi Loan - lecturer at the Faculty

of Finance and Banking, VNU - University of Economics and Business, she has guided

wholeheartedly and thoughtfully in her professional knowledge so that I can complete mygraduation thesis well

In the process of doing the test, I tried my best to fulfil all the requirements and goalsset out, however, my knowledge and experience is limited, so mistakes are inevitable I lookforward to receiving suggestions from teachers to improve my graduation thesis

Finally, I would like to wish all teachers good health and success in their teaching

career!

TABLE OF CONTENTSCHAPTER 1: INTRODUCTTION G5 1E 2111 1n TH TH ng ng Hiệp 7

1.1 The urgency Of the topic - - c1 E101 11 1910111910199 in 71.2 Research ObJ€CfIV€S cọ HH in 8

IS uốn ố 81.4 Scope of the research va research subjects - - +2 12132 net 91.5 Research Questions - G cv TH HT nàn 9

1.6 Research cOntTIDUfiOTI - - << 110v nọ nọ nh 9

1.7 Research Structure cece 9

CHAPTER 2: LITERATURE REVIEW AND THEORETICAL BASIS ON THE

RELATIONSHIP BETWEEN ECONOMIC POLICY UNCERTAINTY AND

VIETNAMESE STOCK MAR.KET, Ăn HH 11

2.1 Literature review n 11

2.1.1 Overview of foreign research c1 113221011113 101 1 19 11111911 ng vn vờ 11

2.1.2 Overview of domestic r€S€aTCH c2 c E101 1113301 1 199111 9 vn vn vn rưy 13

2.2 Research ch 15

2.3 Theoretical basis on the relationship between Economic Policy Uncertainty and stock

2.3.1 Overview of Economic Policy UnC€TfAITVY s5 s3 vs seeeesresree 16

2.3.2 Theory regarding the effect of Economic Policy Uncertainty on the stock marketTOCUINS eee eee ẻ 20

2.3.3 Other theories concern the relationship of Economic Policy Uncertainty and the

3.2 Econometric model: Panel Regression Model - - «+ +- + +svkksseesseeeseves 30

3.3 Data collection methOs - - <6 1111911113911 1 1011k vn ng 33

CHAPTER 4: RESEARCH RESULTS OF THE RELATIONSHIP BETWEEN ECONOMIC

POLICY UNCERTAINTY AND STOCK MARKET RETURNS IN VIETNAM 38

4.1 Overview of the Vietnamese stock market and the uncertainty of economic policy in

Mr 435 38

4.1.1 Overview of the Vietnamese stock maTKef - 556 1 1+1 9 vs ke rey 38

4.1.2 Overview of Economic Policy Uncertainty in Vietnam «55+ <++++ 40

3

4.2 Research r€SuÏ(S - Q20 002022 6222229519953111 1111111 v TT gếg 41

4.2.1 Descriptive Sf{A{ISEICS HH nọ cư 41

4.2.2 Correlation ImATIX - <6 + 1 11 91v ng ng nh rưy 42

4.2.3 Result of Panel Regression Model - s + x19 1199 vn ngư, 43

4.2.4 Selection of Regression Model - - c 13111113511 1119111110111 18111 ng kh 45

4.2.5 Diagnostic ChecKing chờ 45

4.2.6 Re-estimation o6 e 45 46

CHAPTER 5: CONCLUSION 00115 49

5.1 Summary of research results 8 .e 49

5.2 Policy Implications - ceseceecceseeesaeceseecsseeesseeesaecesseseseeesaeessaeeeseeeneeenaeene 50

5.2.1 Policy Implications for ŒOV€TnIN€TI - c5 2 c1 13332111133 EEEESsseerree 50

5.2.2 Policy Implications for inVestors <5 2 E111 KH Hư, 505.3 Research limitations and directions for future stUd1eS - 555 «+ +ssxessss 51

5.3.1 Research ]ImI{Af1OTS c1 1201011991111 011119 vn rưy 51

5.3.2 Directions for future Studies - 5 0121112111191 9 1119 11191 vn ngư, 52

3535450101117 Ô - 53

References in English P0 53

References in ¿coi Bố e 54

LIST OF ABBREVIATIONS

ABBREVIATIONS ORIGINAL

EPU Economic Policy Uncertainty

PE Price/Earning RatioEPS Earning Per Share Ratio

DP Dividend Payout Ratio

DI Domestic Investors

FI Foreign Investors

TO Turnover

EU European UnionHOSE Ho Chi Minh City Stock Exchange

POLS Pooled Ordinary Least Square

FEM Fixed Effect Model

REM Random Effect Model

LIST OF TABLES AND FIGURE

Table 3.1: Variables and Source of Data - <5 1119210111199 1 11199 11H ng ky 36Figure 4.1: VN-Index in the period 2003-22 - - - << 6 1111391113391 11 311 1y key 38

Figure 4.2 Economic Policy Uncertainty Index in Vietnam 55 << s++ssecsss 40

Table 4.1 Descriptive Statistics - Ặ HH HH ky 41

Table 4.2: Correlation matrix - ó6 c0 1901169911 89111 91 90v 42Table 4.3 : Result of POLS, FEM, REM model - - - + EE *E + SE ££ceeee 43Table 4.4: Model Selection R©SuÏ 56 c1 99112 vn ng 45

Table 4.5 Multicollinearity of Mode] .- s 6111111111991 1119k rưy 45

Table 4.6 : F-statistic from Serial Correlation Wooldridge test - 55 2-ss<s++sseesss 46

Table 4.7: Result of FEM model - - - - <5 1113111112111 199011 rưy 47

CHAPTER 1: INTRODUCTION

1.1 The urgency of the topic

The world is facing Economic Policy Uncertainty (EPU) such as the economic shockdue to the COVID-19 pandemic and US-China trade war Fascinatingly enough, unlike the

9/11 Terrorist Attack, Russia-Ukraine War or even Syrian Civil Wars, COVID-19 pandemic

is the first event that imposed such high degree of uncertainties that had ever degraded thestock market and soared the economic policy risk Thus, it is certain that the current world is

more sensitive towards economic policy risk (EPU) than ever before The phenomenon of

Economic Policy Uncertainty (EPU) is not limited to a specific set of countries, and manycountries have experienced EPU in varying degrees EPU can arise due to several reasons,including changes in government policies, political instability, geopolitical tensions, orunexpected events such as pandemics (Phan et al 2021, Fang 2019, Jiang 2020) For instance,

the Brexit referendum in the United Kingdom caused significant EPU, as policymakers andinvestors were uncertain about the future of the country's trade relations with the European

Union (EU) The challenge facing each country's policymakers is that understanding the

impact of the EPU on countries' economies is crucial for policymakers and investors to make

informed decisions and minimize the potential negative effects of the EPU

In light of the recent global financial crisis and growing partisan policy disputes in the

US, there are growing concerns about policy uncertainty mainly related to economic policies

and financial decisions (Baker et al., 2016) This is largely based on the belief that U.S andEuropean tax uncertainties, as well as fiscal, monetary, and other regulatory policies, have

contributed significantly to the economic downturn and global finance in 2008 and the slowrecovery thereafter Issues such as rising unemployment and income inequality, migration,

and volatile oil prices have complicated the global economy Furthermore, uncertainty in

economic policy has always played an important role in shaping economic outcomes, asevidenced by the recent sluggish economic growth in many countries currently experiencing

policy instability

The effects of EPU on countries' economies can be significant and may differ

depending on the country's economic structure, policies, and institutional frameworks Forinstance, a study by Ludvigson et al (2021) found that EPU can reduce investment and output

growth, increase unemployment, and lower household consumption In the case of the United

States, Baker et al (2016) found that EPU has a negative impact on economic activity, with

lower investment, employment, and output growth.Li and Zhang (2020) found that EPU inChina reduced investment, particularly in state-owned enterprises, and weakened the link

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between investment and economic growth Similarly, Baek and Brockman (2020) found that

EPU in Korea reduced stock market liquidity, which can lead to higher transaction costs and

lower trading volumes Overall, these studies suggest that EPU can have negative effects oncountries' economies, which can be challenging for policymakers to manage In contrast,

studies have shown that EPU can have a positive impact on countries with more flexible

economic policies, such as China According to Wang et al (2021), EPU in China canstimulate investment in certain industries, such as real estate, due to the government's flexible

policy responses

These challenges about EPU are also apparent in emerging economies such asVietnam The Vietnam stock market is not immune to the effects of EPU, as it has been

shown to have a negative impact on the stock market's performance For instance, Nguyen et

al (2020) found that EPU has a significant negative impact on the returns and volatility of theVietnam stock market Therefore, it is crucial to investigate the relatedness between EPU and

the Vietnam stock market to identify the factors that influence the market's performance and

investors’ behavior By studying the relationship between EPU and the Vietnam stock market,

we aim to contribute to the existing literature on the effects of EPU on the stock markets

Ultimately, my research will shed light on what we can expect when considering the

relationship between Economic Policy Uncertainty and the Vietnam stock market

Qualitative method: Collect reputable documents and refer to previous research papers

related to the topic to get detailed information about the research object, thereby forming atheoretical basis, reasonable and solid reasoning method for the topic

Quantitative method: after having background information and data set, model

variables using quantitative models in a specific time frame The data from World Uncertainty

Index for Vietnam https://fred.stlouisfed.org/seriessWUIVNM is the foundation of the

research Data are presented in panel form and using OLS , FEM, REM model to estimate andevaluate the effect of EPU.

1.4 Scope of the research va research subjects

- Time scope: Effect of Economic Policy Uncertainty on the stock market between the

Ist quarter of 2002 to the first quarter of 2023

- Space scope: Studying the influence of economic uncertainty policy on the Ho Chi

Minh City Stock Exchange (HoSE)

1.5 Research questions

- (1) How does Economic Policy Uncertainty affect the Vietnamese stock market and its

dynamics?

- (2) What is the difference between the impact of domestic and international EPUs on

Vietnam's stock market?

- (3) What macroeconomic factors affect the relationship between Economic Policy

Uncertainty and the stock market?

1.6 Research contribution

Through the study, the author is expected to make the following contributions:

First, overview, systematize the theory on the relationship between Economic PolicyUncertainty and the stock market

Second, the study measures Economic Policy Uncertainty and the stock market

through panel data models including: POLS, FEM, REM In addition, the study also evaluates

the impact of the Economic Policy Uncertainty index on the stock market's profitability ratio

In particular, the study tests that the EPU index has a negative relationship with the

profitability of the Vietnamese stock market

Third, based on the research results, the study also makes some recommendations for

the Government and investors, securities companies to improve the level of investors as well

as enhance market transparency

illustrates the research data and models specification Chapter 3 Chapter 4 presents empiricalresults Chapter 5 is the conclusion.

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CHAPTER 2: LITERATURE REVIEW AND THEORETICAL BASIS ON THE

RELATIONSHIP BETWEEN ECONOMIC POLICY UNCERTAINTY AND

VIETNAMESE STOCK MARKET

2.1 Literature review

2.1.1 Overview of foreign research

“* Economic Policy Uncertainty impact on stock market

The paper by Li et al (2015) studies the predictive power of Economic Policy

Uncertainty (EPU) on stock market volatility The evidence in our sample shows that a higherEPU leads to a significant increase in market volatility The out-of-sample findings suggest

that incorporating EPU as an additional predictor to existing volatility prediction models will

significantly improve the predictive power of these models

The paper by Jun et al (2015) examines the link between Economic Policy

Uncertainty and stock prices in both time and frequency domains Wavelet analysis shows

that the relationship is generally negative but time-varying represents low-to-high frequencycycles Furthermore, the timing of frequency changes overlaps when U.S policy uncertainty

combines with other countries' policy uncertainty

The study by Saud et al (2019) contributes to existing research by reviewing theliterature on the impact of Economic Policy Uncertainty on corporations and the economy

economy worldwide The paper demonstrates the importance of measuring and monitoringuncertainty by highlighting its influence on financial decisions This paper examines the

growing number of studies that use the Baker et al (2016) Economic Policy Uncertainty index

(EPU) as a key factor in measuring uncertainty sure Then look at the impact of the EPU on

financial markets, macro and micro levels, stock markets, corporate behavior, and risk

management Then document the asymmetric policy responses of economic uncertainty.Overall, policy uncertainty has a significant impact on corporate financial policies as well as

consumer spending In particular, corporations act more cautiously during times of greatuncertainty, thereby slowing investment in production and employment Besides the localeffect of the EPU, it also spreads to other countries

Article by Phan et al (2018) using data from 16 countries, examines whetherEconomic Policy Uncertainty (EPU) predicts surplus returns stock balance First, the paper

points out that the EPU's ability to forecast stock returns depends not only on the country

used, but also on the sectors examined This indicates that the earnings forecast is countrydependent (industry dependent), suggesting that the EPU is relatively more important for

some countries (sectors) than others (sectors) Second, the paper examines whether the

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predictive power of the EPU is from either or both the cash flow and discount rate channels.The results of the article support the discount rate channel on the cash flow channel Third,the paper uses positive and negative shock EPU to predict excess stock returns and findsevidence of asymmetric predictability Finally consider a mean variance investor and show

that the investor has positive utility by having the following projections generated from the

EPU-based model The results of the article are consistent with several durability tests

Research by Umer et al (2019) examines the relationship between Economic Policy

Uncertainty (EPU) and the performance of non-financial companies listed in the United States

Using four measures of firm performance such as Return on Assets, Return on Equity, NetProfit Margin, and Tobin's Q, the author finds that the effect of EPU on company

performance is significant and negative for all four representatives Systematic-GMM

estimation is used to solve the problem of endogeneity because the unreported results suggestthe presence of variable variance and autocorrelation in the OLS and fixed effects estimates

The paper by Xu et al (2021) investigates the predictive performance of the China

Economic Policy Uncertainty Index (EPU) developed by Davis et al (2019) in Profit forecast

of China stock market By using univariate and two-variable predictive regression models, the

paper confirms that the monthly EPU can have a negative and significant impact on the next

month's stock returns and has the ability to predict out-of-sample outperforms the existingEPU and several macroeconomic variables By comparing the predictive performance of theEPU index before and during special events with increased uncertainty, find that thepredictive power of the EPU declines rapidly as the event occurs

The paper by Chen et al (2018) investigates the impact of China's Economic PolicyUncertainty (EPU) on the time series variation of expected returns on Chinese stock market.Using the EPU's news-based measure, find that the EPU negatively predicts future stock

market returns at various horizons This negative relationship between Economic PolicyUncertainty and expected future returns remains significant when controlling for several

economic and market uncertainties or conducting out-of-sample testing Our findings are

consistent with behavioral asset pricing models, where high uncertainty amplifies behavioraltrends and creates speculative, mispricing in short selling

s* Micro and macro factors affecting the stock market

The research of Kaan et al (2019) investigates the impact of macroeconomic factors,

German government bond yields, sentiment and other leading indicators on the main Germanstock index, namely the DAX30, for the time period from 1991 to 2018 Using a dataset on 24

factors and over a timeframe of about 27 years, found evidence that across most subsamples,

the Composite Leading Indicator (OECD), the Institute for Economic Research (ifo) Export

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Expectations index, the ifo Export Climate index, exports, the Consumer Price Index CPI, aswell as 3 y German government bonds yields show delayed impacts on stock returns Furtherfound that the delayed impact of the constituents of the monetary aggregate M2 on stockreturns changed direction between the crisis and post-crisis periods Overall, the results

illustrate that in the crisis period a larger number of factors and economic indicators had

significant impacts on the stock returns compared to the pre- and post-crisis periods This

implies that in the post-crisis period a macro-driven market prevails

The research objective of Chang et al (2019) is of twofold: first, to empirically

examine the short-run and long-run impact of macroeconomic variables such as industrialproduction, foreign direct investment (FDI), trade balance (TB), exchange rate, interest rate

(IR) and consumer price index (CPI) on stock prices (SP) of KSE-100 index; and second, to

examine whether this relationship changes as a result of the financial crisis

Bhuiyan et al (2019) examines how certain macroeconomic variables influence

different sectors of the stock market differently in the US and Canada Using monthly data

over the 2000-2018 period, a cointegration analysis is applied to model the relationshipbetween industrial production, money supply, long-term interest rate, and different sector

indices Sectors that have been examined in this study include energy, financials, real estate,

industrial, healthcare, consumer discretionary, and consumer staples Results suggest thatthere is a stable long-term relationship between the macroeconomic variables used in thestudy and different sector indices for the US but not for Canada However, US money supplyand interest rate can explain the Canadian stock market The results suggest important insightsfor private investors, pension funds, and governments as long-term investors often base their

decision to invest in equities on the stated macroeconomic variables

Kofi et al (2019) examine the degree of significance between different sectors

stock-price and MVs and predict a 30-day head stock-stock-price using Random Forest (RF) with an

improved leave-one-out cross-validation tactic and Long Short-Term Memory Recurrent

Neural Network An empirical analysis of the proposed model over the Ghana Stock

Exchange (GSE) exhibits high prediction accuracy and better mean absolute error compared

with other time-series techniques It can, therefore, be inferred from the fallouts that theproposed stock-market prediction with MVs, provides an efficient approach to automatic

identification and extraction of MVs that affect diverse sector stock and offer an accurate

prediction of a stock's future price

2.1.2 Overview of domestic research

“* Uncertainty in the market impact on Vietnam's economy

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Ly et al (2020) examines the effect of China's Economic Policy Uncertainty oncorporate cash holdings in six countries in Southeast Asia The idea of research stems fromthe increasingly close relationship between the Chinese economy and neighboring countries,

in which China's dominant role has emerged over the remaining countries Using level data in the six countries mentioned above for the period 2010-2018, the research results

company-show that increasing uncertainty in China's economic policy causes companies in SoutheastAsia to hold less cash In addition, we find evidence that Economic Policy Uncertainty

contributes to reducing the negative impact of investment on money holdings The results are

consistent when using alternative measures for China's Economic Policy Uncertainty andwhen changing the estimation method

Nguyen et al (2023) studied the impact of Economic Policy Uncertainty on stock

volatility forecasts The topic applies the GARCH - MIDAS model, which can combine theuncertainty index of low-frequency economic policy with the return of high-frequency

securities into the model and forecast the volatility of the stock index The estimated results in

the sample show that both the magnitude and the variance of the uncertainty index ineconomic policy provide useful information on forecasting the volatility of the Vietnam stock

index The forecast results show that the uncertainty of economic policy in the GARCH —

MIDAS model can significantly improve the predictability of stock index movements

Vo et al (2023) explores the causal relationship between inflation and inflationuncertainty in some Southeast Asian countries The data used in the research is collected fromJanuary 2008 to December 2019 The paper measures inflation uncertainty by the conditionalvariance estimated from the GARCH model In addition, besides the Granger test, Toda-Yamamoto test was also added to add statistical significance on the causal relationship Theresearch results found a two-way causal relationship between inflation and inflation

uncertainty in Singapore, Thailand and East Timor while Vietnam, Laos and the Philippinesonly recorded a one-way effect from inflation to inflation uncertainty

s* Micro and macro factors affecting the stock market

Yen et al (2014) analyze the current situation and empirical research results, this

study shows the extent and direction of influence of macroeconomic factors such as inflation,interest rate, money supply, exchange rate on Vietnam's stock market in the period 2007-2012

as well as pointing out the remaining problems of the Vietnamese stock market and its causes

From the research results, the author proposes solutions to stably develop Vietnam's stockmarket

The research objective of Truong (2014) is exploring determinants of stock returns forthe Ho Chi Minh Stock Exchange (HOSE) Data used in the study include quarterly series of

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portfolio price index and earning per share (EPS) of 20 stocks listed on HOSE, interest rate,USD/VND exchange rate, gold price and consumer price index (CPI) for the period from 31December 2006 to 31 December 2012 The results derived from this study show that EPS andUSD/VND exchange rate have positive effects on stock returns while gold price volatility and

inflation rate have a negative impact on stock returns

Research paper by Nguyen et al (2020) examines the factors affecting the profitability

of securities on the Vietnamese stock market by using the valuation models CAPM, Fama

-French, Carhart The research data is collected as secondary data and from the financial

statements of 100 companies listed on the Ho Chi Minh Stock Exchange (HOSE) for theperiod 2015 - 2019 The research results show that the return rate of securities on HOSE, in

addition to being objectively affected by market factors, is also affected by factors belonging

to the characteristics of listed companies such as size, value (BE ratio) /ME) and trends Themarket factor plays the most important role among the four factors and is positively correlated

with profitability The size factor has a negative correlation and plays an important role

When considering the company's value factor (BE/ME ratio), this factor is positivelycorrelated, but has a negligible impact on profitability Finally, the trend factor partly explains

the impact on profitability but not significantly The results of this study will help companies

better understand their intrinsic value as well as their competitiveness At the same time,helping investors have a basis to choose an effective investment portfolio in the current

exciting stock market

2.2 Research gap

Thus, it is certain that the current world is more sensitive towards economic policy

risk (EPU) than ever before As a result, researchers are interested in exploring therelationship between EPU and stock market, examining the effect of EPU on stock market At

present, there are not many research articles on the impact of EPU on the stock market in

Vietnam Although there have been a number of detailed studies as mentioned above, thereare currently almost no studies directly observing and measuring the influence of EPU on

stock price movements in the stock market securities in Vietnam with a holistic and general

approach The data sample used is only in a certain period of time and has not been updated

until 2023

For the above reasons, this paper wishes to contribute to the overall picture of the

impact of EPU on stock returns on the Vietnamese stock market, giving an overview and

some ideas recommendations to stakeholders The author proposes an approach to study the

influence of EPU on stock price returns for nearly 20 years in the Vietnamese stock market

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From there, the author hopes to be able to examine the influence of EPU from a dimensional, deeper perspective, and at the same time, be able to detect and test someanomalous phenomena occurring through the waves of stock fluctuations in the market Thedata sample is also spread with nearly 20 years on HoSE, quarterly data, updated as of March

multi-31, 2023 Thanks to previous research works, the author of this essay can refer to the research

methods as well as the research results that have been achieved to create a premise for thedevelopment of his own research

2.3 Theoretical basis on the relationship between Economic Policy Uncertainty and

stock market

2.3.1 Overview of Economic Policy Uncertainty

2.3.1.1 The concept of uncertainty in economic policy

Economic Policy Uncertainty (EPU) has its origins in the uncertainty of inflation,

negative economic growth, financial crisis, extraordinary loan cuts, pandemics, increases of

unemployment, foreign exchange fluctuations and unexpected changes in monetary policy.EPU can manifest in the form of unexpected changes in monetary, fiscal, and regulatory

policies, and it mainly comes from whether current policies will change in the future or not?Economic Policy Uncertainty describes the unknown effects of new policies on the economy

and the private sector

Over the past few years, a number of major challenges have emerged, causing global

political and economic instability These began with the revolutionary wave of the "Arab

Spring", which led to political instability in the Middle East and among the world'ssuperpowers, and followed by the election of Donald Trump, who called for major changes in

the global status quo became president of the United States The recent vote for the UK toleave the European Union, or "Brexit", has raised doubts about the future of the Euro and

economic policies in Europe As the world continues to develop at a rapid pace, such changes

create a sense of political and economic instability, increasing uncertainty around the world

Since the publication of John Kenneth Galbraith's book “The Age of Uncertainty” in

1977, many significant events covered by the media and in academia have highlighted

uncertainty as a significant issue in the financial world There is no doubt about theimportance of uncertainty; however, the literature does not agree upon a single definition ofuncertainty Furthermore, the effect of uncertainty on corporations was not studied until a fewyears ago Galbraith, 1977 Geopolitical uncertainty, industry-specific events, or even firm-

specific news, such as ambiguous sales forecasts, rumors of a competent CEO's departure, or

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a change in management, are just a few examples of uncertainty Therefore, some touncertainty as the unpredictability of fiscal, regulatory, and monetary policies, whichultimately contributes to market volatility More specifically, economic uncertainty can bedefined as unexpected changes that affect the economic ecosystem, and how such changes in

fiscal or monetary policies or any other government policies affect corporations (Abel, 1983)

Policy uncertainty is the economic risk associated with undefined future governmentpolicies and regulatory frameworks This phenomenon further increases the risk that both

businesses and individuals will delay their spending and investments due to market

uncertainty According to Baker et al (2016), after the 2008 global financial crisis,uncertainty around government policies peaked due to business and household uncertainty

regarding the government's future regulatory framework, spending, taxes, monetary policies,

and healthcare These authors suggest that policy uncertainty particularly delayed thepossibility of recovery from the recession as businesses and postponed their decisions about

investment and consumption expenditures The ambiguity of future policies has only a

long-term effect It is evident that many factors affect uncertainty Some issues affect uncertaintyboth in the short and long terms, such as currency fluctuations and changes in senior

management, whereas other issues have only a short-term effect, such as variations in oil

prices Thus, the time horizon is a key factor in understanding the impact of the determinants

of uncertainty This calls for finding measurement of the uncertainties caused by these variousfactors

Uncertainty is the ambiguity, uncertainty, and ambiguity, but in a broader sense, thejudgments of a diverse group of people such as customers, corporate executives and policymakers about possible future prospects of the business Another definition, Economic PolicyUncertainty is unpredictable changes that affect the economic system and thereby cause

changes in government policies In other words, it reflects the volatility of the economyresulting from unpredictable economic, political, and monetary policies (Saud et al., 2020)

Many factors influence the degree of uncertainty, however, as uncertainty increases,

its effects are expected to have long-term effects on investment and economic development

(Sahinoz et al., 2018) It is therefore essential to devise a measure that reflects the degree ofnational uncertainty that has a material effect on the economy as a whole

2.3.1.2 Measuring uncertainty in economic policy

It is clear that many factors influence uncertainty in economic policy Some issues

affect uncertainty both in the short and long term, such as currency fluctuations and topmanagement changes, while others have only a short-term impact, such as the changes in oil

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prices Thus, delineating the short-term or the long-term is key to understanding the impact ofthe determinants of uncertainty This requires finding ways to measure Economic PolicyUncertainty caused by various factors.

One of the oldest and most widely accepted measures is the standard deviation of

stock prices and stock returns The Market Volatility Index (VIX) from the Chicago Board of

Options Exchange has been used for many years as a proxy for corporate uncertainties in theStock Market However, the VIX is a market metric, thus capturing only market uncertainty

Since market measures depend on market liquidity and depth, they represent the best capture

performance for mature markets and industries and cannot be further expanded in countries

Another research trend focuses on emphasizing the importance of political uncertainty

Julio and Yook (2012) explore the uncertainty surrounding election years and propose the use

of a dummy variable for these years Jaramillo et al (2007), measure uncertainty usingeconometric techniques The authors argue that macroeconomic instability is a factor in the

uncertainty surrounding election years and propose the use of a dummy variable during these

years Jurado et al (2015) measure uncertainty using econometric techniques The authorsargue that macroeconomic instability is a factor that creates uncertainty, thereby developing

and introducing new indicators for uncertainty in economic policy through measures of

macroeconomic instability, collectively known as the macroeconomic instability index Theseindicators are based on a variety of economic parameters including macroeconomicparameters and financial market indicators Although these measurements are acceptable, thelimitation is that they only measure one or a few specific factors that constitute the generaluncertainty The advantage is that these measures highlight the importance and differencesbetween factors affecting future uncertainty; it illustrates how news, politics, policy andmarkets can affect policy uncertainty However, most of these measurement methods are noteasy to use because they are not widely publicized and are not easy to use and replicate in

different countries and economies It is this gap that prompts researchers to look for a broader,

more inclusive measure to capture all the factors that make up uncertainty

These prior efforts motivated Baker et al (2016) to develop a proxy index for

Economic Policy Uncertainty that includes and measures most of the factors highlighted inearlier studies The EPU index captures uncertainty from news, policy, market, and economic

indicators Baker et al (2016) aggregate all these factors into a new index-the economic

policy index-by using the average of three parts: the extent of newspaper coverage for related economic uncertainty, how many provisions in the federal tax code expire soon, and

policy-the disagreement among economic forecasters Among policy-these three factors, policy-the authors assert

that the coverage of news in reputable journals mentioning uncertainty in the economy related

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to policy factors is the central factor forming EPU index, therefore Baker et al (2016)

improved this index to include only the news element This can be measured by searching for

newspaper articles containing the words “economic”, “economy”, “uncertainty”, and

“uncertain” along with “regulation” and “legislation” and one or more of the following terms:

“congress” ,” “legislation”, “white house”, “regulation”, “federal reserve” or “deficit”

The EPU index is based on diverse indicators of Economic Policy Uncertainty, such asthe frequency of references to policy uncertainty in newspapers This index corresponds well

with events widely associated with times of extreme policy uncertainty, wars, debt ceiling

debates, the Eurozone crisis, and the Troubled Asset Relief Program (TARP) legislation Themeasure is also highly correlated with the VIX The availability of this index has spurred

many scholars’ interest in the field and has helped answer a wide range of related research

questions These efforts have led to widespread acceptance of the index and opened the doorfor further studies Davis (2016) based on the principle of Baker et al., built a global EPU

index based on the principle of weighted averaging data of countries with large economies,

arguing that these countries cover most of the world picture

Consequently, the EPU has significant micro- and macro-economic policy

implications More specifically, uncertainties about both monetary and fiscal policies have a

massive impact on the overall economy For example, when it comes to financial markets,monetary policy uncertainties usually have an impact on exchange rates and financial trading

markets They illustrate some exchange rate trading strategies that can achieve high returns

during periods of financial or monetary uncertainty In other words, uncertainty about thefuture economic policy can alleviate the impact of monetary policy tools Thus, the EPU canaffect and reduce the power of monetary policy changes The effect of international trade ondomestic employment depends on industry and trade exposure; more exposure results in astronger effect (Pierce et al., 2016) The impact of uncertainty on employment depends on

industry exposure to both economic policies and international trade Therefore, EPU plays amore significant role in forecasting future economic growth That the EPU index haspredictive power and can be used to forecast future recessions Uncertainty introduces new

friction into financing that stops or at least slows economic growth Therefore, various laborrelocation trends, the aggregate output into the economy, and changes in unemployment

should be prioritized to predict new macro-economic indicators The uncertainty around the

growth of future corporate earnings has significant predictive power for GDP and influencesboth production and employment Besides, it has a significant impact on banking and

monetary policies

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Additionally, the EPU index has a negative correlation with both inflation andproduction Inflation rates are low, and unemployment rates are high when uncertainty is

high, leading to lower demand for consumption and spending (Leduc et al., 2016)

Consequently, this creates a demand shock in the whole economy The theory of endogenous

financial policy and growth best explains the shocks that translate into aggregate demand

uncertainty shocks However, the predictability of future uncertainty can change over timeand depends on the time horizon and data range The correlation between uncertainty and

inflation changed from positive to negative during the mid to late 1990s Overall, the EPU has

harmful effects, as both the government and households avoid financial risk Furthermore,policy uncertainty further reduces the motivation for investors, households, and governments

to invest Thus, there is a negative impact of EPU in the economy at both the micro- and

macro-economic levels Therefore, governments around the world should put the rightfinancial policies in place for banking borrowing, interest rates, and overall economic

policies Recurrent budgetary allocations, development allocations, and avoid borrowing by

the government should follow a well laid out policy framework to any looming economic

volatility (Mian et al., 2015)

2.3.2 Theory regarding the effect of Economic Policy Uncertainty on the stock market

returns

Economic Policy Uncertainty is of a macro nature because it originates from the

uncertainty of inflation, negative economic growth, financial crisis, pandemic, that's whythe EPU is very important and has a great influence on the stock market returns Some recent

studies examine the specific effects of uncertainty, especially macro-economic and political

uncertainty, on market returns Exposure to national and global political risk and governmentinstability may lead to less freedom and flexibility, as well as a potential decrease in firm

efficiency Also, for specific industries, local and global political risks could lead to higherreturn volatility Consequently, uncertainty in political conditions introduces challenges for

businesses (Boutchkova et al., 2012) Therefore, The EPU index can be used to predict futurereturns in the financial market, economics should be considered a risk factor and compensatedwith a premium Returns are lower during periods of high uncertainty than in other periods

An investment strategy based on EPU index can produce significant positive returns The

options market shows that investors consider uncertainty in their pricing; as a result, stocks

have lower prices during times of high uncertainty Thus, the exposure to Economic PolicyUncertainty may be a contributing factor to jump risk in the crosssection of returns EPU

index has some predictive power for market shocks So, EPU does not only affect the stocks

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returns but also volatility Therefore, firm exposure to Economic Policy Uncertainty can offersome explanation to the asymmetric volatility puzzle However, the effects of EPU depend onthe country, the strength of the economy, and the size of the stock market (Christou et al.,

2017) The findings from prior research show that it still has a significant negativerelationship with the stock market, however, the impact of uncertainty is weaker in some

countries In addition, there is disagreement on the direction and strength of the relationshipbetween the EPU index and stock markets in emerging markets, that the EPU index has more

considerable influence in emerging markets due to credit constraints; however, the effect is

lower in other emerging markets (Das et al., 2018) Uncertainty can have a spillover effect toother countries, EPU has a significant negative relationship not only with the stock market but

also with bond prices, production, and investment Stock market volatility leads to higher

unemployment rates, which means that policy uncertainty could lead to fewer jobs in theeconomy The results reveal that the EPU has a potentially harmful influence on the US stock

and bond markets

The effect of EPU is not limited to capital markets but also applies to bank valuations,where values decrease with uncertainty (He & Niu, 2017) Banks have lower valuations

because they have low or even negative growth rates under high uncertainty Besides, EPU

has a significant impact on GDP growth, commodity returns, and volatility Similarly, the

EPU has a highly significant positive correlation with the prices of oil companies over thelong run Furthermore, it has some predictive power in terms of the returns of both the oil and

stock markets (Balcilar et al., 2017a) In future policies impact gold prices in the short run interms of both returns and volatility Therefore, movement in EPU index leads to movement ingold prices, consistent (Fang et el., 2018) Recent literature examines the influence of politicaluncertainty in financial markets The “presidential puzzle,” the phenomenon where returnsunder Republican and Democratic presidencies dramatically differ Annual returns are

between 9% and 16% higher under Democratic administrations than under Republican

administrations While concluding that government spending growth is higher under

Democratic leadership, the mechanism driving the return disparity remains an unansweredpuzzle This is in line with other studies that illustrate that the peak EPU index is close to

presidential election periods (Baker et al., 2013) High investment rates in the public sector

forecast high-risk premiums on stocks at both the aggregate and firm levels This issue

directly by using EPU index and exposure to government spending predicts returns in thecross-section With a high degree of exposure to government spending outperform those with

a low degree of exposure under Democratic presidencies and underperform under Republican

presidencies The same pattern holds in terms of cash flow These results are unexplained by

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firm characteristics, common risk factors, or the business cycle There is higher governmentspending under Democratic presidencies than Republican uncertainty presidencies This isintroduced as a potential explanation for the higher returns for firms with significant

government exposure.

On the other hand, the market sentiment about future policies has a minor impact on

consumer spending (Mian et al., 2015) The influence of government economic policy andinvestor sentiment on the aggregate micro- and macro-economy However, uncertainty in

economic policy increases overall market volatility and firms are more exposed to the impacts

of uncertainty during these periods The impact is not limited to capital markets but hasgeographical spillover effects; it is one of the main factors driving investor sentiment This

calls for more research to understand the interconnection between these factors and reveal themain drivers

2.3.3 Other theories concern the relationship of Economic Policy Uncertainty and the

stock market

2.3.3.1 Efficient market theory

The efficient market theory has an important theoretical and practical significance inthe financial industry The economist Samuelson once remarked: "Financial economics is

considered the crown jewels of the national holidays, the Efficient Market Theory will

account for half of those jewels!"

The efficient markets hypothesis (EMH), was first put forward by Eugene Fama(1970) The article is an important work, paving the way for many later studies on the

accuracy of the Efficient Market Theory The term "efficiency" here is used by the author to

imply the rapid absorption of information, not resources that produce maximum output as inother fields of economics Information is also understood as news that can affect prices and isunpredictable

In fact, in capital markets, efficient markets can be understood in many different ways.Fama (1970) states that: “A market in which prices always reflect available information iscalled an efficient market.” Meanwhile, Malkiel (1992) argues that a capital market is said to

be efficient if it fully and accurately reflects all relevant information in determining stock

prices.Usually, however, markets are said to be efficient for some information, if security

prices are not affected by disclosure of that information to participants

The study of stock market efficiency has been popular since the 1960s This concept

began to appear in the research papers of a French mathematician, Louis Bachelier Do you

study stocks and other commodities to see if they fluctuate randomly? In 1905, Karl Pearson

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introduced the random walk (Random walk or Drunkard walk concept) However, the firstefforts of Bachelier and Pearson were ignored and no further studies were made until 1930.After that, a series of analyzes and studies were conducted Some typical milestones in thestudy of Efficient Market Theory can be mentioned:

Kendall (1953), who first used the term random walk in financial theory, observed 22

UK stock indexes and US commodity prices to find regular price cycles He noticed thatprices seemed to follow a random walk, they could go up or down on any particular day,

regardless of what happened the day before

Roberts (1959) finds similar results for the US indices He confirmed that changes inthe Dow Jones are random Osborne (1959) demonstrated that US stocks move randomly like

particles

In particular, Fama (1965) discussed some empirical evidence supporting the randomwalk theory in his doctoral thesis He then presented his doctoral thesis at the University ofChicago Management Conference in 1965 Fama developed the random walk theory as anaccurate description of reality At that time, fundamental analysis or technical analysis wasoften used and supported the methods of stock price prediction by market experts Fama

contrasted the random walk theory with fundamental and technical analysis These methods

are considered too complicated for non-mathematicians The logic behind technical analysis,

he claims, is that history tends to repeat itself According to him, it is not possible to achieve

extraordinary returns by looking at past price changes because price changes are independent

The assumptions of fundamental analysis depend on the belief that a security has an intrinsicvalue that is different from its actual price Thus, an analyst can predict the future price of asecurity by assessing factors that affect intrinsic value such as the quality of management, thegeneral state of the industry, economic conditions, etc and compare it with the actual price

of the stock

According to Fama (1970), presented a landmark paper on efficient markets This

article has focused on a comprehensive review of this theory He defines an efficient marketvery clearly: “A market in which prices always fully reflect all available information is said to

be efficient.”

In the following years, a series of studies on Efficient Market Theory were born to

analyze and prove the arguments made earlier, about the practicality of Efficient Market

Theory Whether a stock market is said to be efficient is up for debate in any country

Efficient markets include many different hypotheses, depending on the extent to which

information is reflected in security prices

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Weak form efficiency hypothesis: Weak efficiency occurs when a security's pricereflects historical information about a security's price, including stock price and tradingvolume In other words, based on past stock prices, one can forecast current stock prices.Since it is assumed that current market prices reflect all past earnings and all market

information, historical returns, as well as other historical data, has no relationship with future

rates of return (return rates are independent of each other) Empirical research shows thatoften markets are weakly efficient The evidence shows that subsequent price changes are

often random and that the correlation between today's stock price and the next day is close to

zero Therefore, past prices and volumes do not help forecast future price changes (andtechnical analysis isn't worth it)

Semi-strong form efficiency hypothesis: This level of efficiency occurs when a

security's price reflects publicly available information in the market, including historicalinformation about the security's price and information that is publicly available in the market,

such as those on an issuer's prospectus Moderately efficient markets cover the weak

efficiency hypothesis because all market information must be publicly considered based onthe weak form efficient market hypothesis such as stock prices, interest rates, and transaction

volume Public information also includes all non-market information such as: earnings and

dividend announcements, P/E, D/P, P/B, stock splits, political economy information Thishypothesis implies that investors, when making decisions based on new information after

publication, will not receive higher-than-average returns because stock prices immediately

reflect all publicly available information When past information is an aggregate of all

publicly available information, if the market is moderately efficient, it is also weakly efficient

However, the market can be weakly efficient when it has not yet reached its average

efficiency This implies that investors can obtain extraordinary returns based on publiclyavailable information The faster the stock market responds to this information, the less profitinvestors will earn

Strong form efficiency hypothesis: Strong efficiency occurs when all information is

fully reflected in stock prices, including non-public information, such as information within

the business The strong-form efficient market hypothesis is a combination of both the form and the medium-form efficient hypothesis The strong-form efficient market hypothesis

weak-extends the assumption to efficient markets - markets in which the pseudo-markets reflect

publicly available information, to perfect markets - markets in which all information is freeand available at the same time If the market is strongly efficient, the market must be

moderately efficient However, a market that is not highly efficient can still be moderately

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efficient At that time, non-public information can be used to generate extraordinary profits,

but once this information is made public, extraordinary profits cannot be achieved

2.3.3.2 Behavioral finance theory

The method of principal component analysis (PCA) proposed by Karl Pearson in

1901, Hotelling in 1933 and Jolliffe in 2002, is a method of linear transformation of data into

a new coordinate system, such that the set of the new variables — the principal components —

are linear functions of the original variable Basically, PCA is just a coordinate

transformation, used to reduce the size of the data set PCA reduces the data down to its basiccomponents, stripping away any unnecessary parts According to behavioral finance theory,

the momentum effect in the market is the result of investors’ slow reaction This reaction takes

place in the short and medium term, in the long term leads to overreaction causing a reversal

effect

Hong & Stein (1999) proposed a behavioral model consisting of two trading subjects,

newswatcher and momentum trader (roughly translated as news investor and trend investor)

The pattern begins to take shape when private information spreads slowly in the news trader

community These people reacted causing the stock price to gradually correct to createmomentum, but the correction was not strong enough for the price to exceed fair value

Therefore, this initial reaction is a slow one Price movements attract a second player to the

market, further fueling the momentum effect The increasing trade of a class of followers at some point causes the market price to exceed fair value, their reaction being anoverreaction, leading to a reversal This study was then provided evidence in the article byHong et al (2000) on the US stock market

trend-According to Barberis et al (1998) and Doukas & McKnight (2005), momentum

comes from investors’ conservative sentiment That is, investors have the mentality of

maintaining previous views, valuing past views, and underestimating new information,

leading to a lack of behavioral adjustments It is difficult for investors to change or changetheir investment views very little, and when behavioral adjustments are not made enough, it

leads to slow response

Daniel et al (1998) argue that self-attribution bias causes momentum: Overconfidentinvestors overestimate their abilities or information they currently have, ignoring other

information and downplaying the risks Baber & Odean (2000) agree that transaction

frequency is a measure of confidence According to them, confident investors often think theycan be the winners of the market, so in order to capture more profit opportunities, they will

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trade frequently resulting in momentum However, the reality is the opposite, Barber & Odean(2000) concludes that the more investors trade, the more they lose.

Behavioral finance believes that the irrational behavior of investors in the stockmarket usually takes place continuously, not intermittently The following analysis will clarify

the argument of the behavioral finance school when considering the decision-making process

of investors in the stock market:

Overconfidence

Many researches about psychology on the stock market have shown that investors tend

to be overconfident about their behaviors (Barberis and Thaler, 2003) One typical aspect ofoverconfidence is the better than average effect, where people believe their skills are better

than the average and think unrealistically of themselves (Taylor and Brown, 1988) It was

proved in many studies that many investors also tend to believe that they are better than others

at selecting the best shares, as well as the best time to enter and withdraw from the market

They, at the same time, believe that they work with above-average efficiency, which indicates

overconfidence exists or even plays important roles in their activities (Odean, 1998; Wang,2001; Heaton et al., 2002; Grinblatt and Keloharju, 2009; Montier, 2009)

Herd Behavior

On the stock market, herd behavior is when investors follow others’ behaviors, even

when their private information tells them to act otherwise In other words, it is when investorscopy each other (Banerjee, 1992; Bikhchandani and Sharma, 2000; Hwang and Salmon,

2004) If only one investor behaves irrationally, it does not affect stock price However, if the

irrationality is systematic, meaning when a large group behaves in the same irrational way,price will be determined wrongly and probably over a long period Experimental studies also

reveal the fact that investors tend to have irrational behavior at or around a certain point of

time In that case, individual investments are not considered as separate transactions but ratherbehavior by a huge organization that strongly affects the market, causing inaccurate stock

pricing (Odean et al., 2009) Besides, herd behavior is not only in the sense of copying the

crowd but also not acting in the opposite direction of the crowd’s behavior regardless of what

their own information tells them This is a direct influence on investing attitude

Psychology of risk

There are many definitions of risk in finance, but most arguments contain the concepts

of unexpected results and uncertainty Tversky and Kahneman (1974) reveal that predictingand forecasting under uncertainty do not usually follow probability rules The prospect theory

by Tversky and Kahneman claims that people tend to be risk averse in the “profitable zone”

and risk seeking in the “losing zone” (Tversky and Kahneman, 1992) Therefore, deviating

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from the standpoint of standard finance, behavioral finance also examines subjective factors,

where observed risks include both emotional and perceptual aspects Two main attitudes

toward risk are risk aversion and risk seeking, both could manifest in one individual underdifferent circumstances (Olsen, 2007; Olsen, 2008) It was proved that one of the importantfactors influencing investing attitude is investors’ tolerance for risk (Bennet, 2011) Duringthe period of this research, the Vietnamese economy suffered from recession, which created

risk aversion among investors on the Vietnamese stock market

Excessive optimism

Overconfident investors usually overestimate the role of their own information andtherefore excessively trust their capacity Excessive optimism usually comes from

overconfidence and captures the perception that future incidents would be better and more

positive than present situations Over-optimistic investors may believe that bad investmentwould not harm their portfolio and therefore expect too much from the market and from

investing opportunities (Wang, 2001; Heaton et al., 2002; Lindblom et al., 2002) Excessive

optimism also has positive impacts on investing attitude and encourages people to invest,since too much risk aversion would decrease trading volume (Heaton et al., 2002) However,

excessive optimism has negative effects when it leads to highly risky investment Moreover,

there exists a link between overconfidence and excessive optimism as indicated by (Lindblom

returns, suggesting that higher inflation rates lead to lower stock returns For example, Chen

et al (1986) found that inflation rate has a significant negative effect on stock returns in the

long run, while Fama and Schwert (1977) found a negative correlation between inflation rate

and stock returns in the short run However, other studies have found a positive correlation

between inflation rate and stock returns For instance, Binswanger and Fare (1989) found apositive correlation between the inflation rate and stock returns in the long run, while Khan

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