The nexus between the credit rating and financial markets in Asian Countries 2019 2000
Prepared by the researcher : Amira Abdelhalim Fathy , Reham Hussein Hasan , Donia Hesham Abdelaziz , Roaa Waleed Mostafa , Mostafa Moawed Mohamed – Supervisor : Dr. Ali Mohamed Ali – BeniSuef University – Faculty of Politics and Economics
Democratic Arab Center
Abstract
The financial development has significant impact on the economy, capital accumulation and fosters the economic growth. Also, a country’s sovereign credit rating may affect its ability to access capital in the domestic and global bond market. This study relies on the data provided by the Fitch rating agency for the credit ratings of the nine Asian countries. Moreover, it studies the relationship between the financial market and credit ratings in 9 Asian nations from 2000 to 2019 is explained in this study. The authors in this study used the financial development index, financial market index and financial institution index as proxies for the financial development as dependent variable. And the explanatory variables are Countries credit rating, Real GDP per capita, real interest rate. Furthermore, Pooled OLS, Fixed effect and random effect are used to estimate the effect of sovereign credit rating on financial development. Particularly, the finding exhibits that there is a positive relationship between the financial development index and countries credit rating. Also, there is a positive relationship between the Countries credit rating and financial market index also, there is a positive relationship between financial institutions index and countries credit rating.
 Introduction:
The financial development in Asia may be dated to the nineteenth century, When Western nations first made their presence felt in the area, and the Empirical estimates suggest that financial development has supported growth. However, it was not until after World War II that Asian countries began to develop their own financial systems. And some financial liberalization happened which led to make the financial markets became less regulated, that allowed for the entry of international banks and other financial institutions. Also, the financial development could yield additional gains for the region. In addition to it plays a huge role in the economy, also promotes economic growth through capital accumulation.
The sovereign credit rating of a country may determine its ability to access funds in the national and international bond markets, there are three influential credit rating agencies include Moody’s, Fitch Ratings, and Standard & Poor’s, as a result of lacking of the data; this study depend on Fitch rating agency in their data for the 9 countries credit rating.
This study explains the relation between the financial market and the credit rating in 9 Asian countries from 2000 to 2019 that differs in all of these indicators, With the respective to the financial market, the study examine the financial development index rates nations according to the depth, access, and efficiency of their financial institutions and financial markets, that defined the financial development market. So, the study aims to providing an explanation of various Asian nations’ sovereign credit ratings, outlining the variables that influence the financial markets. In theoretical framework the study is using independent variables as Real GDP, Consumer Price Index (CPI), Real interest rate and countries credit rating and dependent variables as financial development index, financial market index and financial institution index using pooled OLS estimation, Fixed effect estimation, Random effect estimation and 2SLS.
1.1. Research Problem:
A sovereign credit rating is an independent assessment of the creditworthiness of a country or sovereign entity. Sovereign credit ratings can give investors insights into the level of risk associated with investing in the debt of a particular country, including any political risk.
Because its importance, it attracted the attention of many economists, also many theoretical and practical studies have emerged from it, especially on the issue of the impact of sovereign credit rating on financial markets in various countries of the world, due to the strong relationship between sovereign credit rating and financial markets. So, the main question on which the research depends on:
To what extent does sovereign credit rating affect financial markets?
The following subquestions are emerged from the main question as follow:
 What are the factors that affect financial markets?
 How does sovereign credit rating affect financial markets?
1.2. Research Importance:
As scientific importance, this study reinforces the scientific theory between changes in sovereign credit rating and financial markets, as it works to estimate the extent of the impact of sovereign credit rating on financial markets.
As practical importance, the practical importance of this study is that it is a tool that can be used by decisionmakers in finding solutions to the question of sovereign credit rating and its impact on financial markets. In the volume of in addition to that it covers a large part of this issue, which can be taken as a reference for researchers in the same field.
1.3. Research Objectives:
This study aims to:
 Explaining the sovereign credit rating in some Asian countries.
 Clarifying the factors that affect financial markets.
 Analyzing the relationship between sovereign credit rating and financial markets in 9 Asian countries (2000 – 2019).
 Estimate the effect of sovereign credit rating on financial development index, financial market index and financial institution index.
1.4. Research Hypotheses:
The study testing if financial markets are affected positively by sovereign credit rating or not.
1.5. Research Limitations:
Through this study, authors aim to measure the impact of sovereign credit rating on financial markets, it has two spatial and temporal frameworks, regarding the spatial framework, this study concerns 9 Asian countries limited to data availability. As for the time frame, it defined the Period (2000 2019).
 2. Literature reviews:
Cantor et al (1996):[1]
This study finds evidence that the rating agencies’ opinions independently affect market spreads. Event study analysis broadly con firms this qualitative conclusion: it shows that the announcements of changes in the agencies’ sovereign risk opinions are followed by bond yield movements in the expected direction that are statistically significant. In addition, it shows that the relationship between ratings and yields is nonlinear. If finds that Standard and Poor’s announcements that corporate ratings are under review have significant market impact only when announcements classified by the authors as “expected” are excluded from the sample.
Larraín et al (1997):[2]
The study aims to a broader empirical content for judging whether the two leading rating agencies lead or lag market events with respect to sovereign risk. The study uses two methodologies Granger causality tests and event study. the results show a twoway causality between ratings and yield spreads and reject Granger causality of both ratings and yield spreads. The result explains that ratings cause yield spreads and vice versa.
Ferri et al (1999):[3]
The study demonstrate that credit rating agencies aggravated the East Asian crisis. In fact, having failed to predict the emergence of the crisis, they downgraded East Asian crisis countries more than the worsening in these countries’ economic fundamentals would justify. As the crisis became full blown the rating agencies downgraded the sovereign ratings of Indonesia, Korea and Thailand all below investment grade. the discussion on the rating agencies’ failure to warn the markets before the East Asian crisis. Moreover, the study compared between the Asian and Mexican crisis. The methodology used is random effect estimation, the results show that the shortterm debt measure is negatively and significantly correlated with sovereign ratings, GDP per capita changes to negative in both the pre and postcrisis models so it is not statistically significant with credit ratings and the budget deficit, is negatively correlated with ratings, and not significant.
Kaminsky et al (2001):[4]
This study examines the effect of credit rating upgrading and downgrading on the financial market using panel data of countries from East Asia, East Europe, and Latin America states. The study finds that the change in credit rating has an effect on the country risk and stock market. This paper examined the effect of domestic vulnerability, as measured by the ratings of international agencies. It uses panel regressions, event studies as methodology to measure its objective. It used EMBI spreads, stock returns, interest rates, and credit ratings as variables to measure the hypothesis. the study reached a number of results which are; rating changes significantly affect bond and stock markets. When credit rating increased (upgrades) the yield spread increased by 3 % and in the case of downgrade the stock return decline by 1%. Due to contagion, rating changes between the emerging markets changes in the yield spreads and stock returns in foreign countries. Still, the effect is smaller than that of rating changes of the domestic economy.
Kräussl (2005):[5]
The study examines the role of credit rating agencies in international financial market, and do sovereign credit ratings have an impact on the financial stability in emerging market economies in the second half of the 1990s. During the 1990s, the global securities markets have become an increasingly important source of external funding for many emerging market countries. Adjustments of sovereign credit ratings for many emerging market economies throughout the Asian financial crisis of 199798 raises the worries about the credit rating process and in particular about the usefulness of sovereign credit ratings, the study explores the role of credit rating agencies in international financial markets, in addition to the importance of credit ratings for institutional investors. The two different methodologies have been applied are event studies to know any possible dynamic effects after the agencies’ sovereign credit rating actions, and the panel regressions are estimated to know the effects following the changes in the sovereign credit ratings. As a measure of financial market crises is measured as the weighted average of daily nominal exchange rate changes, daily shortterm interest rate changes and daily stock market changes. The specification results show that a firstorder autoregressive process is sufficient, since further lags appear to be insignificant. The results of the study shows that credit rating agencies have an influence on the size and volatility of emerging markets lending, in addition to being significantly stronger in the case of government’s downgrades and negative sovereign credit rating actions. In addition to this, sovereign credit rating event moves the index of financial market pressure only by 1.3 percent.
PukthuanthongLe et al (2007) :[6]
The study examines the impact of changes in sovereign ratings and outlooks on international capital markets using database of 34 countries over the period 1990– 2000. They affect both bonds and stocks market. It ensures that bond markets react differently than stock markets in many respects. It finds ,for bond market returns, a positive impact is significant when the economic outlook is upgraded. In addition, downgraded ratings and economic outlooks occur mainly during bond market downturns. On equity returns, the market responses of downgrade are more pronounced in the cases of high inflation, low fiscal balance, and local currency debt.
Kim and Eliza Wu (2008) :[7]
This study discusses how the history of sovereign credit ratings affects the development of the domestic financial sector and international capital flows to emerging countries. We address this issue using data from 51 emerging markets from Standard & Poor’s during the period 19952003. We find strong evidence that sovereign credit ratings influence intermediary financial sector developments and capital flows. We find that: first, longterm sovereign credit ratings in foreign currencies are important to encourage the development of financial intermediaries and to attract capital inflows; second, longterm domestic currency ratings stimulate domestic market growth but discourage international capital flows; third, shortterm ratings (foreign and local currency) delay all forms of financial developments and capital inflows.
Afonso et al (2011):[8]
The study examines the effects of sovereign credit rating announcements of upgrades and downgrades (as well as changes in rating outlooks) on sovereign bond yield spreads in EU countries using EU sovereign bond yield and CDS spreads daily data through a couple of dimensions: first, the effect is anticipated, the effect is different between the economic and Monetary Union (EMU) and nonEMU countries, if the reaction of yields and CDS markets has increased after the onset of the 2008 financial crisis ;second, the methodology is standard event study analysis on the reaction of government yield spreads before and after announcements from rating agencies, in addition to the study runs a causality test between the transformed ratings and the yield (CDS) spreads. Furthermore it uses dummy variables up M and down M, as an example for Moody’s. Moreover it examines if sovereign yields and CDS spreads in a given country react to rating or not.
Rabah et al (2011):[9]
The study examines spillovers effects of sovereign credit rating news across countries and financial markets. This study uses daily data on sovereign credit default spreads (CDS), stock market indices and banking and insurance subindices for selected European countries from 2007 to 2010. It finds that these spillovers effects depend on the type of rating announcement, the source country that is downgraded moreover the rating agency from which the announcement originate. In addition to reducing the sovereign credit rating has indirect effects, such as stimulating financial instability, with statistical and economic significance across countries and financial markets. For example, on December 8, 2009, the downgrade of Greece’s sovereign credit rate from A to BBB+ by Fitch had systemic spillover effects across the Eurozone countries. In this study, there are important implications for policy makers to encourage the provision of longer term credit ratings to promote financial development in emerging economies.
Christopher et al (2012):[10]
This study conducts various analyses to measure the impact of sovereign ratings on an emerging market’s: first, stock market comovement with its corresponding regional stock market index; second, bond market comovement with its corresponding regional bond market index. It examines the effects of sovereign credit ratings on the stock and bond market in nineteen emerging countries during the period from January 1, 1994 to July 1, 2007. Sovereign ratings and its expectations have an spillover positive impact on the regional stock market whereby upgrades provide common benefits to neighboring countries, however downgrades will cause investors to shift their money from the downgraded market to the surrounding area. On the other hand, the sovereign rating and outlook negatively affects the regional bond market. It finds that the negative impact is concentrated in countries with foreign currency debt ratings above the regional average.
Alsakka and Ap Gwilym (2013):[11]
The financial crisis in Europe 2006:2010 has drawn our attention to the role of credit rating agencies in the financial system. Moreover, he studied how the foreign exchange markets react. And the results show that the sovereign credit signals have a significant impact on the foreign exchange market. And, there are different reactions to the news from the different credit rating agencies. Moreover, they notice that the effect of the credit rating in the crisis has more impact on the exchange rate of the countries and contributes to contagion.
Afonso et al (2014):[12]
The study focuses on the analysis of the daily stock market in Europe stock market and sovereign, and studied the impact of volatilities to sovereign rating and announcements on the European bond and equity market. The study concludes that the changes in the sovereign ratings have symmetric effect on equity and bond volatilities. The upgrade in the ratings has no significant impact but any downgrade increases the volatilities of the stock market. Moreover, the results showed the importance of taking into consideration the credit rating because this act can decrease the risk and increase the benefits.
Fatnassi et al (2014):[13]
The study uses panel regression of 4 European stock markets (Greece, Portugal, Spain and Italy) from June 2008 to June 2012 to examine the impact of sovereign credit rating announcements of Standard and Poor’s, Fitch and Moody’s on the own stock market and neighboring countries. The study find that sovereign credit ratings affect stock market returns, during debt crisis negative announcements have an impact not only on own stock market returns but also contributed to contagion.
Pilar Abad et al (2017):[14]
This study shows liquidity shocks on the US corporate bond market around credit rating change announcements. The results show that: first, the market anticipates rating changes; second, the concrete materialization of the announcement is not fully anticipated; third, a clear asymmetric reaction to positive and negative rating events is observed; fourth, different agencyspecific and ratingspecific features are able to explain liquidity behavior around rating events; fifth, financial distress periods exacerbate liquidity responses derived from downgrades and upgrades.
Tracy Li and Zhang (2017):[15]
This study analyses the impact of credit rating changes from two aspects. Firstly, credit rating will impact company capital structure decisions. Secondly, there is an offset pattern in daily abnormal returns and volatility of stock returns increases after a credit rating change event. Specifically, downgrade has a bigger impact on stock performance. The result is the companies generally issue more debt when forecasting a credit downgrade to take the advantage of the relatively low cost of capital, while a small number of firms keep corporate structure unchanged due to flexibility concerns.
Abdul Rafay et al (2018):[16]
The study covers three aspects; factors determining credit ratings, impact of credit ratings on performance of entities and the relationship between stock returns and credit ratings. The study focuses on the firms listed in Taiwan Stock Exchange (TSE) of Taiwan. The result is the credit ratings are predicted by important firm specific factors like size and growth opportunities, capital intensity, asset returns, sector type etc. Results suggest that firms with higher credit ratings tend to have better performance.
luitel and Vanpée (2018):[17]
Their study investigates to what extent sovereign credit ratings help low developed countries to financially develop. The study uses a sample of 24 developing countries that are unrated on December 2016 and find that sovereign credit ratings the government is less dependent on bank financing and make banks provide more credit to the private sector which increase banks’ risk weighted assets. The results show the crucial role of sovereign credit ratings in the country financial development.
Rabia Nawaz (2018):[18]
In this study, the researcher focuses on the effect of the sovereign credit rating announcements on sample of five countries of ASEAN and four of southern Asian markets from 1997:2015. This study investigate the effect of changing ratings in the stock market, and the effect of the rating news on closed border countries. In southern Asia the results show indirect effect of the downgrades in the credit rating on the movements of the stock market in ASEAN which lead the investors to withdraw funds from the downgraded country as well as the neighbouring countries which lead negative effect on neighbouring countries. The results confirm asymmetric effect of the correlations which lead to spill over effect of the information and have negative correlation with the stock market.
Stijn Claessens et al (2018):[19]
The study shows how banks determine loan terms under capital constraints. Using a unique and comprehensive supervisory datasets of individual corporate loans in the US, the study shows that unexpected adjustments to banks’ internal rating systems, which only alter how outsiders assess the riskiness of borrowers, trigger changes in loan terms. The result there are effects to be strong for smaller, riskier, and capital constrained banks as well as for borrowers with poorer credit quality and for non guaranteed loans.
Chunling Li et al (2019):[20]
This study attempts to model the impact of sovereign credit ratings score assigned by standard Poor’s and Moody’s on financial markets using autoregressive distributed lag setting to test linear and nonlinear impact of CR on financial market development. Panel dateset of 40 European countries from 1990 to 2018 as a stable and developed financial markets implies that Economic, financial and political variables affect stock market in long term while only political and financial have an impact in short term. This study find that there is an asymmetric relationship between credit ratings and financial market development proving that policy formation should take into account nonlinearity otherwise policies maybe detrimental if they based on only linear models.
Ramin Baghai et al (2020):[21]
They see that the credit rating is used globally in mandates, and it is considered an important factor to determine the level of the risk taking by funds. Moreover, even if the credit rating has flaws it is necessary for the investors, the health of the financial market.
Khansa Pervaiz et al (2021):[22]
They studied the role of sovereign credit ratings announcement by standard and Poor’s and Moody’s on financial market development of 24 Asian countries from 1990 to 2018 using historical grades to establish the relationship and financial crisis impact which spread through financial channels and trade to Asian markets the study performing regression analysis on SCR changes based on financial market development index and its factors and using Driscoll kraay’s covariance matrix find that sovereign credit ratings have positive impact on financial market development in the region.
Asif Khan and Oláh (2022):[23]
The study shows the impact of the sovereign credit rating (SCR) on the financial market development (FMD) of China , which provides policy input for shortterm decision making. in this context, it is worthwhile investigating how the SCR asymmetrically affected the FMD of China. The result shows that the relationship of SCRFMD turns nonlinear.
 Theoretical framework:
There are no general agreements between the empirical studies about a unified mathematical equation for the financial development index, financial institution index and financial market index.
Therefore, table (1) summarizes the key determinants that affect financial developments in the most empirical studies:
Table (1) financial development determines in previous studies
Authors  Dependent variable  Explanatory variables 
Calza et al. (2001)  Real loans  GDP per capita in PPS, shortterm and longterm real interest rates. 
Hofmann (2001)  Real loans  Real GDP, real interest rate, housing price. 
Calza et al. (2003)  Real loans  Real GDP growth, nominal lending rate, inflation rate. 
BrzozaBrzezina (2005)  Real loans  Real GDP growth, real interest rate, GDP per capita n PPS, inflation rate, financial liberalization index. 
Cottarelli et al. (2005)  Credit to the private sector (%GDP)  Accounting standards, entry restrictions to the banking sector, German origin of legal system, public debt 
Boissay et al. (2006)  Credit to the private sector (%GDP)  GDP per capita, real interest rate 
Kiss et al. (2006)  Credit to the private sector (%GDP)  GDP per capita, real interest rate, inflation rate 
Frank Packer. (1996)  Credit rating  Income per capita, GDP growth, Inflation, Fiscal Balance, External Balance. 
Eliza Wu. (2008)  FINDEV are the three financial market development measures for country.  foreign currency ratings for long term sovereign debt issues, foreign currency rating shortterm sovereign debt issues, local currency sovereign debt for long term, local currency sovereign debt for long term . 
J. E. Stiglitz (1999)  Sovereign rating  shortterm debt, GDP per capita, Real GDP growth, Inflation rate, Budget deficit, Current account balances, External debt 
Judit Oláh (2022)  Financial market development  Sovereign credit rating 
József Popp (2021)  Financial market development index  Sovereign credit rating, economic growth, trade openness, inflation, banking development, investment 
Victoria Zhang (2017)  Expected market return  Credit rating 
Rosanne Vanpée (2018)  Financial development  Sovereign credit rating 
Source: constructed by authors from Egret, Backe and Zumer study (2006) and literature reviews.
Based on the previous table, the suggested equation between them could be formulated as follows:
FD_{it }= f (GDP, SCR, Inflation, Real interest rate)
 Where i refers to the country, t refers to the time dimension (year).
 Financial development (FD) is proxies by financial development index, financial institution index and financial market index.
 SCR stands for Sovereign credit rating.
 is the other control variables affecting the financial development level.
 In this context and based on table (1), X would be represented by GDP, Inflation and Real interest rate.
 GDP is proxies by Real GDP per capita.
 Inflation is proxies by Consumer price index.
 Data and methodology:
The objective of this study is to investigate empirical correlation between financial development and credit rating applying on 9 Asian countries from 20002019.
4.1. Data:
The data set consists of dependent and independent variables which are first : credit rating, according to Fitch agency ;that represents the dependent variable and the independent variables and other control variables which are , the Financial development index (FDI) which summarizes how developed the financial institutions index ( FII) and the financial markets index (FMI) are in terms of their financial market depth index (FMDI) in addition to financial institutions depth index ( FIDI) which represent by the size and liquidity , although the financial market access index (FMAI) and financial institutions access index ( FIAI) through the ability of individuals and companies to access financial services, finally represents the financial market efficiency index (FMEI) and financial institutions efficiency index ( FIEI) by the ability of institutions to provide financial services at low cost and with sustainable revenues and the level of activity of capital markets.
4.2. Descriptive statistic
Table (2) exhibits the descriptive statistics associated with financial development index, financial market index, financial market efficiency index, financial market depth index, financial market access index, financial institutions index, financial institutions efficiency index , financial institution depth index and financial institution access index. The sample is panel data for 9Asian countries from 2000 to 2019 that differs in all of these indicators as reflected by the magnitude of the standard deviation relative to the mean of each indicator.
Table (2)
Descriptive statistic for all variables
Variables  Mean  Median  Standard deviation  Maximum  Minimum  Observation 
FDI  0.551  0.604  0.217  0.812  0.272  9 
FMI  0.534  0.578  0.215  0.183  0.811  9 
FMEI  0.606  0.63  0.333  1  0.171  9 
FMDI  0.529  0.565  0.250  0.816  0.0895  9 
FMAI  0.447  0.38  0.175  0.734  0.221  9 
FII  0.542  0.567  0.566  0.865  0.2975  9 
FIEI  0.664  0.645  0.051  0.7265  0.576  9 
FIDI  0.462  0.475  0.305  0.8995  0.111  9 
FIAI  0.396  0.331  0.248  0.879  0.1625  9 
Source: constructed by authors from IMF data base.
 3. Financial development levels in Asian countries:
Financial development index is a relative ranking of countries on the depth, access, and efficiency of their financial institutions and financial markets. It is an aggregate of the financial institutions index and the financial markets index. It shows the average value of financial development for 9 Asian countries for the period (2000:2019) with
Figure (1) shows that Japan has the highest value (0.812) and Sri Lanka has the lowest value (0.272). The average of other countries are: china is 0.752, India is 0.434, Indonesia is 0.32245 Korea.Rep is 0.8115, Malaysia is 0.623, Philippines is 0.3265, and Thailand is 0.6054.
Source : constructed by authors from IMF data base.
Figure (1) Financial Development Index
Figure (2) shows the average value of financial market index for 9 Asian countries for the period (2000:2019). Financial market index uses to explain a certain area of the financial market which reflect the stock market. The average in China is 0.729 which is lower in India that is 0.507 and Indonesia is 0.312 unlike japan and Republic of Korea which are 0.7265 and 0.811 that is highest average, where Malaysia records 0.578, Thailand is 0.6215, Philippines is 0.269 and Sri Lanka is 0.1825.
Source : constructed by authors from IMF data base.
Figure (2) Financial Market Index
Figure (3) shows the average of financial market efficiency index for 9 Asian countries for the period (2000:2019). Market efficiency refers to the extent to which current prices reflect all available and relevant information about the actual value of the underlying asset. A truly efficient market eliminates the possibility of market beating, because whatever information is available to any trader is already incorporated into the market price. As the quality and quantity of information increases, the market becomes more efficient which reduces arbitrage opportunities and market returns on top of it. It is clear that The Republic of Korea is the highest country (1) then Japan (0.9935), on the other hand, Sir Lanka is the lowest country (0.171).
Source : constructed by authors from IMF data base.
Figure (3) Financial Market Efficiency Index
Figure (4) shows the average of financial market depth index for 9 East Asian countries for the period (2000:2019). Early literature used the ratio of total bank credit to GDP as an indicator of financial depth. Deeper financial markets can absorb flows more easily. With more developed capital markets, liquidity flows tend to be more diffused across the financial system. Furthermore, a deep financial system can use liquidity more effectively in a nonwasteful and nondistorted way.
Source : constructed by authors from IMF data base.
Figure (4) Financial Market depth Index
Figure (5) represents the average of the financial market access index which records a highest average on China and Republic of Korea by 0.6925 and 0.734 while in India is 0.221. In contrast in Indonesia is 0.3445 and Japan 0.4805 also in Malaysia is 0.518, Philippines 0.3555 also Sir Lanka is not too much different which records 0.2955 where Thailand is more than Sri Lanka by 0.0845 which is 0.38.
Source : constructed by authors from IMF data base.
Figure (5) Financial Market access Index
Figure (6) shows the average value of the financial institutions index and how it differs between the countries. In China, it is (0.745), India (0.345), Indonesia (0.3235), Japan (0.865), Korea (0.7835), Malaysia (0.647), Pakistan (0.2495), Philippines (0.2975), Sri Lanka (0.3065), and Thailand (0.5665).
Source : constructed by authors from IMF data base.
Figure (6) Financial Institution Index
Figure (7) shows the average values of financial institutions efficiency index for 9 Asian countries during the period 20002019. The highest average of Japan and Malaysia (0.726), and the lowest average value goes to India (0.576). Other countries average values are: Korea Republic (0.7045), Thailand (0.6885), Philippines (0.636), Indonesia (0.6455), Sri Lanka (0.6455) and China (0.6255).
Source : constructed by authors from IMF data base.
Figure (7) Financial Institution efficiency Index
Figure (8) shows the average values of financial institutions depth index for 9 Asian countries from 2000 to 2019. China has the highest value which is (0.8995) and the lowest value goes to Sri Lanka (0.111). Other countries average values are: India (0.2915), Indonesia (0.123), Japan (.6895), Korea Republic (0.7025), Malaysia (0.731), Philippines (0.141), and Thailand (0.4745).
Source : constructed by authors
Figure (8) Financial Institution depth Index
Figure (9) shows the average value of the financial institutions access index for the different countries we are studying. In China, it is (0.451), India (0.1625), Indonesia (0.2395), Japan (0.879), Korea (0.693), Malaysia (0.3305), Philippines (0.169), Sri Lanka (0.2155), and Thailand (0.4265).
Source : constructed by authors from IMF data base.
Figure (9) Financial Institution access Index
4.4. Financial development determinants (Analytical overview)
This section explains graphically the relationship between variables in the 9 Asian countries over the 2000:2019 period.
Graph (1) explains the relationship between real GDP (on the horizontal axis) and financial development index (on the vertical axis). It indicates a positive correlation between them.
Source: constructed by authors from IMF data base.
Graph (1) financial development index and real GDP
Graph (2) shows the relationship between financial development (on the vertical axis) and real interest rate (on the horizontal axis). The graph indicates the negative correlation between them.
Source : constructed by authors from IMF data base.
Graph (2) Financial development index and real interest rate
Graph (3) explains the relationship between consumer price index (on the horizontal axis) and financial development index (on the vertical axis). It indicates a negative correlation between them.
Source : constructed by authors from IMF data base.
Graph (3) Financial development index and consumer price index
Graph (4) explains the relationship between real GDP (on the horizontal axis) and financial development index (on the vertical axis). It indicates a positive correlation between them.
Source : constructed by authors from IMF data base.
Graph (4) Financial market index and real GDP
Graph (5) shows the relationship between real interest rate (on the horizontal axis) and financial market index (on the vertical axis). There is a negative correlation between them.
Source : constructed by authors from IMF data base.
Graph (5) Financial market index and real interest rate
Graph (6) explains the relationship between consumer price index (on the horizontal axis) and financial market index (on the vertical axis). It indicates a negative correlation between them.
Source : constructed by authors from IMF data base.
Graph (6) Financial market index and consumer price index
Graph (7) shows the relationship between the financial institutions index (on the vertical axis) and the real GDP (on the horizontal axis). There is a positive correlation between them.
Source : constructed by authors from IMF data base.
Graph (7) Financial institution index and real GDP
Graph (8) shows the relationship between financial institutions index (on the vertical axis) and real interest rate (on the horizontal axis). The graph indicates the negative correlation between them.
Source : constructed by authors from IMF data base.
Graph (8) Financial institution index and real interest rate
Graph (9) shows the relationship between the consumer price index (on the horizontal axis) and the financial institutions index (on the vertical axis). This graph shows a negative correlation between those two indicators.
Source : constructed by authors from IMF data base.
Graph (9) Financial institution index and consumer price index
 Methodology
Pooled OLS, Fixed effect and random effect are used to estimate the effect of sovereign credit rating on financial development.
 For pooled OLS and random effect, the following equation is used:
 For fixed effect , the following equation is used:
Where stands for the time invariant factors.
Also, Husman test is used to check for the appropriate model to estimate the effect of sovereign credit rating on financial development.
H_{0}: Random effect is consistent
 Results:
This section presents the empirical results of estimating the effect of sovereign credit rating on financial development. Table 3, 4 and 5 show the empirical results of estimating the effect of SCR on FDI, FMI and FII ,respectively, using pooled OLS. Table 6, 7 and 8 show the empirical results of estimating the effect of SCR on FDI, FMI and FII ,respectively, using fixed effect. Table 9, 10 and 11 show the empirical results of estimating the effect of SCR on FDI, FMI and FII ,respectively, using random effect.
Table (3) exhibits the OLS estimation for financial development index as dependent variable with other explanatory variables. Equation (1) explains the financial development index with explanatory variable which is countries credit rating and its estimated coefficient is 0.058 at a 1% level of significance. Also equation (2) represents the financial development index and explanatory variables are Countries credit rating, Real GDP per capita, with estimated coefficients are 0.054 at 1% level of significance and 0.0001 at 10% level of significance. Equation (3) shows the financial development index and the explanatory variables are Countries credit rating, Real GDP per capita, real interest rate , with estimated coefficients are 0.056 at 1% level of significance, 0.0001 at 5% level of significance, 0.481at 10% level of significance. Equation (4) explains the financial development index and the explanatory variables are Countries credit rating, Real GDP per capita, real interest rate and consumer price index difference with estimated coefficients are 0.052 at 1% level of significance, 0.0001 at 5% level of significance,0.283 that is insignificant after adding the fourth variable that is the Consumer price index difference and its estimated coefficient is 0.003 which is significant at 10% .
According to table (3) there is a positive relationship between the financial development index and countries credit rating, Real GDP per capita and real interest rate, in contrast there is a negative relationship between the dependent variable and consumer price index difference.
Table 3. Pooled OLS estimates
(dependent variable: Financial development index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.058***(0.002)  0.054***(0.003)  0.056***(0.003)  0.052***(0.004) 
Real_GDP_per_capita  0.0001*(0.0001)  0.0001*(0.0001)  0.0001*(0.0001)  
Real_interest_rate  0.481*(0.267)  0.283
(0.235) 

Consumer_Price_Index_Difference  0.003*(0.001)  
Constant  0.458***(0.037)  0.408***
(0.046) 
0.465***
(0.056) 
0.363***
(0.077) 
Observations  180  180  180  180 
R^{2}  0.810  0.814  0.817  0.821 
Adjusted R^{2}  0.809  0.812  0.814  0.817 
Residual Std. Error  0.093(df = 178)  0.092(df = 177)  0.092(df = 176)  0.091(df = 175) 
F Statistic  759.435***(df = 1; 178)  387.113***(df = 2; 177)  262.438***(df = 3; 176)  200.712***(df = 4; 175) 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (4) exhibits the OLS estimation for financial market index as dependent variable with other explanatory variables. Equation (1) shows the Financial Market Index as dependent variable with explanatory variable which is the countries credit ratings and estimated coefficient is 0.054 at 1% level of significance. Equation (2) explains the Financial Market Index with explanatory variables which are the countries credit ratings and Real GDP per capita with estimated coefficients are 0.056 which is significant at 1% level of significance and( 0.0001) which is insignificant Equation (3) shows the Financial Market Index with explanatory variables which are the countries credit ratings , Real GDP per capita and Real interest rate with estimated coefficients are 0.064 which is significant at 1 % level of significance ,(0.00003) which is insignificant and 1.892 which is significant at 1% level of significance. In equation (4), financial Market Index with explanatory variables which are the countries credit ratings , Real GDP per capita and Real interest rate and consumer price index difference, with estimated coefficients are : 0.060 which is significant at 1 % level of significance , (0.00003) which is insignificant, 1.734 which is significant at 1% level of significance and (0.002) and insignificant.
According to table (4), there is a positive relationship between the Countries credit rating and real interest rate with the financial market index, and a negative one with the Consumer price index difference and Real GDP per capita with the financial market.
Table 4. Pooled OLS estimates
(dependent variable: Financial market index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.054***(0.002)  0.056***(0.003)  0.064***(0.003)  0.060***(0.004) 
Real_GDP_per_capita  0.0001(0.0001)  0.00003(0.0001)  0.00003(0.0001)  
Real_interest_rate  1.892***(0.279)  1.734***(0.298)  
Consumer_Price_Index_Difference  0.002(0.001)  
Constant  0.415***(0.043)  0.445***(0.053)  0.672***(0.058)  0.590***(0.081) 
Observations  180  180  180  180 
R^{2}  0.740  0.741  0.795  0.797 
Adjusted R^{2}  0.738  0.738  0.791  0.793 
Residual Std. Error  0.107(df = 178)  0.107(df = 177)  0.096(df = 176)  0.095(df = 175) 
F Statistic  505.738***(df = 1; 178)  253.159***(df = 2; 177)  227.117***(df = 3; 176)  171.918***(df = 4; 175) 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (5) exhibits the results of OLS estimation, explaining the financial institution index as dependent variable with explanatory variables. Equation (1) explain the results of OLS estimation, explaining the financial institution index with explanatory variable which is countries credit rating with estimated coefficient is 0.062 at 1% level of significance. Equation (2) explains the financial institution index with explanatory variables which are countries credit rating, Real GDP per capita with estimated coefficients are 0.054 at 1% level of significance, 0.0003 at 1% level of significance. Equation (3) represents the financial institution index with explanatory variables which are countries credit rating, Real GDP per capita, Real interest rate and the estimated coefficients are 0.052 at 1% level of significance, 0.0003 at 1% level of significance and 0.587 at 5% level of significance. Equation (4), this equation shows the financial institution index with explanatory variables which are countries credit rating, Real GDP per capita, Real interest rate and consumer price index difference with estimated coefficients 0.048 at 1% level of significance, 0.0003 at 1% level of significance, 0.763 at 1 % level of significance and 0.002 at 10% level of significance.
According to table (5) is a positive relationship between financial institutions index and countries credit rating and real GDP per capita between financial institutions index and countries credit rating and real GDP per capita and negative relationship between the dependent variables with Real interest rate and consumer price index difference.
Table 5. Pooled OLS estimates
(dependent variable: Financial institution index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.062***
(0.002) 
0.054***
(0.003) 
0.052***
(0.003) 
0.048***
(0.003) 
Real_GDP_per_capita  0.0003***
(0.0001) 
0.0003***
(0.0001) 
0.0003***
(0.0001) 

Real_interest_rate  0.587**
(0.249) 
0.763***
(0.266) 

Consumer_Price_Index_Difference  0.002*
(0.001) 

Constant  0.539*** (0.036)  0.429***
(0.043) 
0.359***
(0.052) 
0.269***
(0.072) 
Observations  180  180  180  180 
R^{2}  0.837  0.852  0.857  0.860 
Adjusted R^{2}  0.836  0.851  0.855  0.856 
Residual Std. Error  0.091
(df = 178) 
0.087
(df = 177) 
0.086
(df = 176) 
0.085
(df = 175) 
F Statistic  910.797***
(df = 1; 178) 
511.242***
(df = 2; 177) 
351.458***
(df = 3; 176) 
267.802***
(df = 4; 175) 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (6) exhibits the results of fixed effect estimation, explaining the financial development index as dependent variable with other explanatory variables. In equation (1), the fixed effect shows the estimated coefficient of countries credit rating which is 0.006 that is insignificant. In equation (2), the fixed effect shows the estimated coefficients of countries credit rating, Real GDP per capita which is 0.004 that is insignificant and 0.001 which is significant at 1% level of significance. In equation (3), the fixed effect shows the estimated coefficients of countries credit rating, Real GDP per capita, real interest rate that are (0.016) which is significant at 1 % level of significance, 0.0005 which is significant at 1% level of significance, (1.321) which is significant at 1% level of significance. In equation (4), the fixed effect shows the estimated coefficients of countries credit rating, Real GDP per capita, real interest rate and consumer price index which are ( 0.016) which is significant at 1% level of significance, 0.0004 which is significant at 1% level of significance, (1.383) which is significant at 1% level of significance and (0.001) which is significant at 10% level of significance.
According to the table (6), there is a positive relationship between Real GDP per capita and financial development while there is a negative relationship between the financial development and countries credit rating, real interest rate and consumer price index.
Table 6. Fixed effect estimates
(dependent variable: Financial development index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.006
(0.004) 
0.004
(0.004) 
0.016***
(0.004) 
0.016***
(0.004) 
Real_GDP_per_capita  0.001***
(0.0002) 
0.0005***
(0.0002) 
0.0004***
(0.0002) 

Real_interest_rate  1.321***
(0.192) 
1.383***
(0.198) 

Consumer_Price_Index_Difference  0.001*
(0.001) 

Observations  180  180  180  180 
R^{2}  0.015  0.090  0.289  0.296 
Adjusted R^{2}  0.037  0.036  0.242  0.246 
F Statistic  2.617
(df = 1; 170) 
8.324***
(df = 2; 169) 
22.766***
(df = 3; 168) 
17.588***
(df = 4; 167) 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (7) exhibits the results of fixed effect estimation, explaining the financial market index as dependent variable with other explanatory variables. In equation (1), the fixed effect shows the estimated coefficient of countries credit rating which is (0.005) that is insignificant. In equation (2), the fixed effect shows the estimated coefficient of countries credit rating and Real GDP per capita which are (0.007) that is significant at 5% level of significance, 0.001 that is significant at 1% level of significance. In equation (3), the fixed effect shows the estimated coefficient of countries credit rating, Real GDP per capita and Real interest rate which are (0.012) that is significant at 1% level of significance, 0.001 and significant at 1% level of significance and (0.307) which is insignificant. In equation (4), the fixed effect shows the estimated coefficient of countries credit rating, Real GDP per capita and Real interest rate and consumer price index difference are (0.012) that is significant at 1% level of significance, 0.001 which is significant at 1% level of significance, (0.326) that is insignificant and (0.0004) which is significant at 10% level of significance.
According to table (7), there is a positive relationship financial market index and Real GDP per capita and negative relationship between countries credit rating, consumer price index difference and real interest rate.
Table 7. Fixed effect estimates
(dependent variable: Financial market index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.005
(0.003) 
0.007**
(0.003) 
0.012***
(0.004) 
0.012***
(0.004) 
Real_GDP_per_capita  0.001***
(0.0002) 
0.001***
(0.0002) 
0.001***
(0.0002) 

Real_interest_rate  0.307
(0.192) 
0.326
(0.198) 

Consumer_Price_Index_Difference  0.0004*
(0.001) 

Observations  180  180  180  180 
R^{2}  0.016  0.094  0.10  0.108 
Adjusted R^{2}  0.036  0.040  0.049  0.044 
F Statistic  2.730(df = 1; 170)  8.743***(df = 2; 169)  6.734***(df = 3; 168)  5.066***(df = 4; 167) 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (8) exhibits the results of fixed effect estimation, explaining the financial institution index as dependent variable with other explanatory variables. In equation (1), the fixed effect shows the estimated coefficient of countries credit rating which is 0.023 and significant at 1% level of significance. In equation (2), the fixed effect shows the estimated coefficient of countries credit rating and Real GDP per capita which are 0.020 that is significant at 1% level of significance. In equation (3), the fixed effect shows the estimated coefficient of countries credit rating, Real GDP per capita and Real interest rate which are (0.007) that is significant at 10% level of significance, 0.0004 that is significant at 1% level of significance, (1.798) which is significant at 1% level of significance. In equation (4), the fixed effect shows the estimated coefficient of countries credit rating, Real GDP per capita and Real interest rate which are (0.007) that is significant at 10% level of significance, 0.0004 that is significant at 1% level of significance, (1.873) which is significant at 1% level of significance and (0.001) that is insignificant.
According to table (6), there is a positive relationship between financial institutions index and Real GDP per capita and negative with countries credit rating, Real interest rate and Consumer price index difference
Table 8. Fixed effect estimates
(dependent variable: Financial institution index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.023***
(0.004) 
0.020***
(0.004) 
0.007*
(0.004) 
0.007*
(0.004) 
Real_GDP_per_capita  0.001***
(0.0002) 
0.0004***
(0.0001) 
0.0004***
(0.0001) 

Real_interest_rate  1.798***
(0.165) 
1.837***
(0.170) 

Consumer_Price_Index_Difference  0.001
(0.001) 

Observations  180  180  180  180 
R^{2}  0.179  0.250  0.560  0.562 
Adjusted R^{2}  0.135  0.205  0.53  0.531 
F Statistic  36.988***(df = 1; 170)  28.142***(df = 2; 169)  71.180***(df = 3; 168)  53.610***(df = 4; 167) 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (9) exhibits the results of random effect estimation, explaining the financial development index as dependent variable with other explanatory variables. Equation (1) shows the estimated coefficient of countries credit rating which is 0.027 which is significant at 1% level of significance. Equation (2) shows the estimated coefficient of countries credit rating and Real GDP per capita which are 0.017 that is significant at 1% level of significance and 0.001 which is also significant at 1% level of significance. Equation (3) shows the estimated coefficient of countries credit rating, Real GDP per capita and real interest rate which are 0.005 that os insignificant,0.001 that is significant at 1% level of significance and (0.694) which is also significant at 1% level of significance. Equation (4) shows the estimated coefficient of countries credit rating, Real GDP per capita, real interest rate which are 0.002 that is insignificant. 0.001 which is significant at 1% level of significance, (0.847) which is significant also at 1% level of significance, (0.002) which is significant at 5% level of significance.
To conclude table (9), there is a positive relationship between financial development index with countries credit rating and real GDP per capita and negative one with real interest rate and consumer price index difference.
Table 9. Random effect estimates
(dependent variable: Financial development index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.027***
(0.004) 
0.017***
(0.004) 
0.005
(0.004) 
0.002
(0.005) 
Real_GDP_per_capita  0.001***
(0.0001) 
0.001***
(0.0001) 
0.001***
(0.0001) 

Real_interest_rate  0.694***
(0.216) 
0.847***
(0.223) 

Consumer_Price_Index_Difference  0.002**
(0.001) 

Constant  0.076
(0.066) 
0.199***(0.064)  0.440***
(0.086) 
0.506***
(0.089) 
Observations  180  180  180  180 
R^{2}  0.239  0.321  0.306  0.317 
Adjusted R^{2}  0.234  0.313  0.294  0.301 
F Statistic  55.764***  83.502***  77.43***  81.171*** 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (10) exhibits the results of random effect estimation, explaining the financial market index as dependent variable with other explanatory variables. Equation (1) shows the estimated coefficient of countries credit rating which is 0.006 which is insignificant. Equation (2) shows the estimated coefficient of countries credit rating and Real GDP per capita which are 0.002 that is insignificant and 0.001 which is significant at 1% level of significance. Equation (3) shows the estimated coefficient of countries credit rating, Real GDP per capita and real interest rate which are 0.005 that is insignificant,0.001 that is significant at 1% level of significance and (0.215) which is also insignificant. Equation (4) shows the estimated coefficient of countries credit rating, Real GDP per capita, real interest rate and consumer price index difference which are 0.003 that is insignificant, 0.001 which is significant at 1% level of significance, 0.091 which is insignificant and (0.001) that is insignificant.
To conclude table (10), there is a positive relationship between financial market index with countries credit rate, Real GDP per capita and real interest rate while negative with consumer price index difference.
Table 10. Random effect estimates
(dependent variable: financial market Index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.006
(0.004) 
0.002
(0.004) 
0.005
(0.004) 
0.003
(0.005) 
Real_GDP_per_capita  0.001***
((0.0001) 
0.001***
(0.0001) 
0.001***(0.0001)  
Real_interest_rate  0.215
(0.213) 
0.091
(0.219) 

Consumer_Price_Index_Difference  0.001
(0.001) 

Constant  0.437***
(0.068) 
0.451***
(0.064) 
0.374***
(0.087) 
0.436***
(0.090) 
Observations  180  180  180  180 
R^{2}  0.014  0.143  0.156  0.149 
Adjusted R^{2}  0 0.008  0.133  0.142  0.129 
F Statistic  2.464  29.453***  32.547***  30.612*** 
Note: *p < 0.1; **p <0.05; ***p<0.01 
Table (11) exhibits the results of random effect estimation, explaining the financial institution index as dependent variable with other explanatory variables. Equation (1) shows the estimated coefficient of countries credit rating which is0.033 which is significant at 1% level of significance. Equation (2) shows the estimated coefficient of countries credit rating and Real GDP per capita which are 0.026 which is significant at 1% level of significance and 0.001 also significant at 1% level. Equation (3) shows the estimated coefficient of countries credit rating, Real GDP per capita and real interest rate which are 0.007 which is significant at 10% level, 0.001 significant at 1% level and (1.391) which is significant at 1% level of significance. Equation (4) shows the estimated coefficient of countries credit rating, Real GDP per capita, real interest rate and consumer price index difference which are 0.005 that is insignificant, 0.001 significant at 1% level, (1.492) significant at 1% level and (0.001) insignificant.
Table 11. Random effect estimates
(dependent variable: Financial institution Index) 

Eq (1)  Eq (2)  Eq (3)  Eq (4)  
Countries_credit_Rating  0.033***
(0.004) 
0.026***
(0.003) 
0.007*
(0.004) 
0.005
(0.004) 
Real_GDP_per_capita  0.001***
(0.0001) 
0.001***
(0.0001) 
0.001***
(0.0001) 

Real_interest_rate  1.391***
(0.180) 
1.492***
(0.186) 

Consumer_Price_Index_Difference  0.001
(0.001) 

Constant  0.038
(0.065) 
0.034
(0.062) 
0.437***
(0.075) 
0.482***
(0.077) 
Observations  180  180  180  180 
R^{2}  0.333  0.409  0.544  0.549 
Adjusted R^{2}  0.329  0.402  0.536  0.538 
F Statistic  88.896***  122.459***  209.779***  212.663*** 
Note: *p < 0.1; **p <0.05; ***p<0.01 
To conclude table (11), there is a positive relationship between financial institution index with countries credit rating and real GDP per capita while negative with consumer price index difference and real interest rate.
 Conclusion:
In our study, we attempted to analyze the nexus between sovereign credit rating and financial market in 9 Asian countries during the period 2000:2019. We use the countries’ sovereign credit ratings by Fitch ratings, the financial market index, financial institution index, and financial development index as indicators for financial markets. The analysis was based on ordinary least square, two stage least squares, random and fixed effect methods. The estimation of financial development index equation indicates that the sovereign credit rating is positively related to financial market.
The Results of Husman test find that:
 For financial development index, p less than 0.1 ,so fixed effect is more appropriate than random effect.
 For financial market index, p less than 0.1 ,so fixed effect is more appropriate than random effect.
 For financial institution index, p more than 0.1 ,so random effect is more appropriate than fixed effect.
The study has some limitations firstly, is that analysis clarified CPI as a proxy of inflation rate negatively related to financial development index lastly, the analysis of sovereign credit ratings based on Fitch ratings only not the other ratings of S&P’S and Moody’3s which would make the findings more accurate.
The empirical results of study show the positive relationship between the financial development index and countries credit rating, real GDP per capita and real interest rate in contrast there is a negative relationship between financial development index and consumer price index difference.
In this paper, we present a study during recently period coping with the world updates, and for the future research we recommend not to use consumer price index as a proxy of inflation rate as it makes the results not accurate and we recommend to use all data of sovereign credit ratings for countries from Fitch, of S&P’S and Moody’s if the data available.
This study provides better understand of the relationship between sovereign credit rating and financial market. the random and fixed effect methods did not clarify the relationship and our contribution for the future research to use the two stage least squares method to analyze variables data.
This study prove that sovereign credit rating announcements bring uncertainty to the financial markets, particularly in case of downgrade announcements so, policy makers must cautiously improve the factors that affect sovereign credit rating as GDF growth of a country. strong GDP growth means that a country will be able to meet its debt obligations since the growth in GDP results in higher tax revenues for the government.
Inflation rate affects the ability of country to finance its debt and that affect sovereign credit ratings so, policy makers must control inflation rate and the decisions that affect inflation rate of the country.
External debt, increasing debt levels translate to a higher risk of default which negatively affect sovereign credit ratings.
 Recommendation:
 Precisely observing the movements of sovereign credit ratings since it has a crucial rule in the economic risk management in any country. Moreover, monitoring credit ratings has a tremendous impact on financial market stability.
 Providing experts to monitor the developments of the credit ratings and be able to forecast the potential effects of that change and make outlook announcements for the economy.
 Studies should be conducted for the other markets because any change in the credit rating for those countries may be contagious for the surrounding economies and even more it can turn into a global financial crisis.
 sufficient awareness about the swings of the credit ratings must exist since under certain circumstances, especially in economic panic, it can aggravate the downward spiral of the economic crisis.
 Preventive measures have to be taken whenever a downgrade happens and immediate communicate between the decision makers has to be made to dissipate the concerns regarding to the weaknesses that are noticed by the market participants.
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 Rafay, A., Chen, Y., Naeem, M. A., & Ijaz, M. (2018). Analyzing the impact of credit ratings on firm performance and stock returns: An evidence from Taiwan. Iranian Economic Review, 22(3), pp. 767786, Available at: https://ssrn.com/abstract=3258268.
 World development indicators (no date) DataBank. Available at: https://databank.worldbank.org/source/worlddevelopmentindicators(Accessed: 30 May 2023).
 Appendix
Appendix 1:
List of countries in the study
Japan  Korea  Indonesia 
China  Malaysia  Thailand 
India  Philippines  Sri Lanka 
Appendix 2:
In appendix 2, all literature reviews of this study are existed with presenting its objective, data and results.
Study  Objective  Data  Results 
1)Sovereign Rating News and Financial Markets Spillovers: Evidence from the European Debt Crisis
Rachel Christoph er ,Suk Joon Kim and Eliza Wu. (2012) 
1How do sovereign ratings affect an emerging country’s stock and bond market in both the short and longterm?
2It conducts various analyses to measure the impact of sovereign ratings on an emerging market’s: 1) stock market co movement with its corresponding regional stock market index, and 2) bond market co movement with its corresponding regional bond market index. 
Y Dynamic Conditional Correlations for stock and bond markets estimated separately
X1 The foreign currency and local currency sovereign credit ratings X2 The foreign currency and local currency sovereign credit outlooks X3 Exchange rate volatility X4 CBOE’s Volatility Index (VIX) 
1It finds sovereign credit ratings have greater economic significance for debt than stock markets.
2The longrun coefficients on ratings and outlooks are mostly significant and negative. 3It finds that the countries that have ratings higher than their regional average rating tend to have a negative ratings coefficient 4It finds that bond markets experience negative regional rating spillover effects and the financial impacts are on a larger scale since sovereign ratings/outlooks are designed as credit assessments specifically for debt markets 
2)Sovereign Rating News and Financial Markets Spillovers: Evidence from the European Debt Crisis
Arezki, Rabah; Candelon , Bertrand; Sy, Amadou (2011) 
1This paper examines the spillover effects of sovereign rating news on European financial markets during the period 20072010.
2Whether sovereign rating news, such as downgrades , have spillover effects both across countries and markets in a financially integrated environment such as Europe. 
Y The return on market
X1 Rating announcements (Rating news). X2 Ndimensional vector of asset prices (taken in logarithm). 
1It finds that sovereign rating downgrades have statistically and economically significant spillover effects both across countries and financial markets..
2 Those spillover effects depend both on the type of rating announcements, on the source country experiencing the downgrade and the rating agency from which the announcements originates from. 3 Sovereign rating downgrades not only impact the financial markets in country subject to the rating announcement but also in other Euro zone countries implying that rating agencies announcements could spur financial instability. 4 Banking linkages between countries play a key role in the transmission channels of sovereign news. 
3)Equity and debt market responses to sovereign credit ratings announcements
Kuntara Pukthuan thongLe ,Fayez A. Elayan men Lawrence C. Rose. (2007) 
We study the impact of changes in sovereign ratings and outlooks on international capital markets  Y CAAR is cumulative abnormal returns of both bond and stock markets of country.
X1 Economic DevelopmenX2 Inflation, X3 Current Account X4 Fiscal Balance X5 Currency, common law X6 Crisis X7 Liquidity X8 Change in outlook upgrade and downgrade X9 Rating Change across Class X10 Size of Rating Change. 
1 It find rating agencies do provide financial markets with new tradable information and changes in ratings and outlook significantly affect both the bond and stock markets.
2 Only bond market reacts positively and significantly when economic outlook is upgraded. 3 The impact of outlook changes is larger than the impact of rating changes only for bond markets, suggesting investors most likely anticipate the later rating change from the outlook. 4 The cumulative abnormal bond return during 45 days before 2 days after the announcement date is negatively significant when the rating is downgraded and it is negatively (positively) significant when the economic outlook is downgraded (upgraded). 5Upgrade rating events have no discernible impact on both bond and stock return,but downgrade has a significant negative impact on bond and stock returns countries with less development and high inflation. 
4)Determinants and Impact of Sovereign Credit Ratings
Richard Cantor and Frank Packer. (1996) 
1Measure whether rating announcements directly affect market yields on the day of the announcement.
2How much of an impact do ratings have on borrowing costs for sovereigns? 3The impact of rating announcement on doller bond spreads. 
Y Sovereign credit rating
Xs Income per capita, GDP growth, Inflation, Fiscal Balance, External Balance. 
1A high per capita income appears to be closely related to high ratings
2 Lower inflation and lower external debt are also consistently related to higher ratings. 3Contrary to our expectations, the impact of one agency’s announcement is greater if the announcement confirms the other agency’s rating or a previous rating announcement. 4Of the individual coefficients, per capita income, GDP growth, inflation, external debt, and the indicator variables for economic development and default history all have the anticipated signs and are statistically significant. The coefficients on both the fiscal and external balances are statistically insignificant and of the unexpected sign. 5the impact of rating announcements on dollar bond spreads is highly significant. 
5)Sovereign credit ratings, capital flows and financial sector development in Emerging markets.
Suk Joong Kim, Eliza Wu. (2008) 
It explains “How does the sovereign credit ratings history provided by independent ratings agencies affect domestic financial sector development and international capital inflows to emerging countries?”  Y FINDEV are the three financial market development measures for country i and year t.
X1 FINDEV for the last year X2 Foreign currency ratings for long term sovereign debt issues (FCLT). X3 Foreign currency rating shortterm sovereign debt issues (FCST). X4 Local currency sovereign debt for long term (LCLT) . X5 Local currency sovereign debt for long term (LCST). 
1 The results suggest that the sovereign credit ratings
2 Foreign currency long term ratings show expected positive influence in general, and it is statistically significant for bond market developments. 3 Financial development is significantly related to the behavior of the second moments of stock return distributions. 4 private bond sector is the most sensitive to sovereign credit ratings and its development can be hampered by all types of sovereign credit ratings except longterm foreign currency ones. 5 Longterm foreign currency ratings have the expected positive influences on all three types of capital inflows. 6 Trade openness is significantly related to capital flows. However, it only promotes FDI, not bank flows. Interestingly, all three forms of portfolio flows show negative associations. 7 We also find that financial market development (proxies by SMCAP) has a significant positive effect on portfolio equity flows. 
6) Emerging Markets Instability:
Do Sovereign Ratings Affect Country Risk and Stock Returns? Kaminsky, Schmukler (2001) world bank 
This paper examines whether sovereign ratings affect financial markets. And complements the previous research on rating agencies by also examining these possible crosscountry and securitymarket spillovereffects of rating changes. It also contributes to the literature on contagion and international transmission of shocks by examining the effect of domestic vulnerability, as measured by the rating  EMBI spreads, stock returns, interest rates, and credit ratings  1) The coefficient for the lag dependent variable is positive and statistically significant.
2) The coefficient for the changes in ratings (domestic and foreign) is negative and statistically significant 3) bond spreads increase up to 9 percent in the 10days prior to downgrades. Similarly, the stock market spreads decline up to 7 percent 
7) “Do Credit Rating Agencies Add to the Dynamics of Emerging Market Crises?”
Kräussl (2003) 
This study analyses the specific experience with sovereign credit ratings for emerging markets in the second half of the 1990s  Data set consists of daily sovereign credit ratings of longterm foreign currency debt
daily nominal exchange rates, shortterm interest rates and stock market price indexes 
1) a sovereign credit rating event moves the index of financial market pressure only by 1.3 percent
2) Adding the significant response of the SMP during the ten days after the sovereign credit rating modification, the cumulative movement of the speculative market pressure index is as high as 4.4 percent. 3) the index of speculative market pressure rises in the case of sovereign, credit rating downgrades by accumulated 7.5 
8) G. Ferri, L.G. Liu and J. E. Stiglitz (1999)  Propose an endogenous rationale for rating agencies to become excessively conservative after having made blatant errors in predicting the East Asian crisis  Shortterm debt GDP per capita Real GDP growth Inflation rate Budget deficit Current account balances
External debt 
1 In linear: most of the explanatory variables are still statistically significant, with the exception of GDP per capita and the inflation rate. the shortterm debt measure is negatively and significantly correlated with sovereign ratings
2 In nonlinear: for two of the explanatory variables. Though it is not statistically significant, the sign of GDP per capita changes to negative in both the pre and postcrisis models. Budget deficit, though still negatively correlated with ratings, is no longer significant. 3 R2 for pre and postcrisis models have dropped from 0.30 and 0.33 to 0.22 and 0.25 
9) Emerging market risk and sovereign credit rating
Larraín, Reisen, Maltzan(1997) 
Our paper aims at broader empirical content for judging whether the two leading rating agencies lead or lag market events with respect to sovereign risk  Ratings of sovereign foreign currency debt fixedrate dollar bond  The results show a twoway causality between ratings and yield spreads and reject Granger Causality of both ratings and yield spreads. reject the hypothesis β = 0, equation (2.2) rejects the hypothesis γ = 0. This result means that ratings cause yield spreads and vice versa. 
10) Stijn Claessens, Andy Law and Teng Wang
(September 2018) How do credit ratings affect bank lending under capital constraints? 
How banks determine loan terms under capital constraints. Using a unique and comprehensive supervisory dataset of individual corporate loans in the US, Credit ratings are a critical tool for banks to assess the default risk of their corporate borrowers  Independent variable is credit rating Dependent variable is loans  Rating changes in banks’ portfolios can directly affect loan terms by changing the size of capital buffers banks are required to hold. 
11) Pilar Abad, Antonio Diaz, Ana Escribano, and M. Dolores Robles(2016)
The Effects of Credit Rating Announcements on Bond Liquidity 
This paper investigates liquidity shocks on the US corporate bond market around credit rating change announcements. These shocks may be induced by the information content of the announcement itself, and abnormal trading activity can be triggered by the release of information after any upgrade or downgrade.  Independent variable is Credit rating Dependent variables are Price and market share  Its results indicate shocks in liquidity around downgrades with three clear patterns: before, immediately after, and during 1 month after the announcement. First, liquidity proxies before downgrades suggest that the market anticipates the deterioration of credit quality. Second, there is price pressure and abnormally high trading volumes during the first days after the downgrades. Third, prices converge to a stable level, with lowimpact price liquidity and normal levels of trading activity, during the second fortnight. To conclude, the crosssectional analyses show different variables that may affect abnormal liquidity levels. 
12) Chunling Li1, Khansa Pervaiz1, Muhammad Asif Khan, Muhammad Atif Khan2, and Judit Oláh(2022) (Impact of Sovereign Credit Rating Disclosure on Chinese Financial Market)  The impact of the sovereign credit rating (SCR) on the financial market development (FMD) of China  Our dependent variable FMD is a composite index of financial market depth, access, and efficiency. the SCR is the independent variable (Sovereign Credit Rating)  The NARDL results demonstrate an asymmetric impact of SCR variations on FMD in both the short run and long run. Under NARDL specification, the results vary across the SCR measurement. It signifies that stakeholders like analysts, investors and regulators may consider these asymmetries in the nexuses between SCR and FMD while interpreting the sovereign rating announcements, as these may not carry uniform implications. Moreover, the current study is subject to several limitations. 
13) Abdul Rafay, Yang Chen , Muhammad A.B.Naeem , Maham Ijaz(2017), Analyzing the Impact of Credit Ratings on Firm Performance and Stock Returns: An Evidence from Taiwan  The study covers three aspects; factors determining credit ratings, impact of credit ratings on performance of entities and the relationship between stock returns and credit ratings. The study focuses on the firms listed in Taiwan Stock Exchange (TSE) of Taiwan.  The independent variables are all firm specific variables. The dependent variable is credit rating(Entity size, Leverage, Liquidity, Return on asset, Dividend per share, Tobin’s Q, Capital Unburden, Loss Propensity, Industry Type, Stock Price, Stock Returns)  The results show that there are total 294 observations of the underlying study. The average firm size identifies the strong ability to offset the default risk, as these large firms attain from economies of scale. Average liquidity denotes that all the companies included in the sample are able to pay their debts somehow. Average leverage states that Taiwanese companies depend slightly higher on debt as compared to equity. 
14) Tracy Li and Victoria Zhang,(2017) The impact of credit rating change on North American companies’ corporate decision and stock performance  Firstly, credit rating will impact company capital structure decisions. Secondly, there is an offset pattern in daily abnormal returns and volatility of stock returns increases after a credit rating change event. Specifically, downgrade has a bigger impact on stock performance.  Independent var.credit rating
Dependent var. expected market return 
After determining cumulative abnormal returns for each company, it is necessary to test if they are statistically significant we also analysis the effects of credit rating change on companies’ stock performance. Through an event study, we reach the conclusion that credit rating change will increase return volatility. 
15) Sovereign credir ratings and Asian financial market
Hansa Pervaiz1, Zuzana Virglerová 2, Muhamma d Asif Khan3 , Usman Akbar4 , József Popp5 (2021)

investigates the impact of Sovereign credit ratings announcements on the financial market development of 24 Asian economies/territorie s (selected subject to data availability) from 1990 to 2018

Dependent variable: financial market development index Independent variables: Sovereign credit rating
SCR grades are obtained from Standard and Poor’s (SCRS) and Moody’s (SCRM) economic growth trade openness inflation banking development investment 
According to the results, financial market development index has a statistically significant relationship with the sovereign credit ratings of Asian economies. SCRS positively explains the FD_FM and its three components (access, depth, and efficiency). One standard deviation positive change in SCRS brings about 0.52 standard deviation. In contrast, the same change in SCRS translates 0.42, 0.84, 0.76 standard deviation improvement in financial market access, depth, and efficiency, respective 
16) The Use of Credit Ratings in Financial Markets
Ramin P. Baghai, Bo Becker, And Stefan Pitschner. (August 2020) 
Classify fixed income funds’ mandate contents.  dummy variables
NRSRO, Big 3, and All ratings references. S&P Moody’s Fitch is a vector of fund fixed effects and denotes the dependent variables The coefficient β captures trends in rating references by fixed income funds 
1 It find that the trend in ratings use has been positive both in the pre as well as in the postcrisis period
2 The coefficients on the pre and postcrisis trend variables are not statistically different from each other 3 It find that more than 90% of the new funds make a direct or indirect credit ratings reference in their investment mandates. 
17) Rating agencies’ signals during the European sovereign debt crisis: Market impact and spillovers
Rasha Alsakka∗, Owain ap Gwilym (2011) 
Identify whether sovereign credit signals released by a particular CRA have a stronger influence on the market during the crisis than the signals of other CRAs.
– analyzing whether any influence on the market is related to a specific type of credit signal (positive versus negative events, and actual rating changes versus outlook actions versus watch signals). 
Y The change in the natural logarithm of the exchange rate of sovereign
X1 The 1day change in the legittype transformation of the 58point rating. X2 Negative credit signals. X3 The level of event country. 
1 CRA news has a significant and immediate impact on exchange rates in the ‘EU–CA’ region, but the impact of outlook and watch signals is stronger than the impact of rating changes. The effect is stronger in the 2006– 2010 crisis period.
2 CRA news for country i significantly and immediately affects other currencies in the ‘EU– CA’ region, and the effect is stronger in the 2006–2010 crisis period.14 The spillover effects from outlook and watch signals are stronger than from rating changes. 
18) Sovereign credit ratings, market volatility, and financial gains
António Afonso, Pedro Gomes and Abderrahi m Taamouti (March 2014) 
1 Study the volatility of stock market and sovereign bond market returns in EU countries, notably before and during the 2008 2009 economic and financial crisis.
2 Analyse whether countries with higher credit ratings exhibit less volatility than lower rating countries. 3 Valuate the economic significance of the impact of rating announcements on volatility, by quantifying the financial gain and the risk reduction of a portfolio of stocks or bonds that consider this information 
Y j,t: the volatility of returns.
X1 downj,t : the downgrade of any agency. X2 upj,t: the upgrade of any agency. 
1 Sovereign rating changes have asymmetric effects on both equity and bond volatilities.
2 Upgrades do not have any significant effect on volatility, but sovereign downgrades. 3 Downgrade increases the volatility of all other countries, specifically in the other countries. 
19) Impact of Sovereign Credit
Rating Changes on Stock Market Co Movements, In Case Of ASEAN and Southern Asia’s Markets Rabia Nawaz (2018) 
This study investigates the impact of sovereign credit rating announcements on timevarying stock market correlations for a sample of five ASEAN and four South ern Asia’s markets spanning.  Y Dynamic conditional correlation between stock indices re turns of country ‘i’ and ‘j’
X1 Effect of Rating changes actions of each sovereign at time ‘t’. X2 Measuring impulse effect sovereign rating in country ‘i’ and ‘j’. 
1 There is a significant spillover impact of sovereign credit rating news on stock markets.
2 In conclusive opinion, this empirical analysis proposes a significant impact of sovereign creditrating changes on pairwise cross market correlations between the ASEAN markets around the announcement dates. 3 Sovereign credit rating changes have a significant impact on cross country stock markets co movement. 
20) European Capital Markets Institute
Prabesh Luitel and Rosanne Vanpée (2018) 
1 Investigate the transmission channels through which a sovereign credit rating impacts a country’s domestic and international financial development.
2 Make a distinction between the domestic financial sector and a country’s integration in the international financial markets. 
Y Financial development
X1 The average treatment effect on the treated X2 Dummy that is equal to unity if country i is in the treatment group and zero otherwise is the matrix of J exogenous pretreatment variables 
1 When a country obtains a sovereign credit rating, the proportion of foreign currency bond issues increases significantly
2 The impact of a credit rating on the size of mediumterm foreign currency bond issues is not significant. 3 Rated countries issue smaller bond issues than unrated countries, especially when the bonds are issued in local currency sovereign credit rating provision has a significantly positive effect on both direct inward FDI and portfolio investment 
21) Stock Market Reactions to Sovereign Credit Rating Changes: Evidence From Four European Countries
Ibrahim Fatnassi (2014) 
Examine empirical evidence on the effect of sovereign credit rating changes by international credit rating agencies on the stock markets of the most volatile European countries (Greece, Portugal, Spain, and Italy) during the period from June 2008 to June 2012. More specifically, our objective is to determine whether rating changes in individual countries affect ownstock market returns as well as those of other neighbouring countries, thereby transmitting the crisis to those countries  Y The stock market return in country at time and that in the United States (US) at time.
X1 Upgrades in the own country. X2 Downgrades in the own country. X3 Upgrades in foreign countries. X4 Downgrades in foreign countries 
1 There is evidence that sovereign debt rating change announcements affect stock markets. The autoregressive term coefficients, α, are negative and statistically significant, indicating a negative auto correlation of stock returns.
2 The coefficients on changes in US stock returns are all positive and significant, providing evidence that the US market has a strong impact. 3 Negative rating events impact owncountry equity returns and cause significant spillovers to the equity markets of other countries. 4 Upgrades have limited or insignificant impact 5 Sovereign credit signals do have an impact on stock market returns, although there are differing reactions to news from the rating agencies. 
22) SOVEREIGN CREDIT RATINGS AND ASIAN FINANCIAL MARKETS
Khansa Pervaiz, Zuzana Virglerová, Muhammad Asif Khan, Usman Akbar, József Popp Year: 2021 
The study investigates the impact of SCR announcements on the financial market development of 24 Asian economies/territories (selected subject to data availability) from 1990 to 2018.  Y Financial market development index
X1 SCR X2 Economic growth (E.G.) X3 Trade Openness (TRO) X4 Inflation (INF) X5 Banking development (D.C.) X6 Investment 
The findings of Driscoll Kraay’s robust estimator reveals that improvement in sovereign credit rating score enhances the financial market development in the region. positive impact of sovereign credit ratings on financial market development in the region is robust. 
23) On the asymmetries of sovereign credit rating announcements and financial market development in the European region. Chunling Li
, Khansa Pervaiz , Muhammad Asif Khan , Faheem Ur Rehman 3 and Judit Oláh 4 2019 
The study attempted to empirically test the linear and nonlinear impacts of CR on financial market development (FMD) in the European region.  Y Financial market development index
X1 Credit rating are obtained from Standard and Poor’s (SCRS) and Moody’s (SCRM) X2 Economic growth X3 Inflation X4 Investment 
1Significant and negative coefficients of the error correction term (ECT) in all four models estimated clearly demonstrates that CR comoves with FMD in the long run in the European region.
2 Under both outlooks provided by Standard and Poor’s and Moody’s, the FMD reacts differently in the region, which may be due to the CR assessment differences in both outlooks. In the short run, the results do not confirm a not significant change in FMD; however, in the long run, the CR_M impact is significant. Likewise, a 3 positive change in both CR_S and CR_M brings a negative change in FMD over the long run 
Appendix 3:
This appendix section contains results of Rstudio for The empirical study of this study.
Table (12)
Pooled OLS estimates for financial development index
Source : constructed and estimated by authors from Rstudio.
Table (13)
Pooled OLS estimates for financial market index
Source : constructed and estimated by authors from Rstudio.
Table (14)
Pooled OLS estimates for financial institution index
Source : constructed and estimated by authors from Rstudio.
Table (15)
Fixed effect estimates for financial development index
Source : constructed and estimated by authors from Rstudio.
Table (16)
Fixed effect estimates for financial market index
Source : constructed and estimated by authors from Rstudio.
Table (17)
Fixed effect estimates for financial institution index
Source : constructed and estimated by authors from Rstudio
Table (18)
Random effect estimates for financial development index
Source : constructed and estimated by authors from Rstudio
Table (19)
Random effect estimates for financial market index
Source : constructed and estimated by authors from Rstudio
Table (20)
Random effect estimates for financial institution index
Source : constructed and estimated by authors from Rstudio
Husman test for financial development index
Source : constructed and estimated by authors from Rstudio
Husman test for financial market index
Source : constructed and estimated by authors from Rstudio
Husman test for financial institution index
Source : constructed and estimated by authors from Rstudio
Appendix 4:
Contents  Amira  Donia  Roaa  Reham  Mostafa  Date 
Abstract  /  
Introduction  /  /  3/12/2022  
Research problem  /  6/12/2022  
Research importance  /  6/12/2022  
Research objectives  /  8/12/2022  
Research hypothesis  /  8/12/2022  
Limitations  /  8/12/2022  
Literature Reviews  /  /  /  /  /  20/12/2022 
Theoretical Framework  /  /  /  /  /  1/3/2023 
Data and Methodology  /  /  /  /  /  15/1/2022 
Results  /  /  /  /  /  5/4/2022 
Conculsion  /  13/4/2022  
Recommendations  /  1/5/2023  
References  /  /  /  /  /  5/5/2023 
Appendix  /  /  /  /  /  15/5/2023 
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