This paper uses the theory of behavioral finance to examine the factors of individual investors’ psychology as well as their effects on investment decisions in the Vietnam Stock Exchange (VSE). This is an empirical study which based on a survey of 422 investors. All of them have had the deep knowledge about finance investment and worked many years in VSE. The final results show that five factors of psychology which are overconfidence, optimism, herd behavior, psychology of risk and pessimistic have influence on investment decisions. To be more detailed, excessive optimism, psychology of risk and excessive pessimistic affect positively on long-term investment of investors while overconfidence and herd behavior have the negative impact. Based on the theory of behavioral finance, this study explains factors of individual investors’ psychology. However, one of the limited of this paper is that it does not mention about negative outcomes of psychology factors on investment decisions. This is considered as a new path to do research in the future for emerging markets like Vietnam.
Macroeconomic and Institutional Determinants of Capital Market Performance in...Fakir Tajul Islam
This paper examines the institutional and macroeconomic
determinants of stock market performance using data in the last 20 years starting from 1995 to 2015. In this
paper, Gross Domestic Product (GDP), Consumer Price Index (CPI), inflation rate and Foreign Direct Investment
(FDI) inflows were used as the proxy of macroeconomic determinants, whereas market capitalization, total
issued capital and market turnover of Dhaka Stock Exchange were the proxy of institutional determinants of
capital market performance.
This paper uses the theory of behavioral finance to examine the factors of individual investors’ psychology as well as their effects on investment decisions in the Vietnam Stock Exchange (VSE). This is an empirical study which based on a survey of 422 investors. All of them have had the deep knowledge about finance investment and worked many years in VSE. The final results show that five factors of psychology which are overconfidence, optimism, herd behavior, psychology of risk and pessimistic have influence on investment decisions. To be more detailed, excessive optimism, psychology of risk and excessive pessimistic affect positively on long-term investment of investors while overconfidence and herd behavior have the negative impact. Based on the theory of behavioral finance, this study explains factors of individual investors’ psychology. However, one of the limited of this paper is that it does not mention about negative outcomes of psychology factors on investment decisions. This is considered as a new path to do research in the future for emerging markets like Vietnam.
Macroeconomic and Institutional Determinants of Capital Market Performance in...Fakir Tajul Islam
This paper examines the institutional and macroeconomic
determinants of stock market performance using data in the last 20 years starting from 1995 to 2015. In this
paper, Gross Domestic Product (GDP), Consumer Price Index (CPI), inflation rate and Foreign Direct Investment
(FDI) inflows were used as the proxy of macroeconomic determinants, whereas market capitalization, total
issued capital and market turnover of Dhaka Stock Exchange were the proxy of institutional determinants of
capital market performance.
Macroeconomic Variables on Stock Market Interactions: The Indian ExperienceIOSR Journals
To examine the effect of macroeconomic variables on the stock price movement in Indian Stock Market. Six variables of macro-economy (inflation, exchange rate, Industrial production, MoneySupply, Goldprice, interest rate) are used as independent variables. Sensex, Nifty and BSE 100are indicated as dependent variable. The monthly time series data are gathered from RBI handbook over the period of April 2008 to June 2012. Multiple regression analysis is applied in this paper to construct a quantitative model showing the relationship between macroeconomics and stock price. The result of this paper indicates that significant relationship is occurred between macroeconomics variable’s and stock price in India.
The Effects of Macroeconomic Variables on Stock Returns in the Jordanian Stoc...Premier Publishers
This study investigated the effects of six macroeconomic variables on the stock returns in the Jordanian financial market between 1976 and 2016 using annual data. The study used the stock return data for 218 companies listed on the market and the quarterly data of the six macroeconomic variables (Industrial production, interest rates, money supply, inflation, GDP, import prices). Autoregressive Distributed Lag (ARDL) model was employed for the estimations. The reason to test these models in the Jordanian stock market was motivated by the fact that the returns of shares in the Arab markets in general do not follow the normal distribution. The results of the estimated ARDL model revealed that the industrial production has a statistically significant effect on the returns of shares at a significant level of 1 percent, and in line with the hypothesis of the study because the relationship was positive. The effect of the money supply on the stock returns is statistically significant, (positive impact of money supply on stock returns), while the impact of import prices was negative and statistically significant on the stock returns. This work has found that it is imperative to search for new markets for the disposal of Jordanian products, and not rely on traditional markets only such as Gulf markets, the Iraqi market, this requires policies to strengthen and support the role of local industries, to develop global quality requirements, and to develop preferential features for products to be compared with those in other foreign markets.
American Journal of Multidisciplinary Research and Development is indexed, refereed and peer-reviewed journal, which is designed to publish research articles.
Shahid, M., & Kamran, F. (2015). Causal Relationship between Macroeconomic Factors and Stock Prices in Pakistan. International Journal Of Management And Commerce Innovations, 3(2), 172-178. Retrieved from http://researchpublish.com/journal/IJMCI/Issue-2-October-2015-March-2016/0
To develop the candidate understands and ability to apply, analyzes, and interprets the fundamental principles of economics in relation to the business environment both in the domestic and global economies.
Developing economies are different than developed economies in many aspects, i.e., in terms of institutional framework and political situation etc. Thus, the monetary policy needed in developing countries is also different than developed countries. The goal of this study is to investigate exchange rate channel of monetary transmission mechanism in a developing country’s setup. The variables included in our analysis are interest rate, exchange rate, exports, consumer price index and gross domestic product. Johansen cointegration technique is applied to analyze the long run relationship among variables while multivariate VECM granger causality test is used to explore the direction of causality among the set of our variables. We use annual data ranging from 1980 to 2015 while taking account of the limitations of time series data. Our findings suggest that output has a negative long run relationship with exchange rate and interest rate, positive relationship with exports and no statistically significant relationship with inflation. Interest rate granger causes all four of our variables thus showing the power of this policy tool. Exchange rate causes exports, consumer price index and output which means exchange rate is the second most powerful variable in our analysis. Output is granger caused by interest rate, exports and exchange rate which confirms the sensitivity of output to these variables. Consumer price index is granger caused by all four of our variables and came out to be the most sensitive variable in our analysis.
American Journal of Multidisciplinary Research and Development is indexed, refereed and peer-reviewed journal, which is designed to publish research articles.
Macroeconomic Variables on Stock Market Interactions: The Indian ExperienceIOSR Journals
To examine the effect of macroeconomic variables on the stock price movement in Indian Stock Market. Six variables of macro-economy (inflation, exchange rate, Industrial production, MoneySupply, Goldprice, interest rate) are used as independent variables. Sensex, Nifty and BSE 100are indicated as dependent variable. The monthly time series data are gathered from RBI handbook over the period of April 2008 to June 2012. Multiple regression analysis is applied in this paper to construct a quantitative model showing the relationship between macroeconomics and stock price. The result of this paper indicates that significant relationship is occurred between macroeconomics variable’s and stock price in India.
The Effects of Macroeconomic Variables on Stock Returns in the Jordanian Stoc...Premier Publishers
This study investigated the effects of six macroeconomic variables on the stock returns in the Jordanian financial market between 1976 and 2016 using annual data. The study used the stock return data for 218 companies listed on the market and the quarterly data of the six macroeconomic variables (Industrial production, interest rates, money supply, inflation, GDP, import prices). Autoregressive Distributed Lag (ARDL) model was employed for the estimations. The reason to test these models in the Jordanian stock market was motivated by the fact that the returns of shares in the Arab markets in general do not follow the normal distribution. The results of the estimated ARDL model revealed that the industrial production has a statistically significant effect on the returns of shares at a significant level of 1 percent, and in line with the hypothesis of the study because the relationship was positive. The effect of the money supply on the stock returns is statistically significant, (positive impact of money supply on stock returns), while the impact of import prices was negative and statistically significant on the stock returns. This work has found that it is imperative to search for new markets for the disposal of Jordanian products, and not rely on traditional markets only such as Gulf markets, the Iraqi market, this requires policies to strengthen and support the role of local industries, to develop global quality requirements, and to develop preferential features for products to be compared with those in other foreign markets.
American Journal of Multidisciplinary Research and Development is indexed, refereed and peer-reviewed journal, which is designed to publish research articles.
Shahid, M., & Kamran, F. (2015). Causal Relationship between Macroeconomic Factors and Stock Prices in Pakistan. International Journal Of Management And Commerce Innovations, 3(2), 172-178. Retrieved from http://researchpublish.com/journal/IJMCI/Issue-2-October-2015-March-2016/0
To develop the candidate understands and ability to apply, analyzes, and interprets the fundamental principles of economics in relation to the business environment both in the domestic and global economies.
Developing economies are different than developed economies in many aspects, i.e., in terms of institutional framework and political situation etc. Thus, the monetary policy needed in developing countries is also different than developed countries. The goal of this study is to investigate exchange rate channel of monetary transmission mechanism in a developing country’s setup. The variables included in our analysis are interest rate, exchange rate, exports, consumer price index and gross domestic product. Johansen cointegration technique is applied to analyze the long run relationship among variables while multivariate VECM granger causality test is used to explore the direction of causality among the set of our variables. We use annual data ranging from 1980 to 2015 while taking account of the limitations of time series data. Our findings suggest that output has a negative long run relationship with exchange rate and interest rate, positive relationship with exports and no statistically significant relationship with inflation. Interest rate granger causes all four of our variables thus showing the power of this policy tool. Exchange rate causes exports, consumer price index and output which means exchange rate is the second most powerful variable in our analysis. Output is granger caused by interest rate, exports and exchange rate which confirms the sensitivity of output to these variables. Consumer price index is granger caused by all four of our variables and came out to be the most sensitive variable in our analysis.
American Journal of Multidisciplinary Research and Development is indexed, refereed and peer-reviewed journal, which is designed to publish research articles.
Running head: NOMINAL AND REAL EXCHANGE FLUCTUATIONS 1
NOMINAL AND REAL EXCHANGE FLUCTUATIONS 2
Causes of nominal and real exchange rate fluctuations, misalignments and the exchange rate policy
Student`s Name
Instructor
Institution
Course
Date
Fluctuations in Nominal Exchange Rate Comment by Microsoft: Can add introduction part: for example, “In 2008, both the international financial market and the global economy were turbulent due to the financial and economic crisis. This crisis has caused violent exchange rate fluctuations, and lead to an uneven effect on the currencies of major industrial countries. For example, the euro and the dollar move significantly and have experienced appreciation and depreciation. + situation in Turkey + real/nominal exchange rate why important (u did already) + my study is…”
The monetary approach is useful in explaining exchange rate fluctuations. Its predictions are specific, and in case of the relative money supply increases, so does the relative price level. The monetary approach is useful in explaining the exchange rate fluctuations since there is a better proportion of the movement that is relative to the money supply. There is unity in the elasticity of the spot rate. Such an agreement is based on the relative money supply.
Purchasing Power Parity Comment by Microsoft: Need to use PPP as a theory, and use inflation differential to explain perentage change of nominal exchange rate
Ans use formula : NER = - *
Otherwise, how u get D. inflation?
Purchasing power parity= P1/P2
The purchasing power parity for Turkey was 1.6 per international dollar marking an annual growth rate of 12.59%
Interest Parity Condition Comment by Microsoft: Same problem, need to mention Interest rate differentials, Inflation differentials, Monetary growth differentials, Trade balance by using the theory (Purchasing Power Parity, interest parity condition, money supply and trade balance). then Combine the theory and result, whether those variable above could be the reason that lead to percentage change in nominal exchange rate based on the monetary approach.
Based on result, whether the monetary approach is useful in explaining exchange rate fluctuations. If not, what are the limitations
Methodology part require theory +data analysis.
Beginning use theory to explain , later on u should check whether the graph u get is consist with hypothesis that based on your theory. And answer the question whether relative productivity growth rates explain the movements in real exchange rate movements
Is meaningless to put the graph without explanation.
Moreover, could explain how u measure relative productivity of tradable goods, use GDP or employment for relative productivity or industrial production
(1+ Base currency)= Forward foreign exchange rate/Current spot exchange rate* (1+ quoted currency)
Interest parity condition= 1.32* (1+0.0117)/ (1+0.
Running head NOMINAL AND REAL EXCHANGE FLUCTUATIONS .docxglendar3
Running head: NOMINAL AND REAL EXCHANGE FLUCTUATIONS 1
NOMINAL AND REAL EXCHANGE FLUCTUATIONS 2
Causes of nominal and real exchange rate fluctuations, misalignments and the exchange rate policy
Student`s Name
Instructor
Institution
Course
Date
Fluctuations in Nominal Exchange Rate Comment by Microsoft: Can add introduction part: for example, “In 2008, both the international financial market and the global economy were turbulent due to the financial and economic crisis. This crisis has caused violent exchange rate fluctuations, and lead to an uneven effect on the currencies of major industrial countries. For example, the euro and the dollar move significantly and have experienced appreciation and depreciation. + situation in Turkey + real/nominal exchange rate why important (u did already) + my study is…”
The monetary approach is useful in explaining exchange rate fluctuations. Its predictions are specific, and in case of the relative money supply increases, so does the relative price level. The monetary approach is useful in explaining the exchange rate fluctuations since there is a better proportion of the movement that is relative to the money supply. There is unity in the elasticity of the spot rate. Such an agreement is based on the relative money supply.
Purchasing Power Parity Comment by Microsoft: Need to use PPP as a theory, and use inflation differential to explain perentage change of nominal exchange rate
Ans use formula : NER = - *
Otherwise, how u get D. inflation?
Purchasing power parity= P1/P2
The purchasing power parity for Turkey was 1.6 per international dollar marking an annual growth rate of 12.59%
Interest Parity Condition Comment by Microsoft: Same problem, need to mention Interest rate differentials, Inflation differentials, Monetary growth differentials, Trade balance by using the theory (Purchasing Power Parity, interest parity condition, money supply and trade balance). then Combine the theory and result, whether those variable above could be the reason that lead to percentage change in nominal exchange rate based on the monetary approach.
Based on result, whether the monetary approach is useful in explaining exchange rate fluctuations. If not, what are the limitations
Methodology part require theory +data analysis.
Beginning use theory to explain , later on u should check whether the graph u get is consist with hypothesis that based on your theory. And answer the question whether relative productivity growth rates explain the movements in real exchange rate movements
Is meaningless to put the graph without explanation.
Moreover, could explain how u measure relative productivity of tradable goods, use GDP or employment for relative productivity or industrial production
(1+ Base currency)= Forward foreign exchange rate/Current spot exchange rate* (1+ quoted currency)
Interest parity condition= 1.32* (1+0.0117)/ (1+0.
Running head NOMINAL AND REAL EXCHANGE FLUCTUATIONS .docxtodd581
Running head: NOMINAL AND REAL EXCHANGE FLUCTUATIONS 1
NOMINAL AND REAL EXCHANGE FLUCTUATIONS 2
Causes of nominal and real exchange rate fluctuations, misalignments and the exchange rate policy
Student`s Name
Instructor
Institution
Course
Date
Fluctuations in Nominal Exchange Rate Comment by Microsoft: Can add introduction part: for example, “In 2008, both the international financial market and the global economy were turbulent due to the financial and economic crisis. This crisis has caused violent exchange rate fluctuations, and lead to an uneven effect on the currencies of major industrial countries. For example, the euro and the dollar move significantly and have experienced appreciation and depreciation. + situation in Turkey + real/nominal exchange rate why important (u did already) + my study is…”
The monetary approach is useful in explaining exchange rate fluctuations. Its predictions are specific, and in case of the relative money supply increases, so does the relative price level. The monetary approach is useful in explaining the exchange rate fluctuations since there is a better proportion of the movement that is relative to the money supply. There is unity in the elasticity of the spot rate. Such an agreement is based on the relative money supply.
Purchasing Power Parity Comment by Microsoft: Need to use PPP as a theory, and use inflation differential to explain perentage change of nominal exchange rate
Ans use formula : NER = - *
Otherwise, how u get D. inflation?
Purchasing power parity= P1/P2
The purchasing power parity for Turkey was 1.6 per international dollar marking an annual growth rate of 12.59%
Interest Parity Condition Comment by Microsoft: Same problem, need to mention Interest rate differentials, Inflation differentials, Monetary growth differentials, Trade balance by using the theory (Purchasing Power Parity, interest parity condition, money supply and trade balance). then Combine the theory and result, whether those variable above could be the reason that lead to percentage change in nominal exchange rate based on the monetary approach.
Based on result, whether the monetary approach is useful in explaining exchange rate fluctuations. If not, what are the limitations
Methodology part require theory +data analysis.
Beginning use theory to explain , later on u should check whether the graph u get is consist with hypothesis that based on your theory. And answer the question whether relative productivity growth rates explain the movements in real exchange rate movements
Is meaningless to put the graph without explanation.
Moreover, could explain how u measure relative productivity of tradable goods, use GDP or employment for relative productivity or industrial production
(1+ Base currency)= Forward foreign exchange rate/Current spot exchange rate* (1+ quoted currency)
Interest parity condition= 1.32* (1+0.0117)/ (1+0.
Empirical literature on money demand is mainly based on the estimation of a long run relation by means of time-invariant cointergration approach. Taiwan has experienced the economic and financial regime change since 1979. The purpose of this paper is to test structural breaks in Taiwan long run money demand equation. We examine six of the most influential specifications proposed in the literature. The classical set of explanatory variables (e.g. income and interest rates) is extended on the base of a number underlying economic reasons related to financial, labor and international portfolio characteristics. The results suggest that international financial market variables and the classical specifications are the key determinants of structural instability observed in Taiwan broad money.
Impact of Macroeconomic Factors on Share Price Index in Vietnam’s Stock Markettheijes
This paper investigates the macroeconomic determinants of share price in the stock market of Vietnam. The investigation was conducted by using a VECM econometric methodology and revealed thatVietnam’s stock market prices are chiefly determined by economic activities: market price index, inflation, money supply and exchange rate. An increase in market price index and money supply makes share price, while the increase of inflation (CPI) and exchange rate reduces share price. The study’s result showed that Vietnam’s stock market can be replaced by investors of foreign currency (USD), while the exchange rate tends to rise.
Abstract: The theoretical relationship of the long-run equilibrium between real exchange rates and interest rate differentials is essentially derived from the Purchasing Power Parity (PPP) and the uncovered interest parity. However, empirical evidence on this long-run relationship has rather been inconclusive. While several authors are able to establish the long-run relationship between real exchange rates and interest rate differentials other could not found this relationship. The reason for lack of relationship in some of the studies is as a result of omitted variables (Meese and Rogoff, 1988). Therefore, attempt is made in this study to evaluate this relationship between real exchange rate and interest rate differential for the case of Nigeria by controlling for foreign exchange reserves. The paper uses monthly data for the period 1993:1-2012:12 and applies Autoregressive Distributed Lags (ARDL) model. The estimates suggest the existence of long-run relationship between real exchange rate, interest rate differential and foreign exchange reserves. In the long run, the exchange rate coefficient has a positive effect on the foreign reserves. However, the effect of interest rate differential is negative and statistically significant. On the short run dynamics, the finding indicates a non-monotonic relationship between real exchange rate, interest rate differential and foreign exchange reserves. The out-of-sample forecast indicates a better forecast using ARMA model as all Theil coefficients are close zero for all the horizons used in the model.
The theoretical relationship of the long-run equilibrium between real exchange rates and interest rate differentials is essentially derived from the Purchasing Power Parity (PPP) and the uncovered interest parity. However, empirical evidence on this long-run relationship has rather been inconclusive. While several authors are able to establish the long-run relationship between real exchange rates and interest rate differentials other could not found this relationship. The reason for lack of relationship in some of the studies is as a result of omitted variables (Meese and Rogoff, 1988). Therefore, attempt is made in this study to evaluate this relationship between real exchange rate and interest rate differential for the case of Nigeria by controlling for foreign exchange reserves. The paper uses monthly data for the period 1993:1-2012:12 and applies Autoregressive Distributed Lags (ARDL) model. The estimates suggest the existence of long-run relationship between real exchange rate, interest rate differential and foreign exchange reserves. In the long run, the exchange rate coefficient has a positive effect on the foreign reserves. However, the effect of interest rate differential is negative and statistically significant. On the short run dynamics, the finding indicates a non-monotonic relationship between real exchange rate, interest rate differential and foreign exchange reserves. The out-of-sample forecast indicates a better forecast using ARMA model as all Theil coefficients are close zero for all the horizons used in the model.
Using a series of econometric techniques, the study analysed interaction between monetary policy and private sector credit in Ghana. This study made use of monthly dataset spanning January 1999 to December 2019 of credit to the private sector (PSC) and broad money supply (M2). The results reveal that there exists cointegration, a long run stationary relation between monetary policy and private sector credit. This implies, increases in credit should prompt long-term increases in monetary policy. It is not surprising that growth in the private sector might have a stronger effect on monetary policy. The Error Correction Test is statistically significant and that all the variables demonstrate similar adjustment speeds. This implies that in the short run, both money supply and credit are somewhat equally responsive to their last period’s equilibrium error. There is unidirectional causation from private sector credit to monetary policy. It can be said that, there is an interaction between money supply and private sector credit. Thus, credit to private sector holds great potential in promoting economic growth. It can be recommended to the government to increase the credit flow to the private sector because of its strategic importance in creating and generating growth of the economy.
This paper empirically examines the role of uncertainty occurred by ‘news’ in Japanese financial markets. A GARCH-MIDAS model is used for estimation. It finds that news-based implied volatility performs well in predicting long-term aggregate market volatilities. A subsample analysis provides that the predictive power of news-based volatility is continuing, as most of the coefficients are positive and significant. So, in general, the news based implied volatility model is associated with high market volatility. Moreover, stock market prices go on rising, different effects that appeared in each subsample period. On the recent period, when Abenomics was conducted, the effect decreased. Also, the effect of exchange rates decrease in short time. When stock prices decrease, volatilities of the stock prices in the past period increase. There is some possibility that markets were too unstable about the movements because of the low prices. Also, the volatility of long-term interest rates increases when the interest rate declines in the recent period under Abenomics. Although interest rates have been quite low in both sample periods, the Bank of Japan (BOJ) started to manage long-term interest rates in the recent period, so market participants seem to begin noticing the movements.
QUALITY ASSURANCE FOR ECONOMY CLASSIFICATION BASED ON DATA MINING TECHNIQUESIJDKP
Researchers in the quality assurance field used traditional techniques for increasing the organization income and take the most suitable decisions. Today they focus and search for a new intelligent techniques in order to enhance the quality of their decisions. This paper based on applying the most robust trend in computer science field which is data mining in the quality assurance field. The cases study which is discussed in this paper based on detecting and predicting the developed and developing countries based on the indicators. This paper uses three different artificial intelligent techniques namely; Artificial Neural Network (ANN), k-Nearest Neighbor (KNN), and Fuzzy k-Nearest Neighbor (FKNN). The main target of this paper is to merge between the last intelligent techniques applied in the computer science with the quality assurance approaches. The experimental result shows that proposed approaches in this paper achieved the highest accuracy score than the other comparative studies as indicates in the experimental result section.
Devanayagam_Impact of Macroeconomic Variables on Global Stock MarketsDevanayagam N
This presentation is about how macroeconomic variables such as GDP, GDP growth rate, Inflation, Unemployment Rate and Development Status of countries influence the performance of Global stock markets (Stock Exchanges across the world).
How does capital structure affect firm s market competitiveness.pdfNghiên Cứu Định Lượng
Các quyết định về vốn hiệu quả không chỉ làm tăng hiệu quả hoạt động của doanh nghiệp mà còn mang tính chiến lược để mang lại lợi thế cạnh tranh của doanh nghiệp trên thị trường. Sử dụng một tỷ lệ nợ phù hợp giúp doanh nghiệp cân bằng giữa nguồn lực bên trong và bên ngoài để cạnh tranh với các doanh nghiệp trong ngành. Nghiên cứu này nhằm tìm ra ảnh hưởng của cấu trúc vốn thông qua hệ số nợ (DR) đến năng lực cạnh tranh của doanh nghiệp (HHI) ở Việt Nam. Một mẫu gồm 574 công ty niêm yết trên sàn giao dịch chứng khoán của Việt Nam từ năm 2010–2018 được nghiên cứu bằng phần mềm STATA. Kết quả cho thấy cấu trúc vốn ảnh hưởng đến năng lực cạnh tranh của doanh nghiệp hình chữ U ngược. Đồng thời, DR ảnh hưởng đến HHI dưới dạng hàm hình chữ U trong các sản phẩm công nghiệp, thông tin và viễn thông và hàng tiêu dùng. Trong khi đó, DR ảnh hưởng đến HHI theo hình chữ U ngược trong các lĩnh vực dịch vụ tiêu dùng, nguyên vật liệu và tiện ích cộng đồng. Với kết quả của phân tích này, nghiên cứu cũng cung cấp các thảo luận cũng như các hàm ý chính sách đối với doanh nghiệp sử dụng tối ưu cơ cấu vốn để tạo lợi thế cạnh tranh trên thị trường.
The literature shows little evidence on the effects of the business model upon the volatility of banks in developing and fast growing economies. Hence, this study examines the effects of busi-ness model choice on bank’s stability in ASEAN countries. Using GMM and other robust econo-metric methods on the sample of 99 joint stock commercial banks, we find significant and nega-tive impacts of diversification model in which bank shifts toward non – interest and fee – based activities. We also find that the impacts are different between two groups of countries. For Vi-etnam, Indonesia and the Philippines, the diversification entails negative impacts on the stability while demonstrating positive impacts for Thailand and Malaysia. Upon the findings, we draw policy implications for a more sustainable development in ASEAN banking business.
Effect of social capital on agribusiness diversification intention in the eme...Nghiên Cứu Định Lượng
This is the first study to explore the comprehensive effect of the facets of social capital on behavioral intention through behavioral goals and determinants of the TPB under the premises of the RBV. The findings will help emerging economies, for example, Vietnam, where most farmers are family business owners or microscaled entrepreneurs in agriculture.
How does hotel employees’ satisfaction with the organization’s COVID-19 respo...Nghiên Cứu Định Lượng
Bài nghiên cứu của thành viên Trung tâm Nghiên cứu Định lượng tham gia trong dự án về Covid-19
This research examines the role of hotel employees’ satisfaction with their organization’s COVID-19 responses in reducing their perceived job insecurity (PJI) and maintaining their job performance (JP). We conducted two studies using an explanatory sequential mixed-methods design. The results indicated that employees’ satisfaction with organization COVID-19 responses (SOCV19R) positively influences JP and moderates (1) the positive association between perceived health risk associated with COVID-19 (PHRCV19) and PJI and (2) the negative link between PJI and JP. Unexpectedly, PHRCV19 was found to positively affect JP, and the moderating effect of SOCV19R on the relationship between PHRCV19 and JP was significant and positive. We also found that PJI has a mediating role in the PHRCV19–JP relationship. This study fills a significant gap in hospitality research by exploring the role of the organization’s crisis responses in tempering the impact of perceived health risk of a global health crisis on hotel employees. Theoretically, this research revealed that employees’ SOCV19R helps raise JP, mitigate the positive influence of PHRCV19 on PJI and the negative impact of PJI on JP, and strengthen the positive effect of PHRCV19 on JP.
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
Latino Buying Power - May 2024 Presentation for Latino CaucusDanay Escanaverino
Unlock the potential of Latino Buying Power with this in-depth SlideShare presentation. Explore how the Latino consumer market is transforming the American economy, driven by their significant buying power, entrepreneurial contributions, and growing influence across various sectors.
**Key Sections Covered:**
1. **Economic Impact:** Understand the profound economic impact of Latino consumers on the U.S. economy. Discover how their increasing purchasing power is fueling growth in key industries and contributing to national economic prosperity.
2. **Buying Power:** Dive into detailed analyses of Latino buying power, including its growth trends, key drivers, and projections for the future. Learn how this influential group’s spending habits are shaping market dynamics and creating opportunities for businesses.
3. **Entrepreneurial Contributions:** Explore the entrepreneurial spirit within the Latino community. Examine how Latino-owned businesses are thriving and contributing to job creation, innovation, and economic diversification.
4. **Workforce Statistics:** Gain insights into the role of Latino workers in the American labor market. Review statistics on employment rates, occupational distribution, and the economic contributions of Latino professionals across various industries.
5. **Media Consumption:** Understand the media consumption habits of Latino audiences. Discover their preferences for digital platforms, television, radio, and social media. Learn how these consumption patterns are influencing advertising strategies and media content.
6. **Education:** Examine the educational achievements and challenges within the Latino community. Review statistics on enrollment, graduation rates, and fields of study. Understand the implications of education on economic mobility and workforce readiness.
7. **Home Ownership:** Explore trends in Latino home ownership. Understand the factors driving home buying decisions, the challenges faced by Latino homeowners, and the impact of home ownership on community stability and economic growth.
This SlideShare provides valuable insights for marketers, business owners, policymakers, and anyone interested in the economic influence of the Latino community. By understanding the various facets of Latino buying power, you can effectively engage with this dynamic and growing market segment.
Equip yourself with the knowledge to leverage Latino buying power, tap into their entrepreneurial spirit, and connect with their unique cultural and consumer preferences. Drive your business success by embracing the economic potential of Latino consumers.
**Keywords:** Latino buying power, economic impact, entrepreneurial contributions, workforce statistics, media consumption, education, home ownership, Latino market, Hispanic buying power, Latino purchasing power.
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Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
Resume
• Real GDP growth slowed down due to problems with access to electricity caused by the destruction of manoeuvrable electricity generation by Russian drones and missiles.
• Exports and imports continued growing due to better logistics through the Ukrainian sea corridor and road. Polish farmers and drivers stopped blocking borders at the end of April.
• In April, both the Tax and Customs Services over-executed the revenue plan. Moreover, the NBU transferred twice the planned profit to the budget.
• The European side approved the Ukraine Plan, which the government adopted to determine indicators for the Ukraine Facility. That approval will allow Ukraine to receive a EUR 1.9 bn loan from the EU in May. At the same time, the EU provided Ukraine with a EUR 1.5 bn loan in April, as the government fulfilled five indicators under the Ukraine Plan.
• The USA has finally approved an aid package for Ukraine, which includes USD 7.8 bn of budget support; however, the conditions and timing of the assistance are still unknown.
• As in March, annual consumer inflation amounted to 3.2% yoy in April.
• At the April monetary policy meeting, the NBU again reduced the key policy rate from 14.5% to 13.5% per annum.
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what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
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1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
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Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
1. International Journal of Economics and Finance; Vol. 8, No. 7; 2016
ISSN 1916-971X E-ISSN 1916-9728
Published by Canadian Center of Science and Education
132
Impacts of Monetary Policy and Information Shock on Stock Market:
Case Study in Vietnam
Trung Thanh Nguyen1,2
, Thi Linh Do3
& Van Duy Nguyen4
1
School of Economics, Shanghai University, Shanghai, China
2
Faculty of Economics and Business Administration, Hatay Community college, Hanoi, VietNam
3
Faculty of Accounting and Finance, Hatay Community college, Hanoi, VietNam
4
Viet Nam Quantitative Analysis Join Stock Company, Hanoi, Vietnam
Correspondence: Nguyen Trung Thanh, School of Economics, Shanghai University, 99 Shangda Road, Baoshan
District, Shanghai 200444, China. E-mail: ngthanhhn@gmail.com
Received: March 24, 2016 Accepted: May 3, 2016 Online Published: June 25, 2016
doi:10.5539/ijef.v8n7p132 URL: http://dx.doi.org/10.5539/ijef.v8n7p132
Abstract
Evaluation of the impact of monetary policy on Vietnam stock market plays an important role for economists as
well as stock investors. Stock price index not only gets impacts from the macroeconomic factors such as oil price,
gold prices…but also be very sensitive to the changes in monetary policy. For each different markets, stock
index are also different from each other. Hence, this artical is conducted to evaluate the impacts of monetary
policy on Vietnam Stock Index (VNIDEX) in the period of the time from 2006 to 2015. The author uses GJR -
GARCH model and ARDL research with time-serie data by statistical methods and quantitative analysis to
evaluate the above impact related to lag and shocks in the market. The result shows that the monetary policy
including interests, exchange rate and required reserve ratio has a negative impact on stock price in long term.
Besides, both bad or good market shock cause changes of stock price at stable level.
Keywords: ARDL model, GJR-GARCH model, monetary policy, stock price
1. Introduction
1.1 Introduce the Problem
Vietnam stock market was born in 2000 in HCM city. After that, till 2005 the Stock center in Hanoi was
established. Although regarded as a newbie trading center, Vietnam Stock market has experienced the up and
down periods, both strong development and severe recession. From 2005-2008 the stock price reached a top
point of 1137.69 points on Mar 12th 2007, and then fell sharply to 245.74 point on Feb 24th 2009. After this
period, the market grows slowly with the fluctuated level around 500 points.
At present, there are tens of billions of transaction on the Stock Exchange in Vietnam daily. Profits from stocks
are the main income of many young peoples or the accumulated pension of the old (Maskay, 2007). The change
(degradation) of the stock market will led to the confusion in investors’ lives because it directly relates to their
main income. These changes are due to the impact of international market factors (Maskay, 2007) or the
monetary policy (macroeconomic) of the central bank. Therefore, the study of impacts of policies, especially
monetary policy is considered as an important key which helps investors to make right decisions.
There have been many studies on fluctuation of the stock price and monetary policy. The authors approved that
stock indices react sensitively to changes of monetary policy (Azali, Zare, & Habibullah, 2013). Stock investors
always follow market’s changes in general and the monetary policy of the central bank in particular in order that
they can make a right dicision which will bring benefit. Hence, studying impacts of factors on stock price
become a vital part which helps investors to make investment decision.
Nowadays, in Vietnam, there are some studies on macroeconomics or the monetary policy (Ton & Nguyen,
2015), however, there is no study on the long-term or short-term impacts of financial shock and the monetary on
the stock price in detail. These aims of this article is following as: firstly asscessing the short term and long term
impacts of the monetary policy on the stock price; and secondly considering information shock’s impact on stock
index.
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133
1.2 Theoritical Overview
Monetary policy is a monetary measures implemented by the Central Bank to make influence on economic
activities, price stability, employment maximum and stability of the long-term interest rates (Okpara, 2010). In
fact, many economists consider monetary policy as the most important macroeconomic policy (Maskay, 2007).
Apart from the impact on inflation (within the allowed limit of the central bank to control inflation and
supervise bank system), the monetary policy also affects other aspects of the economy such as real GDP,
unemployment and exchange rates, the stock market.
The theory of “efficient market” by Fama (1970) has set an extremely important theoritical basis for policy
makers as well as stock investors. Accordingly, the policy makers can freely implement the national
macro-economic policies without fearing that this policy will change the essense of the stock market because
they only affect the stock price index. Since then there have been many researchers focusing on the impact of
these monetary policies on changes in the stock index.
Monetary policy can be conducted through many different tools such as exchange rate policy, interest rates,
money supply or the required reserve. The policy of interest rates is attractive to researchers to assess the impact
on the stock market. Studies have shown that interest has an opposite impact on the stock price (Ali, 2014;
Dufour & Tessier, 2006; Okpara, 2010; Fischbacher, 2012; Zare et al., 2013; Gali & GAMBETTI, 2013). At the
second rank, exchange rate policy can help investors to forrcast the market change through the exchange rate
policies of central banks (Maskay, 2007; Jamil & Ulla, 2013; Adjasi et al., 2008). Some studies also examined
the impact of money supply on the stock price (Homa & Jaffe, 1971; Hamburger & Chochin, 1972; Maskay,
2007; Nofeldt, 2014), it showed a positive relationship between the money supply and US stock market,
typically the S & P500 Index.
Apart from three key factors, the central bank also uses some other tools in their operations as required reserve
ratio for banks (Teja et al., 2013) and open market operations. However, for newbie financial markets like
Vietnam, the application of the open market is not effective when the transaction is not entirely through banks.
Therefore, open market operation seems not to affect to adjustment of the monetary policy as well as the stock
market.
2. Method
2.1 Researching Models
In this research, the author uses the time-serie data to evaluate the immediate impacts and influctuation at lag. To
solve the researh aim, the author refers the previous studies and launch research model with variables as below:
Tabel 1. Aspect and reference model
Variable name Aspect Authors
Interest rate -
Ali, 2014; Dufour & Tessier, 2006; Okpara, 2010; Fischbacher, 2012;
Zare & et al, 2013; Gali & Gambetti, 2013
Exchang rate -/+ Maskay, 2007; Jamil & Ulla, 2013; Adjasi & et al, 2008
Money Supply + Maskay, 2007; Nofeldt, 2014
Required reserve ratio - Teja & et al, 2013
Source: Authors’ collection.
With interest rate, exchange rate, money supply and required reserve ratio are chosen as independent variables in
the below model:
Figure 1. Researching model
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134
In Which:
Dependent variables:
VNI is VNINDEX price at time “t”
VNIt-i is VNINDEX price at lag i
Independent variables:
IRt: lending interest rates.
EXt: USD exchange rate.
M2t: money supply.
REt: required reseve ratio.
The Variables IRt-i; EX t-i; M2 t-i and REt-i are values at lag i.
To study the impact of these information shocks as well as monetary mutations on the stock price, the authors
used the variance estimating model:
2 2 2 2
0 1 1 1 1 1 1 1* .... * * .... * * * .... * *t t i t i t i t i t t i t i t ih h h u u u d u d
In Which:
ht: variances
dt: variables of possitive and negative shocks.
2.2 Method of Analysing
To evaluate the impact of the monetary policy on the stock price, the time-serie data is used, so ARDL model is
chosen to study.
For time-serie data, to ensure sustainable model before performing ARDL model, researcher used the data source
(stable data chain). The stable input data will avoid fake regression case (Gurajati, 2003; Ramanathan, 2002).
Besides evaluation of the factors having impact on dependent variables, there is many invisible variables,
espeically information shocks which needs being considered carefully to study changes of dependent variables in
more detail. In economic models, Engle has developed the first ARCH models in 1982 and later he cooperated
with Kroner to develop GARCH in 1995 to estimate further market shocks. Basing on the premise of estimating
shocks by Engle, the scientists including Glosten, Jaganathan and Runkle (1993) has developed more by giving
and estimating positive and negative shocks to consider any differences between them (called GJR-GARCH
model).
In this study, in order to asscess impact of manetary policy on Vietnam stock market in 2006-2015, the author
also uses ARDL model to evaluate the impact of market issues on stock price and GJR-GARCH to estimate
positive and negative shocks in this research period.
Yt= α0 +α1*Yt−1+α2*Yt−2 +…+αn*Yt−1 + β0*Xit+β1*Xit−1+…+ βn*Xit−n +Et+ut (1)
2 2 2 2
0 1 1 1 1 1 1 1* .... * * .... * * * .... * *t t i t i t i t i t t i t i t ih h h u u u d u d (2)
In which: Yt and Xt are variables without unit root; ut is residual;
Yt−n and Xt−n are stationary variables at lag levels.
Et is long-term impact of stationary variables of Xt;
ht: variances;
dt: variables of possitive and negative shocks.
Stationary time-serie is a series with constant mean, variance, covariance at every time (Gurajati, 2003). To test
stationary of time serie data, the author uses open ADF (Gurajati, 2003).
Optimal lag is lag at which variables are modeled through the lag variables and the other variables at the same
lag level. The determination of the optimal lag is based on selected indicators (Hansen, 2013); these indicators
are supported in EViews software.
To ensure a sustainable model, the regression equation needs to satisfy the conditions of redundant variables test
(guarantee that models do not contain redundant variables – do not influence on the stock price);
heteroscedasticity, autocorrelation test.
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135
In equation (2) if the coefficient has statistically significant, positive and negative shocks will have different
impacts on the variance ht (Ton & Nguyen, 2015).
3. Results
3.1 Some Figures on the Monetary Policy and Stock Prices
The input data description Statistics: In the period 2006-2015 the stock index reached 543.28 points at average;
in which the maximum value reached 1137.69 points, the lowest value was 245.74 points. Credit interest rates
was 12% per year at average, there was a period up to 20.25% per year in 7/2008. Dollar exchange rate
fluctuates around 18,789 VND/USD; consumer price index reached 107.67 at average; the money supply M2
monthly reached 2,510,000 Bil VND at average and required reserve ratio was 4.16% in the periods (Table 2).
Table 2. The period 2006-2015
VNI
(poit)
IR
(%)
EX
(VNĐ/USD)
CPI
(poit)
M2
(VND)
RE
(%)
Mean 543.28 12.00 18789.41 107.67 2.51E+15 4.16
Maximum 1137.69 20.25 21673 145.10 5.34E+15 11
Minimum 245.74 7.23 15914 62.48 6.76E+14 3
Observations 117
Source: The authors’ collection.
3.2 Correlation Matrix
Correlation coefficients evaluate the two-way relationship of each pair of variables. To examine the relationships
as well as performance of the following analysis, the authors used the values of Loganepe which helps data
series be more stable but still does not alter the transitivity characteristics between variables. Results show that
the variable dependent in stock price has the strongest correlation with money supply (0.5641) and interest rate
(-0.5614), weakest correlation with the required reserve rate (-0.3420) (Table 3).
To evaluate research objectives more clearly, the authors performed a regression analysis based on GJR-GARCH
and ARDL model.
Table 3. Correlation matrix
LVNI IR LEX LM2 RE
LVNI 1
IR -0.5614 1
LEX 0.3747 -0.2791 1
LM2 0.5641 -0.5631 0.9276 1
RE -0.3420 0.4565 -0.7015 -0.6741 1
Source: Eviews’ results.
3.3 Unit Root Test
To assess the impact of monetary policy on stock prices, the input variables must be ensured with data reliability
in order to avoid the fake regression, data needs to be stationary (Gujarati, 2003). The test results were obtained
as follows:
Table 4. Testing result for unit roots of data series
Variables’ name Test result ADF
Statistical Value at the levels of significance.
Prob
1% 5% 10%
LVNI -2.387 -3.489 -2.887 -2.580 0.148
IR -2.680 -3.490 -2.887 -2.581 0.081
LEX -0.515 -3.489 -2.887 -2.580 0.883
LM2 -2.373 -3.489 -2.887 -2.580 0.152
RE -3.388 -4.067 -3.462 -3.157 0.060
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136
THE FIRST DIFFERENCE
DLVNI -8.254 -4.041 -3.450 -3.150 0.000
DIR -6.965 -4.041 -3.450 -3.150 0.000
DLEX -8.565 -4.041 -3.450 -3.150 0.000
DLM2 -9.299 -4.041 -3.450 -3.150 0.000
DRE -4.397 -4.070 -3.464 -3.158 0.004
Source: Results from Eviwes software.
Results showed that the variables do not stop at the significant level of 1%, 5% and 10% so, the author uses the
1st difference and re-tests then finds out that 1st
difference variables are satisfied for conditions of stationary.
Therefore; variables are put into the regression analysis at the first difference in the following steps.
3.4 Determining the Optimal Lag
In the economic study with time-serie data, factors not only have an immediate impact but also influence at lag
stages. To determine the optimal lag and to underestimate the influence of monetary policy on stock price
correctly, authors used statistical indicators to determine appropriate lag level. Results from the data analysis in
the period 2006-2015 are shown as follows (Table 5):
Table 5. The result for determining optimal lag
Lag LogL LR FPE AIC SC HQ
0 96.27573 NA* 0.007703 -2.02835 -1.889471* -1.97235
1 97.98739 3.195099 0.007583* -2.044164* -1.87751 -1.976959*
2 98.23699 0.460385 0.007711 -2.02749 -1.833059 -1.94908
3 98.58347 0.631352 0.007825 -2.01297 -1.790761 -1.92336
4 98.90625 0.581014 0.007946 -1.99792 -1.747936 -1.89711
5 99.36337 0.812646 0.008044 -1.98585 -1.708096 -1.87385
6 100.588 2.149956 0.008007 -1.99085 -1.685313 -1.86764
7 100.6321 0.076398 0.008181 -1.9696 -1.636294 -1.83519
8 100.6887 0.09681 0.008358 -1.94864 -1.587554 -1.80303
Source: Results from Eview software.
Results showed that the study data sources affect each other in two stages (the impact of monetary policy on
stock index immediately in that month and after one month). Thus, the authors choose lag level of 1 to establish
a research model.
3.5 Testing Cointegration
To determine the long-term relationsip between the monetary policy and the stock price, the author implemented
testing for stationary variables.
Table 6. Testing cointegration
Hypothesized
No. of CE(s)
Eigenvalue Trace Statistic Prob.**
None * 0.560 149.452 0.000
At most 1 * 0.342 76.300 0.000
At most 2 * 0.283 39.111 0.003
At most 3 0.089 9.558 0.316
At most 4 0.014 1.292 0.256
Source: Eview’s result.
The results showed there are two long-term relationships between monetary policy and stock price. Therefore, by
using the regressions ARDL, the author evaluates which is the long-term relationship in detail.
3.6 Regression Results
Since the study objective is assessing the one-way impact of monetary policy on the stock price so, the author
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137
focuses on regression analysis without considering the cause and effect of the relationship between variables
(Granger test). Firstly the authors will give a research model of the factors that impact on the stock price, then
will estimate the influence of the shock market. Final results were obtained as belows:
Table 7. Results of estimating factors’ impact on stock price
DLVNI
β S.E Prob
C 1.585216 0.8692 0.0682
LEX(-1) -0.14968 0.0864 0.0832
IR(-1) -0.00339 0.0018 0.0541
RE(-1) -0.01728 0.0041 0.0000
R2
12.50%
Prob(F-s) 0.000
Heteroscedasticity test 0.6762
Autocorrelation test p-value>0.1
Multicollinearity test (VIF)
LEX(-1) 1.977
IR(-1) 1.268
RE(-1) 2.303
Source: EVIEW system.
To make sure the reability of the estimating model, the authors tested the breach of the hypothesis of regression
estimates. The results showed that the model (1) does not meet Heteroscedasticity, Autocorrelation and
Multicollinearity (Table 7). It shows credibility of the conclusions from the estimating model.
Results showed that monetary policy has the opposite effect on Vietnam stock price through three policy
instruments: interest rates, money supply and required reserve ratio (p-value is less than 0.05). However, the
effects will have long-term impacts, but in the short-term, monetary policy seems to have no meaning in making
the stock price change.
To explore the impact of information shocks, authors conducted variance estimates and obtained the following
results:
Table 8. Results for market shock estimats
ht
β S.E Prob
C 0.000 0.000 0.077
2
1tu 0.163 0.103 0.112
2
1 1*t tu d -0.231 0.107 0.031
ht-1 0.811 0.106 0.000
Source: Eview’s results.
The shock is estimated by the residual value and the variance is in the previous period 1 unit. The variance (ht-1)
at lag 1 has statistical significance (p-value is less than 0.05) indicates influence the information to the stock
market. Also, the p-value of the equilibrium coefficient of positive or negative shocks ( 2
1 1*t tu d
) by 0.03 (less
than 0.05) and negative beta coefficient indicates the bad information elements will have less affect than good
information (Glosten, Jaganathan, & Runkle, 1993).
4. Discussion
Stock price index of Vietnam from 2006 till now has strong change periods (stock bubble), which helped
pushing stock prices higher (1137 points) but then the stock price plummeted due to economic crisis in the mid
of 2008. It can be said the period of 2006 to 2007 was the beginning of the Vietnam stock market as well the
golden period. However, mainly because of the development by leaps and bounds in a short time, the shortage of
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138
preparation for the change of the market as well as the integration process, it made investors not react to the
economic crisis of 2008 in time, and made market plunge to below 300 points (Figure 2).
200
400
600
800
1,000
1,200
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
VNI
Figure 2. Stock price over the year
Research results show that the monetary policies (interest rate, exchange rate and required reserve ratio) have
long-term impacts on the stock price. At the same time, the monetary policy limits stock price (oppositte impact
on the stock price). The factor of Money supply seems to be no meaning in changing stock market.
Interest rates have the opposite effect on the stock price. It shows that tightening the monetary (increasing
interest rates) would make the stock market decrease. In the case of high inflation, state banks have tightened the
monetary policy by raising interest rates, which in the short term will not affect the stock market, but in the long
term it will have negative affect to businesses, especially companies that use large amounts of bank loans for
their business operations. The research results of interest rate is compatible with previous studies of (Ali, 2014;
Dufour & Tessier, 2006; Okpara, 2010; Fischbacher, 2012; Zare et al., 2013; Gali & GAMBETTI, 2013).
The policy of required reserve ratio also has the opposite effect on the stock price. Increasing the ratio of
required reserve in banks limited the amount exchanged between banks and outside individuals, business. In the
short time, companies can invest or make liquidity by external borrowings. However, in the longer term,
increasing required reserve ratio will causes many difficulties for enterprises’ business activities.
The exchange rate VND/USD has a negative impact on the stock price. It shows that adjusting exchange rate or
currency devaluating will make stock market get worse.the reason comes from an increase in import price
making difficulties for enterprises. It causes business activities in the country get worse and stock price decrease.
Information Shock has affected stock market prices, the good news shock has more powerful than the bad news.
This suggests that investors always appreciate good information shock. When there is good information flows
from market, it will fluctuate stock price (stock price increase). But, if receiving the bad information flow, prices
fluctuate with smaller amplitude.
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