scholarly journals The Impact of Monetary Policy Announcements on Stock Market Index in Poland

2016 ◽  
Vol 1 (1(1)) ◽  
pp. 7-16
Author(s):  
Hanna Zofia Kołodziejczyk
Keyword(s):  
Monetary Policy ◽  
Stock Market ◽  
Stock Market Index ◽  
Market Index ◽  
The Impact

Impact of monetary policy on house prices: case of Pakistan

2019 ◽  
Vol 13 (3) ◽  
pp. 503-512
Author(s):  
Muhammad Umar ◽  
Moin Akhtar ◽  
Muhammad Shafiq ◽  
Zia-Ur-Rehman Rao
Keyword(s):  
Monetary Policy ◽  
Stock Market ◽  
Time Series Data ◽  
House Prices ◽  
Series Data ◽  
Stock Market Index ◽  
Content Type ◽  
Market Index ◽  
The Impact ◽  
The Relationship

Purpose This study aims to explore the impact of monetary policy on house prices in Pakistan. Design/methodology/approach This study uses monthly time-series data of house prices, monetary policy, inflation and stock market index ranging from January 2011 to December 2016. All the series were checked for stationarity by using augmented Dickey–Fuller test, and lag length of 11 was decided on the basis of Schwert’z rule of thumb. Vector autoregressive (VAR) model was used because the series were not co-integrated. Findings The analysis revealed that monetary policy significantly affects house prices in Pakistan. Tight monetary policy results in lower house prices and vice versa. The relationship between monetary policy and house prices is unidirectional. The study also finds that higher inflation also leads to soaring house prices, but the variation in stock market index does not affect house prices. Originality/value To the best of authors’ knowledge, none of the existing studies explores the impact of monetary policy on house prices in Pakistan. The findings help investors and policy makers to understand the relationship between monetary policy and house prices to make better decisions.

scholarly journals The Impact of Macroeconomics on Stock Market Index in Brazil

2021 ◽  
Author(s):  
Endang Mahpudin ◽  
Reminta Lumban Batu
Keyword(s):  
Stock Market ◽  
Stock Market Index ◽  
Market Index ◽  
The Impact

scholarly journals Capital Asset Pricing Model, Theory and Practice: Evidence from USA (2009-2016)

2017 ◽  
Vol 12 (8) ◽  
pp. 182 ◽  
Author(s):  
Mohammad AbdelMohsen Al-Afeef
Keyword(s):  
Stock Market ◽  
Multiple Regression Model ◽  
Theory And Practice ◽  
Pricing Model ◽  
Stock Market Index ◽  
Market Return ◽  
Market Index ◽  
Stock Market Return ◽  
The Us ◽  
The Impact

This study discussed the Capital Assets Pricing model (CAPM) and its ability to measure the required return, the researcher tested this model on Amazon Company listed in S&P 500 during the period (2009-2016), to measure the impact of beta stock and market index return on the required return. Multiple regression model was used to test the effect of independent variables (Beta stock, Market Index Return) on the dependent variable (Required return), it should be noted that there is a statistically significant impact of the US stock market Return (S&P500) and Amazon stock Beta factor on Amazon stock required return, and the study model explanatory was 20% , this means that 20% of the changes in the required return are due to beta and market return, and 80% of the changes due to other factors, also find that CAPM can be applied on efficiency markets and huge companies.The researcher recommends applying the variables of the study on a group of large companies in the S&P 500 index, and looking for other factors that may affect the required return.

scholarly journals Do confidence indicators have an impact on macro-financial indicators? An analysis of the financial service and real sector confidence indexes: evidence from Turkey

2020 ◽  
Vol 9 (1) ◽  
pp. 74-94
Author(s):  
Esra N Kilci
Keyword(s):  
Stock Market ◽  
Unit Root ◽  
Financial Services ◽  
Structural Breaks ◽  
Unit Root Test ◽  
Real Sector ◽  
Financial Indicators ◽  
Stock Market Index ◽  
Market Index ◽  
The Impact

The primary aim of this study is to analyze the impact of financial services and real sector confidence indexes on some macroeconomic and financial indicators such as industrial production, inflation, stock market index, foreign exchange rates and interest rates in Turkey for the period from May 2012 to May 2019. In this study, the unit root properties of these series are tested by using the Narayan and Popp (2010) unit root test with two structural breaks and the Enders and Lee (2012) Fourier ADF unit root test with multiple structural breaks. We investigate the causal link between confidence indicators and macro-financial variables using the Fourier Toda Yamamoto causality test proposed by Nazlioglu et al. (2016). The results suggest a strong link between financial services and real sector confidence indexes on macro-financial indicators such as stock market index and inflation, supporting the evidence of the short-run impact of confidence indexes on these variables.

scholarly journals The Impact of Covid-19 Spread on Stock Markets: The Case of the GCC Countries

2020 ◽  
Vol 13 (11) ◽  
pp. 16
Author(s):  
Nader Alber ◽  
Amr Saleh
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Stock Market Return ◽  
Gcc Countries ◽  
Developed Stock Markets ◽  
The Impact

This paper attempts to investigate the effects of 2020 Covid-19 world-wide spread on stock markets of GCC countries. Coronavirus spread has been measured by cumulative cases, new cases, cumulative deaths and new deaths. Coronavirus spread has been measured by numbers per million of population, while stock market return is measured by Δ in stock market index. Papers conducted in this topic tend to analyze Coronavirus spread in the highly infected countries and focus on the developed stock markets. Countries with low level of infection that have emerging financial markets seem to be less attractive to scholars concerning with Coronavirus spread on stock markets. This is why we try to investigate the GCC stock markets reaction to Covid-19 spread.   Findings show that there are significant differences among stock market indices during the research period. Besides, stock market returns seem to be sensitive to Coronavirus new deaths. Moreover, this has been confirmed for March without any evidence about these effects during April and May 2020.

scholarly journals Quantitative relationship between corruption and development of the Tunisian stock market

2018 ◽  
Vol 7 (2) ◽  
pp. 39-47
Author(s):  
Ibtissem Missaoui ◽  
Mohsen Brahmi ◽  
Jaleleddine BenRajeb
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Quantitative Relationship ◽  
Stock Market Index ◽  
Private Companies ◽  
Stock Market Development ◽  
Market Index ◽  
The Government ◽  
The Impact ◽  
Positive Effect

The aim of this article is to seek especially the impact of corruption on the bond and stock market development. For the methodology/approach, the authors analyze a sample of 20 listed Tunisian firms from the Stock Exchange and Financial market, covering the period from 2006 to 2016 by using pooling cross section techniques. The results find a significant positive effect of the level of corruption on the stock market index and the logarithm of capitalization. This is consistent with the view that corruption accelerates the economic growth by speeding up transactions and allowing private companies to overcome the inefficiencies imposed by the government. Furthermore, the results find a negative association is not significant with the dependent variable of traded value as a percentage of the number of listed companies.

scholarly journals Assessing the reaction of the Baltic stock market to the spread of the COVID-19 pandemic

2021 ◽  
Vol 25 ◽  
pp. 260-272
Author(s):  
Greta Keliuotyte-Staniuleniene ◽  
Julius Kviklis
Keyword(s):  
Stock Market ◽  
Impulse Response Functions ◽  
Cumulative Number ◽  
Response Functions ◽  
Stock Market Index ◽  
Market Index ◽  
Dependent Variables ◽  
The Baltic ◽  
The Impact ◽  
Research Period

This research aims to assess the impact of the spread of the COVID-19 pandemic on the Baltic stock market. To reach this aim, the methods of bivariate (OLS) regression and VAR-based impulse response functions are employed. We use daily new cases of COVID-19 as well as the cumulative number of COVID-19 cases as independent and OMX Baltic Benchmark GI index as dependent variables for our research. The research period, covering data from 2020 March 1st  to 2020 November 21st, is divided into three separate periods, reflecting the different phases of the spread of the COVID-19 pandemic. The results of the research revealed that the market reaction differs depending on the period; moreover, the Baltic stock market index was affected by new cases and total cases in a slightly different manner.

scholarly journals Daily Stock Movements Through the Lens of Event and News: Evidence from the Pakistan Stock Exchange

2021 ◽  
Author(s):  
Shahid Raza ◽  
Baiqing Sun ◽  
Pwint Kay Khine
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
News Daily ◽  
Stock Market Index ◽  
Daily Newspaper ◽  
Monthly Basis ◽  
Market Index ◽  
The Impact

This study will investigate different signals and events/news that determined the stock market's movements. As we know, many factors affect the stock market on a daily, weekly, and monthly basis, e.g., rate of interest, exchange rate, and oil prices, etc. Our research will investigate the impact of daily events/news in the KSE-100 index due to several policies announced and events/news in the country because the daily movements in the stock market can be determined only by different signals and events/news. Time series data is collected daily for particular reasons from "The News" (Daily Newspaper, Sunday edition) from 2010 to 2019. The results of this study show that political and global news affects the stock market index ferociously. For investors, the investment in blue chips is not less than a safe haven. When day-to-day transactions are concerned, there is always a higher panic attack than the herd behaviour in the stock exchange. Investors tend to make prompt responses to negative rather than positive news, which makes them risk averters. Our finding also confirmed that the ARCH/GARCH model is better than the simple OLS method concerning stock market upheaval.

scholarly journals Economic Interactions among Stock Market Performance and Macroeconomic Variables with Mediating Role of Gold Prices Volatilities: An Evidence from Pakistan

2021 ◽  
Vol 7 (3) ◽  
pp. 383-394
Author(s):  
Rukhsana Rasheed ◽  
Mazhar Nadeem Ishaq ◽  
Rabia Anwar ◽  
Mehwish Shahid
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Inflation Rate ◽  
Market Performance ◽  
Stock Market Index ◽  
Macroeconomic Variables ◽  
Market Index ◽  
Stock Market Performance ◽  
The Impact

In all emerging economies, one of the most challenging issues for investors is the multifaceted inter-relationship between volatility of gold prices and stock market index. During the COVID-19 sub-periods, gold has shown a strong hedging behavior against stock market performance. The main objective of this study was to quantify the long-run relationship among multiple independent macroeconomic variables (predictors) on stock market index (response variable) using the volatilities of gold prices as a mediator factor. This study applied the descriptive statistics, correlation, t-test and OLS multiple regression Model. The specific data comprised of period 2011-2020 regarding the fluctuations in gold prices, exchange rate, interest rate, inflation rate and performance of stock market index has been utilized. The statistical outputs of models showed that exchange rate (Dollar to PKR) was positively affecting the performance of Karachi Stock Exchange (KSE)-100 Index, whereas inflation rate and interest rate were negatively affecting the overall performance of KSE100 index. The findings of this study suggested that to achieve better performance of stock market, relatively low interest rate and inflation rate contribute a significant role. However, to increase the generalization capabilities of this study the impact of mentioned macroeconomic variables in other sectors like industrial production, oil & gas and energy sectors with wider time span can be more helpful.

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