This document summarizes a study that analyzed the reaction of Indian stock indices and investors to different categories of news announcements during the COVID-19 pandemic. The study identified 31 days with extreme stock market returns between February 2020 and June 2021. It grouped the news from those days into 4 categories and examined the reaction of indices like the BSE Sensex and investors like clients, FIIs, and DIIs. The results found a statistically significant difference between the two news announcement groups for stock indices but not for investors. Most of the return series were found to be random, and no day-of-the-week effect was found for investor investment patterns. The impact of negative COVID-19 news was reduced by government interventions, and stock market
Stock market volatility and macroeconomic variables volatility in nigeria an ...Alexander Decker
This document summarizes a study that examines the relationship between stock market volatility and macroeconomic variable volatility in Nigeria from 1986 to 2010. The study uses an EGARCH model to estimate volatility and a LA-VAR Granger causality test to analyze the nexus between stock market volatility and macroeconomic variables. The results found evidence of a bi-causal relationship between stock market volatility and real GDP volatility, and no causal relationship between stock market volatility and interest rate or inflation rate volatility.
This study investigates the impact of scheduled US macroeconomic news announcements on the risk and returns of the US bond, stock, and foreign exchange markets from 1986 to 1998. The authors find that the markets do not respond to just the release of information, but rather to the "news content" - the difference between the actual announcement and expectations. Unexpected balance of trade news had the largest impact on foreign exchange returns, while domestic economic news most affected bonds and inflation news influenced stocks. Volatility responded differently to different announcements, which the authors attribute to varying "policy feedback" effects.
Forecasting real economic growth by using the information contents of financial asset prices is one of the main themes in financial studies in recent years. Based on the micro-level stock data from Shenzhen Stock Exchange Market, the paper constructs a cross-section volatility measure using sample stocks, investigates the impact of stock price volatility on economic growth, and forecasts economic growth with stock prices volatility of different firm size. The empirical results indicate that stock price volatility is a good indicator for forecasting economic growth. The results also show that volatility of both large and small firms can be useful in forecasting economic growth. In addition, volatility of small firms can better predict economic growth.
Market efficiency, market anomalies, causes, evidences, and some behavioral a...Alexander Decker
This document discusses market anomalies and the efficient market hypothesis. It provides definitions of market efficiency, forms of market efficiency including weak, semi-strong, and strong forms. It then defines market anomalies as deviations from expected market behavior that cannot be explained by market efficiency. The document categorizes anomalies into fundamental anomalies, technical anomalies, and calendar or seasonal anomalies. It provides examples of calendar anomalies such as the weekend effect and turn-of-the-month effect, and discusses previous studies that have found evidence of these anomalies in various stock markets. The document aims to review market anomalies and discuss their possible causes from both market efficiency and behavioral finance perspectives.
Stock market anomalies a study of seasonal effects on average returns of nair...Alexander Decker
This document summarizes a research study that examines seasonal effects (anomalies) on stock returns in the Nairobi Securities Exchange (NSE) in Kenya. Specifically, it analyzes the day of the week effect, weekend effect, and monthly effect. The study tests hypotheses about whether average returns differ by day of the week or month. It reviews previous literature documenting calendar anomalies in other stock markets. The conceptual framework focuses on analyzing the three seasonal effects. The study uses 12 years of daily closing price data for NSE indices to test the hypotheses and determine if the NSE exhibits calendar anomalies.
Analysis of Stock Market Anomalies worldwide Aanchal Saxena
This document discusses calendar anomalies in stock markets, including the January effect, time of month effect, turn of month effect, day of week effect, and holiday effect. It analyzes evidence of these anomalies in both developed and emerging markets. While some strategies could exploit certain anomalies in the short term, the document concludes that consistently beating the market using anomalies is difficult. Anomalies vary over time and between markets. It is risky to base investment strategies solely on calendar effects due to the challenges of predicting market 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.
Stock market volatility and macroeconomic variables volatility in nigeria an ...Alexander Decker
This document summarizes a study that examines the relationship between stock market volatility and macroeconomic variable volatility in Nigeria from 1986 to 2010. The study uses an EGARCH model to estimate volatility and a LA-VAR Granger causality test to analyze the nexus between stock market volatility and macroeconomic variables. The results found evidence of a bi-causal relationship between stock market volatility and real GDP volatility, and no causal relationship between stock market volatility and interest rate or inflation rate volatility.
This study investigates the impact of scheduled US macroeconomic news announcements on the risk and returns of the US bond, stock, and foreign exchange markets from 1986 to 1998. The authors find that the markets do not respond to just the release of information, but rather to the "news content" - the difference between the actual announcement and expectations. Unexpected balance of trade news had the largest impact on foreign exchange returns, while domestic economic news most affected bonds and inflation news influenced stocks. Volatility responded differently to different announcements, which the authors attribute to varying "policy feedback" effects.
Forecasting real economic growth by using the information contents of financial asset prices is one of the main themes in financial studies in recent years. Based on the micro-level stock data from Shenzhen Stock Exchange Market, the paper constructs a cross-section volatility measure using sample stocks, investigates the impact of stock price volatility on economic growth, and forecasts economic growth with stock prices volatility of different firm size. The empirical results indicate that stock price volatility is a good indicator for forecasting economic growth. The results also show that volatility of both large and small firms can be useful in forecasting economic growth. In addition, volatility of small firms can better predict economic growth.
Market efficiency, market anomalies, causes, evidences, and some behavioral a...Alexander Decker
This document discusses market anomalies and the efficient market hypothesis. It provides definitions of market efficiency, forms of market efficiency including weak, semi-strong, and strong forms. It then defines market anomalies as deviations from expected market behavior that cannot be explained by market efficiency. The document categorizes anomalies into fundamental anomalies, technical anomalies, and calendar or seasonal anomalies. It provides examples of calendar anomalies such as the weekend effect and turn-of-the-month effect, and discusses previous studies that have found evidence of these anomalies in various stock markets. The document aims to review market anomalies and discuss their possible causes from both market efficiency and behavioral finance perspectives.
Stock market anomalies a study of seasonal effects on average returns of nair...Alexander Decker
This document summarizes a research study that examines seasonal effects (anomalies) on stock returns in the Nairobi Securities Exchange (NSE) in Kenya. Specifically, it analyzes the day of the week effect, weekend effect, and monthly effect. The study tests hypotheses about whether average returns differ by day of the week or month. It reviews previous literature documenting calendar anomalies in other stock markets. The conceptual framework focuses on analyzing the three seasonal effects. The study uses 12 years of daily closing price data for NSE indices to test the hypotheses and determine if the NSE exhibits calendar anomalies.
Analysis of Stock Market Anomalies worldwide Aanchal Saxena
This document discusses calendar anomalies in stock markets, including the January effect, time of month effect, turn of month effect, day of week effect, and holiday effect. It analyzes evidence of these anomalies in both developed and emerging markets. While some strategies could exploit certain anomalies in the short term, the document concludes that consistently beating the market using anomalies is difficult. Anomalies vary over time and between markets. It is risky to base investment strategies solely on calendar effects due to the challenges of predicting market 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.
This document discusses whether stock markets promote economic growth. It begins by outlining the debate on whether financial development causes growth or vice versa. The authors then:
1) Describe previous empirical studies on the relationship between financial development/stock markets and economic growth that have limitations in establishing causality.
2) Explain their use of Granger causality tests on data from 64 countries over varying time periods to help determine the causal direction of the relationship.
3) Present sample statistics showing differences in growth rates and financial development across income levels and degrees of financial market freedom.
This document summarizes a study examining the relationship between inflation and economic growth in Ethiopia from 2000 to 2019. The study used time series data and various econometric tests including unit root tests, cointegration tests, and Granger causality tests. The results found that inflation and economic growth were cointegrated, indicating a long-run relationship. However, the Granger causality tests found no evidence that either inflation or economic growth Granger causes the other, suggesting their influence is contemporaneous. The document provides context on debates around the relationship between inflation and growth and reviews related literature, finding mixed results on the nature and direction of the relationship in different countries and time periods.
This document summarizes a research journal article that examines the determinants of fiscal growth in Jordan. The study uses time series data from 1982-2010 to analyze the relationships between fiscal growth rates and several independent variables, including available liquidity in banking, private sector credit rates, stock market capitalization, and government fiscal policy. The study found positive statistical relationships between fiscal growth and the first three variables, but did not prove an impact of fiscal policy. It recommends policies to encourage bank mergers, intellectual property rights, and coordinating fiscal and monetary policies to link them with economic growth.
The Effect of Real Exchange Rate on Economic DevelopmentBatola David
Interest rate is a closely watched variable in the economy, their movements are reported almost daily by news media because they directly affect our everyday lives and have important consequence for the health of the economy and it is important macroeconomic variables for economic growth, they affect personal decisions such as whether to consume or to save, whether to buy a house and whether to purchase bonds or put funds into a saving account. This paper investigates the effects of real exchange rate on economic growth in Ghana over the period 1975 to 2015 using quarterly time series data. Specifically, it examines the extent to which real exchange rate has on the growth rates of the country reflecting real GDP, inflation rate and interest. The study, therefore, employs the co-integration analysis within the framework of Vector Autoregressive (VAR) to empirically investigate the effects of real exchange rate on real GDP growth in the country.
Testing for fisher’s hypothesis in nigeria (1970 2012)Alexander Decker
This document summarizes a study that tested Fisher's hypothesis in Nigeria between 1970-2012. The study used quarterly data on interest rates and inflation rates to examine the causal relationship between the two variables. It employed cointegration and Granger causality tests and found that:
1) There is no significant long-run relationship between interest and inflation rates, violating Fisher's hypothesis in the long-run.
2) In the short-run, there is no causal link from interest rates to inflation, but there is a causal link from inflation to interest rates, supporting Fisher's hypothesis.
3) Fisher's hypothesis that nominal interest rates consist of expected inflation plus a real interest rate component is validated in the short-run
Equity analaysi on macro economics factor of selectied securityMohitAgarwal312
This document provides an analysis of equity shares in selected Indian industries. It examines daily closing prices of companies in sectors like automobile, banking, IT, oil and gas, and telecom. Technical indicators like simple moving averages, money flow index, and relative strength index are applied to identify buy/sell signals and analyze trends. The analysis finds that some stocks like State Bank of India are oversold and poised for an upturn, while others like Maruti Suzuki may need more confirmation of a trend reversal before being a good investment. The study aims to help investors understand stock behavior and make better decisions.
A survey of day of the month effect in world stock markets 2IAEME Publication
This document summarizes a research article published in the International Journal of Management in 2013. The article examines the "day of the month effect" in the daily stock market returns of 11 stock markets around the world. It finds statistical evidence that some days of the month have historically delivered significantly higher returns than other days in all of the markets tested.
This document provides an economic update on Thailand for December 2010 and January 2011. Some key points:
1) In December, several Thai economic indicators showed signs of moderation from November, though farm income continued expanding, which will support future consumption.
2) Manufacturing growth decelerated in December, while private investment and consumption were flat for the month. Business sentiment remained concerned about rising costs.
3) In January, headline inflation stayed at 3.0% but core inflation edged down, while food and energy were the main drivers of higher prices. Producer price inflation was unchanged at 6.0%.
A sectoral analysis of inflation hedging properties of common stocksAlexander Decker
This summary provides an overview of a research journal article that analyzes the inflation-hedging properties of stocks in the engineering technology, computer/office equipment, and printing/publishing sectors listed on the Nigerian Stock Exchange from 2000-2011. The study finds that while the stocks provided positive real returns based on shareholders' funds and total equity returns, they did not significantly hedge against inflation when considering dividend yields. Traditional hedges like commodities and real estate may not be as effective in modern markets. New financial instruments like derivatives and other exotic investments have emerged as potential inflation hedges, though each asset class has unique risk-return characteristics.
Vietnam financial service industries are growing and contributing much to the economic development and has been affected by inflation. High and increasing inflation might reduce values of insurance and banking contracts. This paper measures the volatility of market risk in Viet Nam banking, insurance and stock investment industry after this period (2015-2017). The main reason is the necessary role of the financial system in Vietnam in the economic development and growth in recent years always go with risk potential and risk control policies. This research paper aims to figure out how much increase or decrease in the market risk of Vietnam banking, insurance and stock investment firms during the post-low inflation environment 2015-2017, compared to what happened in the financial crisis 2007-2009.First, by using quantitative combined with comparative data analysis method, we find out the risk level measured by equity beta mean in the banking industry has increased whereas the risk fluctuation also increased. Second, stock investment industry has the level of market risk as well as the risk fluctuation decreasing. Third, different from the 2 above industries, insurance industry experienced the level of market risk increasing while the risk volatility decreasing. Then, one of its major findings is the comparison between risk level of stock investment industry during the financial crisis 2007-2009 compared to those in the post-low inflation time 2015-2017. During the financial crisis 2007-09, stock industry has the highest beta value whereas during the post-low inflation time, banking industry maintained the highest value. Finally, this paper provides some ideas that could provide companies and government more evidence in establishing their policies in governance. This is the complex task but the research results shows us warning that the market risk need to be controlled better during the post-low inflation period 2015-2017. And our conclusion part will recommends some policies and plans to deal with it.
Ivo Pezzuto - "FED BITES THE BULLET - Implements First Rate Hike in Nearly a ...Dr. Ivo Pezzuto
The US Federal Reserve finally bites the bullet, increasing the
FFR – a key short-term interest rate – by quarter of a per cent.
With this, the regulator has clearly signaled that it might take
similar actions in future, if need arises, to take the economy
towards full recovery.
The objective of this study is to identify the determinants of inflation in West Africa, mainly in the WAEMU zone, in order to contribute to improving the conduct of monetary policy. The equation of the exchange of the Quantitative Theory of the Currency and the generalized method of moments (MMG) in dynamic panel is used. Annual data concerning six countries in West Africa and range from 1991 to 2015. The results of the estimation show that in addition to the economic growth rate and the money supply, the devaluation has a significant effect on inflation. As we can see, inflation is not systematically a monetary phenomenon in West Africa. The authorities must therefore seek to determine the optimal threshold for the rate of increase of the money supply.
Economic and Financial Analysis of Real Estate / REIT Industry (2014 Class Pr...Alexander M. Stearns
In April 2014, I evaluated the economic and real estate industry conditions and compared the merits of 4 real estate investment trust (REIT) securities through business life cycles, key financials, and DuPont analysis. Attached is a 14p. sample of the 40p. report.
What happens if the us credit rating is downgraded 7.22.2021 - Kurt S. Altric...Kurt S. Altrichter
1) The US government debt level of nearly $30 trillion poses risks even though low interest rates have kept debt servicing costs low currently. The upcoming expiration of the debt ceiling raises the possibility of a downgrade in the US credit rating or a technical default.
2) A credit downgrade or hitting the debt ceiling without a resolution could negatively impact risk assets, as occurred in 2011. Investors should take a longer term view and pay attention to weakening economic fundamentals rather than just focusing on record high stock markets.
3) The options available to address the growing debt problem like raising taxes or interest rates all carry risks for either the economy, financial markets or the US dollar. The government appears backed into a corner with
This document describes a study that analyzes the effects of fiscal policy shocks using a vector autoregression (VAR) model that accounts for the level of public debt. It notes that existing empirical studies using VAR models omit how taxes, spending, and interest rates respond to debt levels. This can result in biased estimates of fiscal shock effects. The study uses quarterly US data from 1960-2006 in a VAR that includes public debt and the government budget constraint. It finds the impulse responses from this model differ from those of standard VAR models that omit the debt level. The path of debt implied by the two models also differs.
1.[1 14]the impact of macroeconomic indicators on stock prices in nigeriaAlexander Decker
This document summarizes a study that examines the impact of macroeconomic indicators on stock prices in Nigeria. The study uses secondary data on stock prices of selected firms and six macroeconomic variables between 1985 and 2009. The macroeconomic variables examined are money supply, interest rate, exchange rate, inflation rate, oil price, and gross domestic product. A pooled or panel model is used to analyze the impact of these macroeconomic variables on stock prices at the individual firm level. The empirical findings reveal that macroeconomic variables have varying significant impacts on stock prices, with inflation rate and money supply having no significant impact. The study concludes that trends in macroeconomic variables can predict stock price movements in Nigeria to a great extent.
11.the impact of macroeconomic indicators on stock prices in nigeriaAlexander Decker
This document summarizes a study that examines the impact of macroeconomic indicators on stock prices in Nigeria. The study uses secondary data on stock prices of selected firms and six macroeconomic variables between 1985 and 2009. The macroeconomic variables examined are money supply, interest rate, exchange rate, inflation rate, oil price, and gross domestic product. A pooled or panel model is used to analyze the impact of these macroeconomic variables on stock prices at the individual firm level. The empirical findings reveal that macroeconomic variables have varying significant impacts on stock prices, with inflation rate and money supply having no significant impact. The study concludes that trends in macroeconomic variables can predict stock price movements in Nigeria to a great extent.
The present commentary discusses how past bad policy choices of Canada's central bank have tied its hands to manage the inflation crisis of 2022. The price level has been disconnected from the realities of the economic conditions prevailing in the macroeconomy. Given the low-price level, the bank has been lowering its policy rate since the 1990s. And now it finds itself stuck in a low-rate trap that it can't increase the rate even if current inflationary pressure demands so. If it increases its policy rate to manage the inflation crisis, it may create another crisis(es) in the process – asset crisis, debt crisis, and/or systemic crisis. What to choose, whether inflation crisis or other(s)? It appears to be in a fix.
LQ 45 CAPITAL MARKET REACTION SPEED DURING COVID-19 PANDEMICAJHSSR Journal
ABSTRACT : The study explored the speed of market reaction on the LQ-45 index on the Indonesia Stock
Exchange before and after the Covid-19 pandemic eventthe estimation period is generally the period before the
event period carried out using the estimation period for 60 days before the event day. The reason for taking the
research period (event period) t-3 and t4 or in this study t-5 and T+5 is to avoid any confounding effect due to the
announcement of stock splits, mergers, and rights issues.The results of the study using the event study approach
in the Covid-19 pandemic event show that this event has information content, the reaction is shown by changes
in the price of securities, this is shown by an abnormal increase in stock returns during the pandemic. This can be
seen from T-5 to T-0 which moves in a volatile manner. But at the time of t + 2 experienced a drastic increase to
t+5.Based on the results of the analysis and testing that has been done previously, there are several things that can
be concluded that there are significant differences in lq45 stock prices and stock returns before and after the
National announcement of the Covid-19 outbreak. The existence of Covid-19 cases in Indonesia caused the stock
price to decline, it was certainly offset by a decrease in the value of stock returns.
KEYWORDS: Reaction speed, LQ-45, Covid-19, Event Study, Abnormal return
Sector Wise Stock Market Performance during Pre and Post Covid EraDr. Amarjeet Singh
The spread of the Covid-19 pandemic has an unprecedented and immense impact on the world economy as well as the Indian economy. The stock market, treated as a barometer of the economic activity of any country is adversely affected. Not even in India, countries like Germany, France, the USA, and Spain have been strongly affected. Nationwide lockdown, restriction on the transportation system, demand-supply disequilibrium lead to slow down in the economy and create a fear factor among the participants of the capital market. Rapid fall in the share price and increased volatility are identified during this period. The present study tries to compare the stock price return volatility, no of the transaction, and delivery percentage of various listed companies listed on BSE during the pre and post COVID 19 periods to examine the effect of this pandemic on the economy as a whole.
Impact of corona virus on Indian economy ruchi saini
The document discusses the impact of the COVID-19 pandemic on the Indian economy. It summarizes that the Indian economy was already weak before the pandemic and lockdowns have further slowed growth significantly. The stock market initially crashed but has since rebounded somewhat on hopes of stimulus measures and peaking infection rates. Key sectors impacted include aviation, textiles, finance, MSMEs and more. The paper analyzes the situation pre- and post-crisis and effects on GDP, unemployment and various sectors.
This document summarizes a study that examines the impact of Covid-19 on stock price movements in Indonesia. It analyzes stock prices before and after four Covid-19 related events: the Wuhan lockdown, Italy lockdown, confirmation of the first Covid-19 case in Indonesia, and the implementation of large-scale social restrictions. The study finds a difference in abnormal stock returns before and after the large-scale social restrictions event but no differences for the other three events. It uses an event study methodology and secondary stock price and news data to conduct the analysis.
This document discusses whether stock markets promote economic growth. It begins by outlining the debate on whether financial development causes growth or vice versa. The authors then:
1) Describe previous empirical studies on the relationship between financial development/stock markets and economic growth that have limitations in establishing causality.
2) Explain their use of Granger causality tests on data from 64 countries over varying time periods to help determine the causal direction of the relationship.
3) Present sample statistics showing differences in growth rates and financial development across income levels and degrees of financial market freedom.
This document summarizes a study examining the relationship between inflation and economic growth in Ethiopia from 2000 to 2019. The study used time series data and various econometric tests including unit root tests, cointegration tests, and Granger causality tests. The results found that inflation and economic growth were cointegrated, indicating a long-run relationship. However, the Granger causality tests found no evidence that either inflation or economic growth Granger causes the other, suggesting their influence is contemporaneous. The document provides context on debates around the relationship between inflation and growth and reviews related literature, finding mixed results on the nature and direction of the relationship in different countries and time periods.
This document summarizes a research journal article that examines the determinants of fiscal growth in Jordan. The study uses time series data from 1982-2010 to analyze the relationships between fiscal growth rates and several independent variables, including available liquidity in banking, private sector credit rates, stock market capitalization, and government fiscal policy. The study found positive statistical relationships between fiscal growth and the first three variables, but did not prove an impact of fiscal policy. It recommends policies to encourage bank mergers, intellectual property rights, and coordinating fiscal and monetary policies to link them with economic growth.
The Effect of Real Exchange Rate on Economic DevelopmentBatola David
Interest rate is a closely watched variable in the economy, their movements are reported almost daily by news media because they directly affect our everyday lives and have important consequence for the health of the economy and it is important macroeconomic variables for economic growth, they affect personal decisions such as whether to consume or to save, whether to buy a house and whether to purchase bonds or put funds into a saving account. This paper investigates the effects of real exchange rate on economic growth in Ghana over the period 1975 to 2015 using quarterly time series data. Specifically, it examines the extent to which real exchange rate has on the growth rates of the country reflecting real GDP, inflation rate and interest. The study, therefore, employs the co-integration analysis within the framework of Vector Autoregressive (VAR) to empirically investigate the effects of real exchange rate on real GDP growth in the country.
Testing for fisher’s hypothesis in nigeria (1970 2012)Alexander Decker
This document summarizes a study that tested Fisher's hypothesis in Nigeria between 1970-2012. The study used quarterly data on interest rates and inflation rates to examine the causal relationship between the two variables. It employed cointegration and Granger causality tests and found that:
1) There is no significant long-run relationship between interest and inflation rates, violating Fisher's hypothesis in the long-run.
2) In the short-run, there is no causal link from interest rates to inflation, but there is a causal link from inflation to interest rates, supporting Fisher's hypothesis.
3) Fisher's hypothesis that nominal interest rates consist of expected inflation plus a real interest rate component is validated in the short-run
Equity analaysi on macro economics factor of selectied securityMohitAgarwal312
This document provides an analysis of equity shares in selected Indian industries. It examines daily closing prices of companies in sectors like automobile, banking, IT, oil and gas, and telecom. Technical indicators like simple moving averages, money flow index, and relative strength index are applied to identify buy/sell signals and analyze trends. The analysis finds that some stocks like State Bank of India are oversold and poised for an upturn, while others like Maruti Suzuki may need more confirmation of a trend reversal before being a good investment. The study aims to help investors understand stock behavior and make better decisions.
A survey of day of the month effect in world stock markets 2IAEME Publication
This document summarizes a research article published in the International Journal of Management in 2013. The article examines the "day of the month effect" in the daily stock market returns of 11 stock markets around the world. It finds statistical evidence that some days of the month have historically delivered significantly higher returns than other days in all of the markets tested.
This document provides an economic update on Thailand for December 2010 and January 2011. Some key points:
1) In December, several Thai economic indicators showed signs of moderation from November, though farm income continued expanding, which will support future consumption.
2) Manufacturing growth decelerated in December, while private investment and consumption were flat for the month. Business sentiment remained concerned about rising costs.
3) In January, headline inflation stayed at 3.0% but core inflation edged down, while food and energy were the main drivers of higher prices. Producer price inflation was unchanged at 6.0%.
A sectoral analysis of inflation hedging properties of common stocksAlexander Decker
This summary provides an overview of a research journal article that analyzes the inflation-hedging properties of stocks in the engineering technology, computer/office equipment, and printing/publishing sectors listed on the Nigerian Stock Exchange from 2000-2011. The study finds that while the stocks provided positive real returns based on shareholders' funds and total equity returns, they did not significantly hedge against inflation when considering dividend yields. Traditional hedges like commodities and real estate may not be as effective in modern markets. New financial instruments like derivatives and other exotic investments have emerged as potential inflation hedges, though each asset class has unique risk-return characteristics.
Vietnam financial service industries are growing and contributing much to the economic development and has been affected by inflation. High and increasing inflation might reduce values of insurance and banking contracts. This paper measures the volatility of market risk in Viet Nam banking, insurance and stock investment industry after this period (2015-2017). The main reason is the necessary role of the financial system in Vietnam in the economic development and growth in recent years always go with risk potential and risk control policies. This research paper aims to figure out how much increase or decrease in the market risk of Vietnam banking, insurance and stock investment firms during the post-low inflation environment 2015-2017, compared to what happened in the financial crisis 2007-2009.First, by using quantitative combined with comparative data analysis method, we find out the risk level measured by equity beta mean in the banking industry has increased whereas the risk fluctuation also increased. Second, stock investment industry has the level of market risk as well as the risk fluctuation decreasing. Third, different from the 2 above industries, insurance industry experienced the level of market risk increasing while the risk volatility decreasing. Then, one of its major findings is the comparison between risk level of stock investment industry during the financial crisis 2007-2009 compared to those in the post-low inflation time 2015-2017. During the financial crisis 2007-09, stock industry has the highest beta value whereas during the post-low inflation time, banking industry maintained the highest value. Finally, this paper provides some ideas that could provide companies and government more evidence in establishing their policies in governance. This is the complex task but the research results shows us warning that the market risk need to be controlled better during the post-low inflation period 2015-2017. And our conclusion part will recommends some policies and plans to deal with it.
Ivo Pezzuto - "FED BITES THE BULLET - Implements First Rate Hike in Nearly a ...Dr. Ivo Pezzuto
The US Federal Reserve finally bites the bullet, increasing the
FFR – a key short-term interest rate – by quarter of a per cent.
With this, the regulator has clearly signaled that it might take
similar actions in future, if need arises, to take the economy
towards full recovery.
The objective of this study is to identify the determinants of inflation in West Africa, mainly in the WAEMU zone, in order to contribute to improving the conduct of monetary policy. The equation of the exchange of the Quantitative Theory of the Currency and the generalized method of moments (MMG) in dynamic panel is used. Annual data concerning six countries in West Africa and range from 1991 to 2015. The results of the estimation show that in addition to the economic growth rate and the money supply, the devaluation has a significant effect on inflation. As we can see, inflation is not systematically a monetary phenomenon in West Africa. The authorities must therefore seek to determine the optimal threshold for the rate of increase of the money supply.
Economic and Financial Analysis of Real Estate / REIT Industry (2014 Class Pr...Alexander M. Stearns
In April 2014, I evaluated the economic and real estate industry conditions and compared the merits of 4 real estate investment trust (REIT) securities through business life cycles, key financials, and DuPont analysis. Attached is a 14p. sample of the 40p. report.
What happens if the us credit rating is downgraded 7.22.2021 - Kurt S. Altric...Kurt S. Altrichter
1) The US government debt level of nearly $30 trillion poses risks even though low interest rates have kept debt servicing costs low currently. The upcoming expiration of the debt ceiling raises the possibility of a downgrade in the US credit rating or a technical default.
2) A credit downgrade or hitting the debt ceiling without a resolution could negatively impact risk assets, as occurred in 2011. Investors should take a longer term view and pay attention to weakening economic fundamentals rather than just focusing on record high stock markets.
3) The options available to address the growing debt problem like raising taxes or interest rates all carry risks for either the economy, financial markets or the US dollar. The government appears backed into a corner with
This document describes a study that analyzes the effects of fiscal policy shocks using a vector autoregression (VAR) model that accounts for the level of public debt. It notes that existing empirical studies using VAR models omit how taxes, spending, and interest rates respond to debt levels. This can result in biased estimates of fiscal shock effects. The study uses quarterly US data from 1960-2006 in a VAR that includes public debt and the government budget constraint. It finds the impulse responses from this model differ from those of standard VAR models that omit the debt level. The path of debt implied by the two models also differs.
1.[1 14]the impact of macroeconomic indicators on stock prices in nigeriaAlexander Decker
This document summarizes a study that examines the impact of macroeconomic indicators on stock prices in Nigeria. The study uses secondary data on stock prices of selected firms and six macroeconomic variables between 1985 and 2009. The macroeconomic variables examined are money supply, interest rate, exchange rate, inflation rate, oil price, and gross domestic product. A pooled or panel model is used to analyze the impact of these macroeconomic variables on stock prices at the individual firm level. The empirical findings reveal that macroeconomic variables have varying significant impacts on stock prices, with inflation rate and money supply having no significant impact. The study concludes that trends in macroeconomic variables can predict stock price movements in Nigeria to a great extent.
11.the impact of macroeconomic indicators on stock prices in nigeriaAlexander Decker
This document summarizes a study that examines the impact of macroeconomic indicators on stock prices in Nigeria. The study uses secondary data on stock prices of selected firms and six macroeconomic variables between 1985 and 2009. The macroeconomic variables examined are money supply, interest rate, exchange rate, inflation rate, oil price, and gross domestic product. A pooled or panel model is used to analyze the impact of these macroeconomic variables on stock prices at the individual firm level. The empirical findings reveal that macroeconomic variables have varying significant impacts on stock prices, with inflation rate and money supply having no significant impact. The study concludes that trends in macroeconomic variables can predict stock price movements in Nigeria to a great extent.
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LQ 45 CAPITAL MARKET REACTION SPEED DURING COVID-19 PANDEMICAJHSSR Journal
ABSTRACT : The study explored the speed of market reaction on the LQ-45 index on the Indonesia Stock
Exchange before and after the Covid-19 pandemic eventthe estimation period is generally the period before the
event period carried out using the estimation period for 60 days before the event day. The reason for taking the
research period (event period) t-3 and t4 or in this study t-5 and T+5 is to avoid any confounding effect due to the
announcement of stock splits, mergers, and rights issues.The results of the study using the event study approach
in the Covid-19 pandemic event show that this event has information content, the reaction is shown by changes
in the price of securities, this is shown by an abnormal increase in stock returns during the pandemic. This can be
seen from T-5 to T-0 which moves in a volatile manner. But at the time of t + 2 experienced a drastic increase to
t+5.Based on the results of the analysis and testing that has been done previously, there are several things that can
be concluded that there are significant differences in lq45 stock prices and stock returns before and after the
National announcement of the Covid-19 outbreak. The existence of Covid-19 cases in Indonesia caused the stock
price to decline, it was certainly offset by a decrease in the value of stock returns.
KEYWORDS: Reaction speed, LQ-45, Covid-19, Event Study, Abnormal return
Sector Wise Stock Market Performance during Pre and Post Covid EraDr. Amarjeet Singh
The spread of the Covid-19 pandemic has an unprecedented and immense impact on the world economy as well as the Indian economy. The stock market, treated as a barometer of the economic activity of any country is adversely affected. Not even in India, countries like Germany, France, the USA, and Spain have been strongly affected. Nationwide lockdown, restriction on the transportation system, demand-supply disequilibrium lead to slow down in the economy and create a fear factor among the participants of the capital market. Rapid fall in the share price and increased volatility are identified during this period. The present study tries to compare the stock price return volatility, no of the transaction, and delivery percentage of various listed companies listed on BSE during the pre and post COVID 19 periods to examine the effect of this pandemic on the economy as a whole.
Impact of corona virus on Indian economy ruchi saini
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This document summarizes a study that examines the impact of Covid-19 on stock price movements in Indonesia. It analyzes stock prices before and after four Covid-19 related events: the Wuhan lockdown, Italy lockdown, confirmation of the first Covid-19 case in Indonesia, and the implementation of large-scale social restrictions. The study finds a difference in abnormal stock returns before and after the large-scale social restrictions event but no differences for the other three events. It uses an event study methodology and secondary stock price and news data to conduct the analysis.
This document summarizes a research paper that analyzes the resilience of ESG, sharia compliant, and sin stocks during the COVID-19 pandemic and 2007-08 financial crisis. It begins with an introduction that outlines the research questions, objectives and significance. The introduction discusses how previous literature has found these types of stocks to exhibit lower volatility, higher resilience and abnormal returns during economic downturns. Subsequent chapters will analyze the resilience, return volatility and abnormal returns of these stock types specifically after the two crises.
Stock Market Analysis of 10 Different Countries in the Period of Disease COVI...Dr. Amarjeet Singh
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The essential variables to consider before investing in financial markets dur...AI Publications
The current study aimed to investigate the essential factors to be taking into consideration prior starting an investment in financial markets especially during Covid-19 era. Individual investors are those who make purchases of securities on behalf of other individuals. Most of the time, these investors trade in modest quantities and are primarily interested in the operations of the stock exchange. Quantitative method used in this study to analyze data. The researcher used a questionnaire and distributed in four banks in Erbil city. The researcher used random sampling method in order to gather data from private banks in Erbil city. The population of this study was approximately 210 units. The target population was 142 units. The researcher distrusted 150 questionnaires at four different private banks, from 150 questionnaires; the researcher was able to gather 128 questionnaires that have been completed properly. Accordingly, the sample size of this study was 128 units.The questionnaire was designed in a multiple choise quesirons. The respondents were asked to mark each question on five scales ranging from strongly disagree to strongly agree. The findings revealed that, in terms of first research hypothesis, economnic growthhas significantly predicted financial markets, this indicates that economnic growthwill have a direct positive impact on financial markets. In terms of second research hypothesis, employment patternshas significantly predicted financial markets, this indicates that differnation strategy will have a weak positive impact on financial markets, and in terms of third research hypothesis, demographic trendshas significantly predicted financial markets, this indicates that demographic trendswill have a weak positive impact on financial markets.
The document discusses how media coverage, especially in newspapers like the Wall Street Journal, can influence investors' behavior and financial markets. It reviews literature showing that the content and tone of news coverage can shape investors' perceptions and that emphasizing certain stocks can increase attention and trading of those stocks. The media plays a role in both passively reporting information and actively expressing opinions that guide investment decisions. The way the media distributes and frames news stories has been shown to impact stock prices, trading volumes, and returns through influencing investors' attention and sentiment.
48 variable macroeconomics on stock return 25 ags 2019Aminullah Assagaf
This study examines the effect of macroeconomic variables (inflation, interest rates, money supply, exchange rates) on stock returns of companies listed on the Indonesia Stock Exchange from November 2016 to June 2018. Using multiple linear regression analysis on monthly data, the study found that macroeconomic variables have a significant effect on stock returns. Specifically, changes in inflation rates, interest rates, money supply, and the Rupiah exchange rate influence the overall stock price index and company stock returns in Indonesia. The results indicate macroeconomic conditions impact stock market performance.
Empirical Methods In Accounting And Finance.docx4934bk
This document discusses several studies on the relationship between investor sentiment and the mean-variance relationship in stock markets. It summarizes the key findings of various papers, including that investor sentiment can undermine the positive relationship between risk and return during high sentiment periods. Principal component analysis and GARCH models are used to analyze the impact of sentiment on markets. The results show sentiment has a significant effect and that the relationship varies across different markets and sentiment states.
The problems in this study are the decrease in the share price and the increase in the volume
of stock transactions in BUMN listed in LQ45 as well as the number of positive confirmed …
CAPITAL MARKET DEVELOPMENT AND INFLATION IN NIGERIAAJHSSR Journal
ABSTRACT :This study examined the impact of inflation and capital market development in Nigeria. The
ultimate objective of the study is centered on an empirical investigation of inflation and its impact on the growth
of the Nigerian capital market, and also the trend of inflation and capital market development in Nigeria. In
order to achieve these objectives, the study used tables and graphs to examine the trend of inflation and capital
market development in Nigeria. Augmented Dickey Fuller unit root test was used to check the behavior of data,
and the ARDL bound test was used to check if variables are cointegrated. Post estimation test which includes
the serial correlation, heteroskedasticity and the histogram normality test was also conducted. Data were
collected from secondary sources, such as central bank of Nigeria statistical bulletin and the world development
indicator. The unit root test revealed that the financial sector, financial intermediaries and interest rate were
stationary at levels but exchange rate, inflation, government spending and trade openness became stationary
after the first difference. Empirical findings confirmed that there is a statistically significant long- and short-run
negative effect of inflation on capital market development. On the contrary, economic growth has a statistically
significant long- and short-run positive impact on capital market performance. In addition, results confirmed
that there is positive support of the previous financial sector policies on capital market performance in the
current period.
7 corporate hospital research paper publishedin international journalmaaranhari
1) The document discusses the financial impact of the COVID-19 pandemic on various industries and the global economy. It analyzes data on GDP growth and performance of different sectors in countries like the US, China, Japan, and India.
2) Certain industries like pharmaceuticals, online education, and sanitization products have grown during the pandemic while sectors like banking, finance, and real estate have been negatively impacted.
3) While short term growth is expected to be low, most industries and the overall economy are predicted to recover in the long run as lockdowns ease and consumption increases again. However, the full impact will vary across countries and sectors.
1) The document discusses the financial impact of the COVID-19 pandemic on various industries and the global economy. It analyzes data on GDP growth and performance of different sectors in countries like the US, China, Japan, and India.
2) Certain industries like pharmaceuticals, online education, and sanitization products have grown during the pandemic while sectors like banking, finance, and real estate have been hit hard.
3) While short term economic growth is expected to be low, it is estimated that GDP and growth rates will start increasing again from the third quarter of 2021 as impacts of the pandemic subside. The Indian economy has been less affected than others but some industries have seen major financial impacts.
1) The document discusses the financial impact of the COVID-19 pandemic on various industries and the global economy. It analyzes data on GDP growth and performance of different sectors in countries like the US, China, Japan, and India.
2) Certain industries like pharmaceuticals, online education, and sanitization products have grown during the pandemic while sectors like banking, financial services, and real estate have been negatively impacted.
3) While short-term economic growth is expected to remain low, it is estimated that GDP and growth rates will start increasing again from the third quarter of 2021 as impacts of the pandemic subside. The document concludes that though some industries have been severely affected, others have performed well and are expected to
Effect of Changes in Earning on Stock Prices of Listed Healthcare Sector of t...ijtsrd
Nowadays, information on stock price movement has become paramount in making an investment decision and a good knowledge of the factors that determine stock prices and the ability to predict stock prices are added advantages in the developing economies. Therefore, this study seeks to determine the impact of earnings on the stock price of healthcare firms in Nigeria. The study relied on the linear panel modeling approach of fixed effect and random effect while the Hausman test was applied for the model selection. The panel data set used for the study was sourced from the NSE annual fact book for the periods 2011 to 2020. The result of the random effect model estimated revealed that earnings per share EPS , dividend yield DDY and firm size FSZ have no significant impact on the stock price of healthcare firms in Nigeria. The only exception is book value per share BVPS which is positive and had a significant impact on the stock prices of healthcare firms in Nigeria at the 0.01 significant levels. This study, therefore, concludes that BVPS is the perfect predictor of stock price movement in the healthcare sector. As a result, the study recommends among other findings that Book Value per Share should be considered when making investment decisions in the healthcare firms in Nigeria. Aniedozie Obiamaka Mercy | Prof Alphonsus S. Anichebe | Dr. Emeka-Nwokeji, N. A "Effect of Changes in Earning on Stock Prices of Listed Healthcare Sector of the Nigerian Stock Exchange" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-4 , June 2022, URL: https://www.ijtsrd.com/papers/ijtsrd50335.pdf Paper URL: https://www.ijtsrd.com/management/accounting-and-finance/50335/effect-of-changes-in-earning-on-stock-prices-of-listed-healthcare-sector-of-the-nigerian-stock-exchange/aniedozie-obiamaka-mercy
Returns on financial assets in the stock markets are affected daily by different types of risk, both
internal (systematic) and external (idiosyncratic), to anticipate the possible risks, investors look for tools that
allow them to know the behavior of the market and at the same time identify the risks in which they are
immersed in order to maintain a profitability in the portfolios of investment; t
This paper examine the impact of macroeconomic factors on firm level equity premium. Following
the concept of macro-based risk factor model, we consider macroeconomic variable set of equity premium
determinant. The macroeconomic variables include interest rate, money supply, industrial production, inflation
and foreign direct investment. The macroeconomic variables are not in control of the firm's management. These
are the external factors which affect the company as well as the overall market returns. The Macro-based
Multifactor Model is estimated for the whole sample. It is found that the market premium and the selected five
macroeconomic factors significantly affect the firm level equity premium of non-financial firms. Increase in
market premium, money supply, foreign direct investment and industrial production positively affect the firm
level equity premium while increase in interest rate and inflation negatively affects the firm level equity
premium. These findings are beneficial for the common shareholders, institutional investors and policy makers
to find more specific insight about the relationship between macroeconomic variables and equity premium of
non-financial sectors.
7 corporate hospital research paper hari masterpiece HariMasterpiece
1) The document discusses the impact of COVID-19 on the global economy and various industries. It estimates that global GDP will decline by 3% in 2020 according to the IMF, the lowest level since the Great Depression.
2) Many industries have been severely affected by lockdowns and reduced economic activity. Sectors like media, entertainment, and real estate have been hit hard. However, pharmaceuticals, chemicals, and online education have grown.
3) The paper analyzes secondary data on the performance of various countries and industries during COVID-19. It finds that while all economies have been impacted, the effects on India have been less severe than on the US, China, and Japan. The economic growth rate is
The Soundness of Financial Institutions In The Fragile Five CountriesCSCJournals
In recent years, economic globalization and technological development have contributed to a substantial rise in the integration of financial markets. Research findings in this area have indicated that a financial shock in one market can easily be transmitted to other markets globally. Especially, recent experiences showed that financial markets of some developing economies may even be more vulnerable to financial shocks than the emerging markets. There are several reasons, such as current account deficits, instability of local currencies, weaker financial institutions, for this situation. Contrary to the popular perception, this may be due to the lack of knowledge and prejudices of international investors about some emerging markets. This study evaluates and compares the financial soundness of 18 countries selected on the basis of the “Fragile Five” countries. The soundness of the financial structures of these countries has been evaluated based on the soundness of their financial institutions. The findings indicate that the countries with the weakest performance in the selected period are not the “Fragile Five” countries when compared with the countries in the whole sample.
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72 july2021
1. Investors and Indian Stock Indices Reaction to News Announcements during Covid-19
Dr. Rama Krishna Yelamanchili
Associate Professor, Finance
ICFAI Business School, IFHE-Hyderabad
Dr. Sager Reddy Adavelli∗
Assistant Professor, Finance
ICFAI Business School, IFHE-Hyderabad
Abstract
Using Mahalanobis Distance process we identify 31 extreme values in daily return series of study variables span between
February 2020 and June 2021. These extreme values represent 10 percent of total observations (N=304). We gather news
announcements around those 31 trading days and quantified into four groups. We examine investors (Clients, FIIs, DIIs and
Proprietary) and stock indices (BSE Sensex, and BSE S&P 500) reaction to these news announcements. In addition, using
non-parametric statistical tests, we investigate randomness, equality of distribution and day of the week effect of study
variables. Results are mixed. We find statistically significant difference between two groups of news announcements in
stock indices. On the other side, there is no such difference in investor categories. We find the returns series of Sensex, BSE
S&P 500, FIIs, DIIs to be random and Clients, Proprietary to be non-random. We also find that the daily returns of all
variables are not statistically significant from their median return. Finally, we do not find any evidence of day of the week
effect on investors’ investment pattern. We conclude that impact of negative news surrounding Covid-19 is succumbing by
Government of India (GoI) interventions. The stock market movements are random and there is no day of the week effect in
net flow of investments. There is a visible trend in clients and proprietary investors net flow into the market.
Keywords: Investors’ reaction, news announcement, non-parametric tests, random walk theory, stock market, day of the
week effect.
I.INTRODUCTION
Investors and stock markets reactions to news announcements have received increasing attention in recent years.
Few researchers (Broadstoc and Zhang, 2019, Shi and Ho, 2020) tried to explain whether there exists any
relation between price movement in stock markets and news announcements with empirical and theoretical
studies. Similarly, a proposition in behavioral finance posits that in addition to the basic value of stocks,
emergencies will have an impact on investors' psychological and behavioral factors, which in turn will have an
important impact on stock prices (Pinglin He et. al., 2020). Lee and Jiang (2002) provide an empirical evidence
of this proposition and believe investor confidence reduces earnings volatility, while investor distrust increases
earnings volatility. In the recent years there is growing interest in event studies, especially during Covid-19
pandemic period. Several studies analyze the impact of news on stock markets (Caruso, 2019; Lyocsa, Molnar,
and Plihal, 2019). The consensus is that stock markets tend to adjust prices to news continuously. In the case of
the Covid-19 pandemic, the price adjustment process was being hindered by the enormous amount of news.
Even though investors agreed that the virus would lead to a decrease in current and future cash flows and
earnings and, thus, to a drop in stock prices, the extent of the drop was unclear. A subgroup of studies has
investigated the effect of macroeconomic announcements on stock markets (Jawadi et al., 2019; Ozatay et al.,
2009). Another strand of the literature investigates the effect of non-fundamental news, such as natural disasters
and terrorist attacks, on stock markets (Braun et al., 2019; Ammar, 2020). In this study, we aim to expand the
literature related to the impact of different categories of news announcements on stock markets during Covid-19
pandemic period. During this pandemic period, along with Covid related news, news related to other categories
like federal government interventions, economic activities, and foreign markets are on headlines of media. We
test whether these four news categories have any impact on stock market returns and investors investment
patterns.
In a different context there is a long debate on market anomalies with regard to day of the week effect. These
anomalies are in contrast to efficient market hypothesis. Day-of-the-Week Effect refers to the observations that
mean stock returns are differently distributed among different week days. The First day of the week is usually
considered as a week day because the market remains bearish, while on the last day of the week the market is
found buoyant. We posit that in present information age, information is disseminated in fraction of minute and
∗
Corresponding Author
Journal of Xi'an University of Architecture & Technology
Volume XIII, Issue 7, 2021
ISSN No : 1006-7930
Page No: 743
2. any anomaly surrounding to a stock or market get adjusted instantly. So, in such a context there is no place for
week of the day effect. We opine that this pandemic period is the right time to test this assumption. In this paper
we test our proposition.
The paper proceeds as follows. Section II presents the literature review. Section III outlines the methodology.
Section IV presents the empirical results and analysis. Section V concludes the article.
II. LITERATURE REVIEW
In stock markets disasters and pandemic diseases affects investors’ behaviour towards the stock price influence.
Covid-19 has arisen as a curse in the capital markets with surprising levels of insecurity and high volatility.
Almost thirty per cent of world’s wealth had eroded within three months of emergence of this disease. Ali,
Alam, & Rizvi (2020) conducted a study on nine countries and find the pandemic situation has deteriorated
because of the global spread which was uncontrollable. This started impacting even the safer commodities like
gold. However, in comparison to the stock markets the commodities markets were less volatile.
The presence of calendar anomalies has been observing comprehensively for almost last five decades in capital
markets. Berument & Kiymaz (2001) by taking S&P 500 index for a quarter century, tested the presence of the
day of the week effect on stock market volatilities and find that the volatility and returns patterns across all the
days of the week are different. They also observed that the highest and lowest returns on Wednesday and
Monday, the highest and the lowest volatility on Friday and Wednesday correspondingly. In other countries like
Australia, Chiah & Zhong (2021) reported Tuesday’s stock returns were lower in Australia in comarison to other
days. They also report that speculative stock returns in Australia is more consistent with dynamics revealing of
current day domestic mood and previous day US mood. However, there were observable differences in US with
respect to day-of-the-week effect (Birru, 2018). The results of Birru (2018) were robust in different sub-
samples which are not explained by news releases. Investors are in soaring moods tend to fairly outstrip in
future when they are imagining the ascending mood and vice-versa and further, the role of mood beta observed
that, high mood beta stocks outperform during imminent climbing mood periods and disappoint during
imminent downward mood period (Hirshleifer, Jiang, & DiGiovanni, 2020).
Public news has also been an important influencing weapon on stock markets in recent years. Many research
studies have undertaken on understanding price movements in stock markets which are driven by any political
and economic news. Cepoi (2020) investigated the impact of Covid-19 related news on stock markets by
consindering a quite short term data of 50 trading days and observed the evidence of Covid-19 related news and
stock market returns has the relationship in the countries which are affected by the Covid-19 pandemic. Birru
(2018) find that their results of stock returns are not explained by news releases on economy, news of
companies. Anand, Basu, & Thampy, 2021 used a model developed by Anand et.al (2021) to measure sentiment
describes better the stock market returns and solidifies existing sentiment variables of Consumer confidence
index and Baker Wurgler index are insignificant in its incidence. The Covid-19 has affected the stock markets
across the globe as badly as compared to Spanish Flu. Baker et.al (2020) used text-based methods to observe the
effect of Covid-19 pandemic and government restrictions commercial activities, social distancing measures, and
other stringent interventions to control the pandemic on US stock markets and find that these actions impacted
the stock markets. Hussain & Omrane (2021) the impact of economic news related to US on the Canadian
benchmark index return and volatility considering five minute high frequecy data of every five minutes and find
that US news announcements have impact on the Canadian stock market return and volatility. Afees & Vo
(2020) evaluated the relevance of health related news during the covid-19 pandemic in predicting the stock
returns on twenty most affected countries and find health-news index made by us outstrips the benchmark index,
which indicates the health news searches as a good predictor of stock returns since during this Covid-19
pandemic period.
III. Methodology
Through this paper, we intend to investigate extreme reaction of investors and stock market indices to news
announcements during Covid-19 pandemic period. We also aim to test the randomness and normality of return
series surrounding extreme events during pandemic period. Additionally, we wish to explore whether there is
any day of the week effect in investors investment pattern. To reach our objectives, we sourced daily close
values of BSE Sensex, BSE S&P 500, and Client Category-wise net investment in to the market from Bombay
Stock Exchange of India’s official website. Further, we sourced FIIs net investment from National Securities
Depositary Limited (NSDL). The study period range between February 2020 and June 2021. This is the period
when Indian stock market witnessed impact of Covid-19 pandemic and this research is carried out. By the time
Journal of Xi'an University of Architecture & Technology
Volume XIII, Issue 7, 2021
ISSN No : 1006-7930
Page No: 744
3. we are writing this paper, concerns of Covid-19 still prevail and uncertainties persist. During study period there
were 305 trading days.
To identify extreme movement in the market, we followed Mahalanobis Distance Process. We run two separate
multiple regression models. In first multiple regression model, we regress investor categories on BSE Sensex,
and in second multiple regression model, we regress investor categories on BSE S&P 500. We calculate Chi-
square value using more stringent statistical significance value (0.001) and use this Chi-Square value to filter the
Mahalanobis Distance values. We sorted Mahalanobis Distance values in descending order and considering Chi-
Square value as cutoff value we separated extreme values in each multiple regression equation. Further, we
combined extreme values of each multiple regression equation and retained only unique date values. Of the 305
daily observations, we notice 31 extreme values. Using the dates on which these events occurred, we collected
news announcements from various news media. We see similarity in these news announcements. So, we decided
to quantify this qualitative information. We classified these news announcements into four groups.
Group one contains news announcement related to Covid-19 (Covid-19 spread, vaccine development,
alternative medication etc.). Group two contains news announcement related to foreign markets (movement in
foreign stock exchanges, foreign exchange rate, crude oil prices, foreign economies, etc.). Group three contains
news related to Indian real economy factors (GDP, Inflation, Employment, Index of Industrial Production, and
Purchase Manager’s Index etc.). Group four includes Government of India’s (GoI) intervention measures in the
economy from time to time (Incentives to poor and needy, loan moratorium, policy changes, support to
business, monetary policy, infusion of funds in to market etc.).
Next, to understand roots and repercussions of extreme movements we sourced two preceding and succeeding
days’ data surrounding each extreme day. This data series contained 123 data points. Finally, we have 103
return series points, after excluding pre-post trading days of contingent extreme value days. In our analysis, we
used 31 extreme values to understand the impact of news announcements, 103 return series points to test
randomness and equality of distribution, and 123 data points to test day of the week effect. A preliminary view
of descriptive statistics of data series reveals that all the variables have extreme values, and there is no way to
transform these extreme data points and perform parametric statistical tests. In such context, we prefer to
analyze the data with robust non-parametric statistical tests. We use one way analysis of variance to find out the
difference in mean scores of different news groups. We use Runs test to test the randomness in the data series,
and one sample Wilcoxson Signed Rank Test to check equivalence of distribution of data from its median.
Finally, we use Chi-Square test to assess day of the week effect. In Runs test we define our variables in
dichotomous as positive (1) and Negative (0). In Wilcoxson Signed test we use return series in percentage and
compare it with Median return. In Chi-Square test we classified dependent variable into dichotomous, Net Buy
(1) and Net Sell (0). In next section, we present results of the study in a sequential order in concurrence with
study objectives.
IV. RESULTS
We start presentation of study results with descriptive statistics drawn on combination of two pre and post event
days along with event days. Table 1 displays the descriptive statistics. In all there are 123 trading days including
31 extreme value days. The Skewness and Kurtosis values for all the variables are high and evidently indicate
non-normality of the series. Furthermore, the range of each variable is also high with extreme minimum and
maximum values. Standard deviation values also support this high range with high volatility in data series. All
these statistics drives us to prefer non-parametric statistical tests to parametric statistical tests. We experimented
with different transformation to make this data normal. However, all our experiments fail. So, we influenced to
run non-parametric tests to meet study objectives.
Table 1: Pre-post event Descriptive Statistics
Descriptive Sensex BSE500 FIINet DIINet Clients Net Proprietary Net
Mean 41289.44 16060.89 457.73 298.00 -608.74 100.06
Median 38900.80 15088.37 188.08 -120.35 -131.96 81.94
Standard Deviation 7643.35 3264.04 3980.43 1749.53 2853.10 208.22
Kurtosis -1.42 -1.27 23.83 2.83 91.92 0.25
Skewness 0.06 0.19 3.72 1.09 -9.12 0.24
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4. Range 24659.73 10897.23 37034.34 12590.06 30872.06 1236.07
Minimum 28265.31 10666.93 -8295.17 -4968.90 -29822.91 -526.86
Maximum 52925.04 21564.16 28739.17 7621.16 1049.15 709.21
Count 123 123 123 123 123 123
*Index values are in points. Investors’ values are in Rupees (Rs.) Crores.
Next, we proceed with analysis of event days. Descriptive statistics of event days level values are presented in
Table 2 and descriptive statistics of event days return series are presented in Table 3. In level series and in return
series, the market indices are normally distributed with Skewness and Kurtosis values close to zero. On the other
hand, both the data series of investor categories have high Skewness and Kurtosis values indicating non-
normality. We also observe low volatility in indices values and exorbitant volatility in investor categories. From
descriptive statistics it appears that both the indices report negative daily mean return during these 31 event
days. In contrast, we notice positive daily mean return values in DIIsNet, Clients Net, and Proprietary Net. FIIs
do have negative mean return value. Descriptive statistics indicate that during extreme event days, domestic
investors pumped money into the stock markets and foreign investors were net sellers. To statistically validate
these preliminary observations, we run inferential statistics for each variable. We use one way ANOVA test to
determine whether there are any statistically significant differences between the means of news announcements
groups of each variable. First, we run ANOVA test on investor categories and then on market indices. Results of
ANOVA tests and post-hoc tests and presented in Table 4a and 4b. From ANOVA analysis we fail to find any
statistically significant differences in the mean returns of investor categories. The ANOVA results fail to reject
the null hypothesis at 5% significance level. In divergence, we find statistically significant difference in mean
returns of at least two groups with regard to market indices. For both the BSE Sensex and BSE S&P 500 we
reject the null hypothesis at 5% significance level. To know which two or more groups are different we run two
post-hoc tests namely Tukey HSD test and LSD test (see Table 4b). The post-hoc tests indicate that there is a
significant mean difference between Covid News and Government of India interventions. For Sensex the mean
difference is negative (-2.96) and statistically significant (p = 0.04 and 0.03). Similarly, for BSE S&P 500 the
mean difference is negative (-2.81) and statistically significant (p = 0.03 and 0.00). Results indicate that
negative news related to Covid-19 is followed by positive or supportive news from government agencies.
Similarly, when there is good news about Covid-19 combat the GOI relaxed stringency norms related to
lockdown and people movement.
Table 2: Events descriptive statistics at level
Descriptive Sensex BSE500 FIINet DIINet Clients Net Proprietary Net
Mean 41151.17 15967.70 2303.95 608.63 -1994.94 122.06
Median 38854.55 15006.09 1004.11 -90.46 -303.02 95.13
Standard Deviation 7521.78 3193.55 6785.88 2192.09 5501.96 258.08
Kurtosis -1.47 -1.25 7.98 2.92 23.38 0.52
Skewness 0.13 0.26 2.42 1.56 -4.61 0.08
Range 22734.07 10366.64 37034.34 10045.77 30872.06 1236.07
Minimum 29815.59 11106.47 -8295.17 -2424.61 -29822.91 -526.86
Maximum 52549.66 21473.11 28739.17 7621.16 1049.15 709.21
Count 31 31 31 31 31 31
*Index values are in points. Investors’ values are in Rupees (Rs.) Crores.
Table 3: Events descriptive statistics of Returns in percentage
Descriptive Sensex BSE500 FIINet DIINet Clients Net Proprietary Net
Mean -0.13 -0.15 -1018.56 32.02 1506.69 58.52
Median -0.35 -0.17 -54.31 -18.74 19.18 -22.07
Standard Deviation 2.02 1.83 4569.46 505.10 6139.18 328.88
Kurtosis 0.55 0.23 25.46 10.66 14.47 9.08
Skewness 0.51 0.18 -4.85 2.63 3.67 2.71
Range 8.80 7.82 28237.64 3075.35 32306.40 1790.14
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5. Minimum -3.80 -3.66 -24566.06 -925.51 -3350.57 -424.51
Maximum 5.00 4.16 3671.58 2149.83 28955.84 1365.63
Count 31.00 31.00 31.00 31.00 31.00 31.00
Table 4a: One Way Analysis of Variance result
ANOVA
df F Sig.
FII Net 30 1.236 0.32
DII Net 30 1.445 0.25
Clients Net 30 0.767 0.52
Proprietary Net 30 0.980 0.42
Sensex 30 2.699 0.07
BSE S&P 500 30 2.956 0.05
Table 4b: post-Hoc test result
Test Dependent News Mean Diff SE Sig.
Tukey HSD Sensex Covid vs. GOI Interventions -2.96 1.07 0.04
LSD Sensex Covid vs. GOI Interventions -2.96 1.07 0.01
Tukey HSD BSE S&P 500 Covid vs. GOI Interventions -2.81 0.97 0.03
LSD BSE S&P 500 Covid vs. GOI Interventions -2.81 0.97 0
The mean difference is significant at the 0.05 level.
We next run one sample Runs test for each of the investor category and stock indices. Results are presented in
Table 5. When market closed in green, we labeled it as 1 and when market closed in red, we labeled it as 0.
Using these dichotomous values of each variable we run Runs test to test the randomness of returns series. We
retain the null hypothesis for Sensex, BSE S&P 500, FIIs Net, and DIIs Net. For these variables the Z scores are
low and Asymp. Sig. values are high and range between 0.08 and 0.88. On the other side, we reject the null
hypothesis for Clients Net and Proprietary Net at 5% significance level. These results indicate that return series
of four variables have randomness and two variables are not random. In case of Clients Net we find continuous
net selling and in case of Proprietary Net we find continuous net buying resulting to a trend.
Table 5: Runs Test for Randomness
Runs Test
Sensex BSE500 FIINet DIINet ClientsNet ProprietaryNet
Test Valuea
1.00 1.00 1.00 1.00 1.00 1.00
Total Cases 103 103 103 103 103 103
Number of Runs 53 47 55 58 64 67
Z 0.147 -0.417 1.720 1.579 2.422 3.084
Asymp. Sig. (2-
tailed)
0.883 0.676 0.085 0.114 0.015 0.002
Exact Sig. (2-tailed) 0.921 0.755 0.100 0.121 0.016 0.002
Point Probability 0.078 0.081 0.023 0.023 0.004 0.001
a. User-specified.
To test equality of distribution around median return of each study variable, we use Wilcoxson Signed Rank
Test. The null hypothesis of equality is tested to ascertain the probability of obtaining a number of observed
responses above and below the median. Result of one-sample Wilcoxon Signed Rank tests and their related
descriptive statistics are presented in Table 6a and 6b. It is visibly manifest that the test statistics are high and 2-
sided test Asymptotic Significance values are 0.50 and above for all the six samples. Relying on the test
statistics and significance values we retain the null hypotheses. These results indicate that the return series have
equally distributed data points around their median scores.
Journal of Xi'an University of Architecture & Technology
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ISSN No : 1006-7930
Page No: 747
6. Table 6a: Return Series Descriptive Statistics
Descriptive Sensex BSE500 FIINet DIINet ClientsNet ProprietaryNet
Mean -0.04 0.03 -182.44 -41.68 452.00 21.43
Median 0.03 0.25 -54.31 -30.32 -20.39 -2.70
Standard Deviation 1.98 1.84 2968.39 437.03 3407.32 223.19
Kurtosis 4.92 5.80 51.75 19.72 53.14 15.00
Skewness -1.27 -1.60 -4.19 -0.96 6.94 2.61
Range 13.18 12.83 39711.66 4868.21 32306.40 1939.29
Minimum -8.18 -8.32 -24566.06 -2718.38 -3350.57 -573.66
Maximum 5.00 4.51 15145.60 2149.83 28955.84 1365.63
Count 103 103 103 103 103 103
Table 6b: One-Sample Wilcoxon Signed Rank Test Summary
Sensex BSE S&P 500 FIINet DIINet ClientsNet ProprietaryNet
Total N 103 103 103 103 103 103
Test Statistic 2754.50 2537.50 2781.00 2564.00 2827.00 2696.00
Standard Error 295.19 299.56 299.56 299.56 299.56 299.56
Standardized Test 0.61 -0.30 0.52 -0.21 0.67 0.23
Asymptotic Sig. 0.54 0.77 0.61 0.83 0.50 0.82
We, next test the day of the week effect on investors net buying and selling pattern. We, first draw a summary of
day wise investment flow of each investor category. We present this data in Table 7a. It is clearly visible that
FIIs are net sellers on Friday and Monday. DIIs and Proprietary investors are net buyers on all day of the weeks.
In contrast to this Clients are net sellers on all day of the weeks. To test whether there is any significant
statistical difference in these preliminary observations we apply Chi-Square test. We categorized outcome
variable into dichotomous “1” represents net buy, and “0” represents net sell. Day of the week wise counts are
presented in Table 7b, followed by Chi-square test results in Table 7c. Count of net buy and net sell of FIIs and
DIIs are almost similar. Whereas, count of net buy and net sell of clients and proprietary investors varied. Chi-
square test statistic values range between 1.91 and 3.51 with p-values range between 0.47 and 0.75. For all the
four investor categories we retain the null hypothesis that there is no significant difference in investment pattern
over different day of the weeks. Clients are net sellers and other three categories of investors are net buyers in
the market and they don’t differentiate each day of the week with the other.
Table 7a: Week Day Net Buy / Sell (Rs. Crores)
Row Labels Sum of FIINet Sum of DIINet Sum of Clients Net Sum of Proprietary Net
Mon -4611.58 6168.71 -3010.05 1429.71
Tue 24109.22 3707.59 -11968.41 4660.79
Wed 29243.24 2503.26 -44971.55 2766.81
Thu 17843.25 7344.70 -6175.05 1771.02
Fri -10282.99 16929.79 -8749.94 1679.12
Grand Total 56,301.14 36,654.05 -74,875.00 12,307.45
Table 7b: Week Day Net Buy / Sell Count
FIIs Net DIIs Net Clients Net Proprietary Net
Week Day Net Sell Net Buy Net Sell Net
Buy
Net Sell Net
Buy
Net Sell Net Buy
Mon 11 11 13 9 17 5 7 15
Tue 8 15 12 11 18 5 4 19
Wed 14 13 15 12 21 6 9 18
Thu 11 16 15 12 19 8 11 16
Fri 11 13 9 15 15 9 9 15
Total 55 68 64 59 90 33 40 83
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ISSN No : 1006-7930
Page No: 748
7. Table 7c: Week Day Net Buy / Sell Chi-Square Test
Variable Chi=Square Value df p-value
FII Net 1.907a
4 0.75
DII Net 2.739a
4 0.60
Clients Net 2.284a
4 0.68
Proprietary Net 3.515a
4 0.47
a. 0 cells (0.0%) have expected count less than 5.
V. CONCLUSION
In this paper we aim to assess reactions of stock market indices and investor investment patterns to news
announcements during pandemic period. We desire to test the randomness of return series of study variables.
Furthermore, we examine whether return series follow Gaussian distribution. We also measure whether there is
any presence of day of the week effect. To achieve our objectives, we identified 31 extreme trade days using
Mahalanobis Distance process. In addition to these 31 extreme trade days’ data, we also gather data of two
previous and subsequent trading days. We apply non-parametric statistical tests. Based on the results of the
study, we conclude that different groups of news announcements do not have any significant impact on
investors’ investment patterns. For different news announcements, each category of investors reacts differently,
resultant to harmonizing of investment flows. But news announcements influence stock market movements.
Importantly, Covid-19 related news and GOI interventions drive the market movements. The stock indices
follow randomness because any sudden surge or shrink is adjusted quickly with net buying or selling by
investors. Furthermore, market indices have Gaussian distribution, and Clients and Proprietary investors’
investments follow down trend and uptrend respectively. Friday and Monday witness net selling activity by FIIs,
but there is no statistically significant evidence to prove this descriptive number. Investment flow into the
market does not differ from one day of the week to the other day of the week. Clients are short sighted and reap
benefits from short-term trading activities, and other three investors are investing in the market.
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