scholarly journals H7N9 not only endanger human health but also hit stock marketing

2017 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Wenjie Sun
Keyword(s):  
Avian Influenza ◽  
Stock Prices ◽  
Stock Price ◽  
Composite Index ◽  
Economic Loss ◽  
Chinese Traditional Medicine ◽  
Biological Product ◽  
Distributed Lag ◽  
Closing Price ◽  
Case Number

Objective: This study aims to discuss the correlation between daily reported H7N9 cases and stock price indices in China. Methods: Information on daily reported H7N9 cases and stock market sectors indices between February 19, 2013 and March 31, 2014 were collected. A distributed lag non-linear model was used to describe the variation trend for the stock indices Results: The daily reported number of H7N9 cases was associated with the closing price of the Avian Influenza Sector Index (P < 0.05) and the opening price of the Shanghai Composite Index (P = 0.029). The Avian Influenza Sector Index decreased with increasing of daily reported case number when daily reported cases ? 4. Case number was associated with the opening/closing price of the Chinese Traditional Medicine Sector Index, the Biological Product Sector Index, and the Biomedicine Sector Index (P < 0.05). Conclusion: New or reemerging infectious diseases epidemic cause economic loss which is reflected in movements in stock prices.

MODELING THE INTERACTIONS OF STOCK PRICE AND EXCHANGE RATE IN MALAYSIA

2009 ◽  
Vol 54 (04) ◽  
pp. 605-619 ◽  
Author(s):  
MOHD TAHIR ISMAIL ◽  
ZAIDI BIN ISA
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Price Index ◽  
Composite Index ◽  
Regime Shifts ◽  
Var Model ◽  
Vector Autoregressive ◽  
Stock Price Index

After the East Asian crisis in 1997, the issue of whether stock prices and exchange rates are related or not have received much attention. This is due to realization that during the crisis the countries affected saw turmoil in both their currencies and stock markets. This paper studies the non-linear interactions between stock price and exchange rate in Malaysia using a two regimes multivariate Markov switching vector autoregression (MS-VAR) model with regime shifts in both the mean and the variance. In the study, the Kuala Lumpur Composite Index (KLCI) and the exchange rates of Malaysia ringgit against four other countries namely the Singapore dollar, the Japanese yen, the British pound sterling and the Australian dollar between 1990 and 2005 are used. The empirical results show that all the series are not cointegrated but the MS-VAR model with two regimes manage to detect common regime shifts behavior in all the series. The estimated MS-VAR model reveals that as the stock price index falls the exchange rates depreciate and when the stock price index gains the exchange rates appreciate. In addition, the MS-VAR model fitted the data better than the linear vector autoregressive model (VAR).

scholarly journals ANALISIS CALENDAR ANOMALIES DI PASAR SAHAM INDONESIA TAHUN 1998 – 2018

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Hasna Fairuz Surachmadi ◽  
Anhar Fauzan Priyono ◽  
Heriyaldi Heriyaldi
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Composite Index ◽  
Efficient Market Hypothesis ◽  
Rate Of Return ◽  
Seasonal Effect ◽  
Hypothesis Theory ◽  
Calendar Anomalies ◽  
Movement Tendency ◽  
Observation Period

ABSTRACT   The Efficient Market Hypothesis Theory of Fama states that stock prices cannot be predicted by its movement tendency (random walk). In some stock markets, the movement of stock prices has a seasonal effect, which is the repetition of stock movements at a certain time that can be called a calendar anomalies. The repetition or seasonal effect on rate of return shows that the stock price can be predicted, thus it can be exploited by investors to get the probability of a higher rate of return. This research aims to see whether calendar anomalies prevail in the Indonesian stock market by using the daily and monthly rate of return of LQ45 and the Jakarta Composite Index (JCI) with an observation period of 21 years from 1998 to 2018 and estimated using the GARCH-M model (1,1). The results of this research are the existence of daily anomalies on Monday as the day with the lowest rate of return and Wednesday as the day with the highest rate of return. In addition, we also get the results of monthly anomalies in August as the month with the lowest rate of return and December as the month with the highest rate of return.

scholarly journals The Effect of Daily Stock Price Limits on the Investment Risk: Evidence from the Egyptian Stock Market

2017 ◽  
Vol 6 (4) ◽  
pp. 1 ◽  
Author(s):  
Mai Ahmed Abdelzaher ◽  
Khairy Elgiziry
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Positive Relationship ◽  
Descriptive Analysis ◽  
Negative Relationship ◽  
Fair Value ◽  
Price Limits ◽  
Stock Volatility ◽  
Closing Price

The study aims to investigate the relationship between daily price limits and stock volatility, trading volume, delayed adjustment of stock prices, and its fair value. To achieve this goal, we used the data of the listed firms in EGX30. We analyzed the data using descriptive analysis then we applied General linear model, ARCH and GARCH models. Based on our analysis results show a positive relationship between upper daily limit and stock volatility, a positive relationship between daily price limits (upper limit- lower limit) and trading volume, a positive relationship between upper daily limit and the return between the closing price and the opening price on the same day, a positive relationship between lower daily limit and the return between the closing price and the opening price in the next day, a negative relationship between upper daily limit and the return between the closing price and the opening price in the next day, and a positive relationship between daily stock price limits and the fair value.

Hubungan Rasio Profitabilitasterhadap Harga Saham

2019 ◽  
Vol 4 (1) ◽  
pp. 57-63
Author(s):  
Yuniarti Yuniarti
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Profit Margin ◽  
Coefficient Of Determination ◽  
Net Profit ◽  
Closing Price ◽  
The Relationship ◽  
Profitability Ratios

To find out the relationship between profitability ratios to stock prices used inferential research. Profitabilityratios are proxied byreturn on asset as variable X1, net profit margin as variableX2, gross profit margin asvariableX3, andreturn on equityas variable X4. The stock price is proxied by closing price as the variable Y.Analysis techniques using multiple linear regression, analysis coefficient of determination and testing ofhypothesis both F-test and T-test. The results of the regre

scholarly journals Portfolio Returns of Islamic Indices and Stock Prices in GCC Countries: Empirical Evidence From the ARDL Model

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110184
Author(s):  
Faris Alshubiri
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Price Index ◽  
Ardl Model ◽  
Portfolio Returns ◽  
Distributed Lag ◽  
Gcc Countries ◽  
Long Run ◽  
Short Run ◽  
Stock Price Index

This study aimed to analyze four portfolio returns of Islamic indices to determine the potential of attracting investments in the Islamic Stock Price Index of the six Gulf Cooperation Council (GCC) countries. Monthly data were collected from S&P Dow Jones Indices LLC reports covering the period from December 31, 2010 to December 31, 2019. The study applied the autoregressive distributed lag (ARDL) method for estimation. The findings show that the S&P GCC Composite Shariah, the S&P GCC Composite Shariah Dividend, and the S&P Shariah Domestic Total Return Index are positively related in the long run to the Islamic Stock Price Index but S&P GCC Investable Shariah is negatively related to the Islamic Stock Price Index. The error correction model (ECM) results for the short-run ARDL model indicate that the S&P GCC Composite Shariah and the S&P GCC Investable Shariah are positively related to the Islamic Stock Price Index but S&P Shariah Domestic Total Return Index is negatively related to the Islamic Stock Price Index. The main conclusion is that positive growth in the price of Islamic stocks depends on diversifying the Islamic investment portfolio to hedge against unexpected risks.

scholarly journals The Determinants of House Prices in Malaysia

2021 ◽  
Vol 2 (1) ◽  
pp. 1-18
Author(s):  
Hazmi Hamizan Mohd Zaki
Keyword(s):  
Interest Rates ◽  
Stock Prices ◽  
House Prices ◽  
Consumer Price Index ◽  
Composite Index ◽  
Real Income ◽  
Macroeconomic Factors ◽  
Distributed Lag ◽  
Long Run ◽  
Nominal Interest Rates

This paper studied how house prices were affected by macroeconomic factors from Q1 2009 to Q4 2018. The short and long-run effects of real income, nominal interest rates, inflation rate and stock prices on house prices in Malaysia were examined with the autoregressive distributed lag (ARDL) of a restricted error correction model (ECM). It was discovered that the selected macroeconomic factors were cointegrated with house prices. Income, represented by real Gross Domestic Product (GDP), significantly affected house prices in the short and long-run. Inflation and interest rate, proxied by Consumer Price Index (CPI) and Overnight Policy Rate (OPR), respectively, affected house prices significantly in the long-run. The stock market, tracked by Kuala Lumpur Composite Index (KLCI), had no significant impact on house prices signifying no wealth effect. Through the findings of an inelasticity of demand and an undesirable result of monetary policies, this paper concluded that more effective solutions needed to be carried out to ensure affordability of house ownership in Malaysia.

scholarly journals ADAKAH PENGARUH FREE FLOAT TERHADAP PELAKU PASAR SAHAM DI INDONESIA?

2019 ◽  
Vol 21 (1) ◽  
pp. 39-46
Author(s):  
PUTRI MUTIRA
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Composite Index ◽  
High Price ◽  
Percentage Increase ◽  
Price Changes ◽  
Average Value ◽  
Before And After ◽  
Additional Reference

Indonesian Stock Exchange has released free float adjustment index on November 2018 and composite index declined about 3,2%. Free Float will be an additional reference for the exchange in compiling an index which previously used market capitalization and total transaction value. This study examines the average daily price changes of LQ45 stocks within 60 days before and after the announcement. The daily closing price changes are calculated as a percentage increase or decrease of stock prices according to the previous day, then, the average value is calculated for all the trading days. There are differences in the average stock price changes 60 days before and after the announcement date. After dropped, the price rebound and make a new higher high price two days after the announcement. Bank BCA, Bank Mandiri, Bank BRI, Bank BNI, Astra International and Telkom are companies which increase the weight of the free float meanwhile Unilever and H.M Sampoerna were the opposite.

scholarly journals Do Interbank Interest Rates Matter for Stock Prices at Nepal Stock Exchange?

Pravaha ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 165-170
Author(s):  
Rajesh Gurung
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Distributed Lag ◽  
Long Run ◽  
Auto Regressive ◽  
The Interest Rate ◽  
Bound Test

This study examines an auto-regressive distributed lag (ADRL) modeling approach to develop the relationship between the stock price and interest rate in the context of Nepal, using the monthly data for the period from July 1996 to January 2019. NEPSE Index in Nepal Stock Exchange Limited is used for the stock prices and interbank interest rate released in Quarterly Economic Bulletin of Nepal Rastra Bank is used for the interest rate. The bound test for co-integration and estimated negative coefficient of long-run regression results justified by the Error Correction Mechanisms (ECM) establishes a valid negative long-run association between the INTEREST and PRICE. This suggests important considerations for policies towards an interest rate stabilization for the stock price stability and further development of the stock market in Nepal.

scholarly journals Stock Price Forecast Based on CNN-BiLSTM-ECA Model

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Yu Chen ◽  
Ruixin Fang ◽  
Ting Liang ◽  
Zongyu Sha ◽  
Shicheng Li ◽  
...  
Keyword(s):  
Network Model ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Short Term Memory ◽  
Composite Index ◽  
Multimedia Data ◽  
Series Data ◽  
High Noise ◽  
Stock Price Prediction

Financial data as a kind of multimedia data contains rich information, which has been widely used for data analysis task. However, how to predict the stock price is still a hot research problem for investors and researchers in financial field. Forecasting stock prices becomes an extremely challenging task due to high noise, nonlinearity, and volatility of the stock price time series data. In order to provide better prediction results of stock price, a new stock price prediction model named as CNN-BiLSTM-ECA is proposed, which combines Convolutional Neural Network (CNN), Bidirectional Long Short-term Memory (BiLSTM) network, and Attention Mechanism (AM). More specifically, CNN is utilized to extract the deep features of stock data for reducing the influence of high noise and nonlinearity. Then, BiLSTM network is employed to predict the stock price based on the extracted deep features. Meanwhile, a novel Efficient Channel Attention (ECA) module is introduced into the network model to further improve the sensitivity of the network to the important features and key information. Finally, extensive experiments are conducted on the three stock datasets such as Shanghai Composite Index, China Unicom, and CSI 300. Compared with the existing methods, the experimental results verify the effectiveness and feasibility of the proposed CNN-BILSTM-ECA network model, which can provide an important reference for investors to make decisions.

scholarly journals How Does Stock Prices Respond to Various Macroeconomic Factors? A Case Study of Pakistan

2014 ◽  
Vol 1 (4) ◽  
pp. 25-30
Author(s):  
Ayaz Khan
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Correction Term ◽  
Macroeconomic Factors ◽  
Market Prices ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Long Run

Over the time everything flourished, at the same token the interrelationship among the stock market prices, returns and macroeconomic factors got attendance of the researchers in the field of finance and economics around the world. In this respect current study is an attempt to investigate the response of various macroeconomic factors (GDP, Money Supply, inflation, exchange rate and Size of firm) toward stock market prices in case of Karachi stock exchange over a period of 1971 to 2012. The study utilizes Autoregressive Distributed lag model (ARDL) technique. The results shows that in long run each factor significantly contribute to the stock price while in shot run some factors were significant while some were not but the error correction term shows significant convergence toward equilibrium. The findings of study suggest that for smoothness of stock market the current factors must be targeted.

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