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

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

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

scholarly journals The long-Run and Short-Run Analysis between Stock Market Index and Macroeconomic Variables in Jordan: Bounds Tests Approach

2019 ◽  
Vol 12 (4) ◽  
pp. 50
Author(s):  
Raed Walid Al-Smadi ◽  
Muthana Mohammad Omoush
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
Stock Market Index ◽  
Macroeconomic Variables ◽  
Market Index ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Short Run

This paper investigates the long-run and short-run relationship between stock market index and the macroeconomic variables in Jordan. Annual time series data for the 1978–2017 periods and the ARDL bounding test are used. The results identify long-run equilibrium relationship between stock market index and the macroeconomic variables in Jordan. Jordanian policy makers have to pay more attention to the current regulation in the Amman Stock Exchange(ASE) and manage it well, thus ultimately helping financial development.

Influence of COVID-19's active cases on Malaysia's key economic performance indicators

2021 ◽  
Vol 9 (1) ◽  
pp. 68
Author(s):  
Abd Hadi Mustaffa ◽  
Nur Balqishanis Zainal Abidin ◽  
Noryati Ahmad ◽  
Emmanuel Abiodun Ogundare
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Linear Trend ◽  
Public Awareness ◽  
Consumer Price Index ◽  
Distance Measures ◽  
Series Data ◽  
Stock Market Index ◽  
Market Index ◽  
The Impact

The COVID-19 outbreak was a rare and unprecedented phenomenon. Hence, the pandemic forces the world economy to react unpredictably. Governments worldwide have undertaken several precautions, including social distance measures, public awareness programs, policies on testing and quarantine, and financial aid packages. Using endogenous growth theory, this paper examines the impact of COVID-19 towards Malaysia key economic indicator's performance using univariate regression analysis based on daily time series data from 1 January 2020 to 30 September 2020. Besides, this paper is also forecasting the upcoming three months of Malaysia's key economic indicator performance from October to December 2020, by using linear trend forecasting model. The results indicate that COVID-19 significantly impacted the unemployment rate, gross domestic product (GDP), consumer price index (CPI), foreign exchange rate (FOREX), and stock market index performance in Malaysia. The results of projecting the upcoming three months trends were forecasted to increase unemployment, GDP, FOREX, and stock market index performance. Instead, the CPI is expected to decrease. Furthermore, this paper provides four contributions in the later section.

Impact of monetary policy on house prices: case of Pakistan

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

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

scholarly journals Econometric Modelling: Testing of Randomness,Volatility, Casualty and Cointegration of Emerging Stock Market Indices of India and MIST Countries

2019 ◽  
Vol 9 (2) ◽  
pp. 1402-1417
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Time Series Data ◽  
Global Financial Crisis ◽  
Good News ◽  
Series Data ◽  
Stock Market Index ◽  
Causality Test ◽  
Lm Test ◽  
The Impact

In general, stock market indices are widely interrelated to the other global markets to detect the impact of diversification opportunities. The present research paper empirically examines randomness and long term equilibrium affiliation amongst the emerging stock market of India and Mexico, Indonesia, South Korea and Turkey from the monthly time series data during February 2008 to October 2019. The researcher employs by the way, Run test, Pearson’s correlation test, Johnsen’s multivariate cointegration test, VECM and Granger causality test with reference to post-September 2008 Global financial crisis. The test results of the above finds that Nifty 50 and BSE Sensex is significantly cointegrated either among themselves or with MIST countries particularly during the post-September Global financial crisis. No random walk is found during the study period. The ADF (Augmented DickeyFuller) and PP (Phillips Pearson) tests evidenced stationarity at the level, but converted into non-stationarity in first difference. Symmetric and asymmetric volatility behaviors are studied using GARCH, EGARCH and TARCH models in order to test which model has the best forecasting ability. Leverage effect was apparent during the study period. So the influx of bad news has a bigger shock or blow on the conditional variance than the influx of good news. The residual diagnostic test (Correlogram-Squared residuals test, ARCH LM test and Jarque-Bera test) confirms GARCH (1,1) as the best suited model for estimating volatility andforecasting stock market index.

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

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

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

scholarly journals Prediksi Indeks BEI dengan Ensemble Convolutional Neural Network dan Long Short-Term Memory

2021 ◽  
Vol 5 (3) ◽  
pp. 456-465
Author(s):  
Harya Widiputra ◽  
Adele Mailangkay ◽  
Elliana Gautama
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Time Series Data ◽  
Short Term Memory ◽  
Series Data ◽  
Stock Market Index ◽  
Short Term ◽  
Term Memory ◽  
Market Index ◽  
Long Short Term Memory

The Indonesian Stock Exchange (IDX) stock market index is one of the main indicators commonly used as a reference for national economic conditions. The value of the stock market index is often being used by investment companies and individual investors to help making investment decisions. Therefore, the ability to predict the stock market index value is a critical need. In the fields of statistics and probability theory as well as machine learning, various methods have been developed to predict the value of the stock market index with a good accuracy. However, previous research results have found that no one method is superior to other methods. This study proposes an ensemble model based on deep learning architecture, namely Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM), called the CNN-LSTM. To be able to predict financial time series data, CNN-LSTM takes feature from CNN for extraction of important features from time series data, which are then integrated with LSTM feature that is reliable in processing time series data. Results of experiments on the proposed CNN-LSTM model confirm that the hybrid model effectively provides better predictive accuracy than the stand-alone time series data forecasting models, such as CNN and LSTM.  

scholarly journals Macroeconomic Determinants of Stock Market Fluctuations: The Case of BIST-100

Economies ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 8 ◽  
Author(s):  
Caner Demir
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Exchange ◽  
Capital Inflows ◽  
Foreign Direct Investments ◽  
Domestic Currency ◽  
Stock Market Index ◽  
Macroeconomic Factors ◽  
Market Index ◽  
The Impact

The purpose of this study is to analyze the impacts of some prominent macroeconomic factors on the Turkish Stock Market index, BIST-100 (Borsa Istanbul-100). For centuries, and mostly since the 20th century, stock markets are at the heart of economies. In our era, the largest economic crises arise from the stock market instabilities and thus, the stock markets are the focus of interest of the economy. Economists, investors, and policymakers try to predict the tendency of share prices, which substantially depend on foreign and domestic macroeconomic factors. Within this purpose, this study tries to investigate the impact of some selected macroeconomic factors on BIST-100 index over the 2003Q1–2017Q4 period. The findings obtained from the quarterly data via the ARDL Bounds Test suggest that economic growth, the relative value of the domestic currency, portfolio investments and foreign direct investments raise the stock market index while interest rate and crude oil prices negatively affect it. The results briefly reveal that the Istanbul Stock Exchange Market needs stronger domestic currency, higher international capital inflows, and lower energy and investment costs.

scholarly journals The Impact of Macroeconomic Factors on Stock Market: An Evidence from China and Pakistan

2020 ◽  
pp. 1-26
Author(s):  
Isbat Alam ◽  
Muhammad Mohsin ◽  
Khalid Latif ◽  
Muhammad Zia-ur -Rehman
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Developing Economies ◽  
Stock Exchange ◽  
Series Data ◽  
Foreign Direct Investments ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
The Government ◽  
The Impact

Silk Road is an ancient strategy of economic and trade routes development networks between emerging and developing economies (China & Pakistan). The main purpose of this research is to empirical inspect the association that exists among the China stock exchange (SSE), Pakistan Stock Exchange (KSE-100) with macroeconomic variables (Gross Domestic Product, Balance of Trade, Foreign Direct Investments, Lending interest rate, and Money Supply). The annual time series data from 1995 to 2019 used to find out the results. Macroeconomic variables have an essential role in any changes in every economy. Any unexpected variations amongst these variables influence the economy in several ways. Multiple regression techniques were analyzed and examine for the significance of data to approximate the probable impacts of variables on stock market prices. Breusch Godfrey Serial Correlation with heteroskedasticity assessment is utilized to investigate the correctness as well as residual normality of series data. The finding of this study exposed that GDP is negative significant 10% with SSE and 1% at level with KSE, FDI is insignificant with SSE. negative significant 10% at level with KSE and the result of BOT shows positive significant 5% at level with SSE while insignificant with KSE, M2 is significant 5% at level with SSE but insignificant with KSE and LI are shown statistically significant 1% at level with SSE While positive significant 10% with KSE. It is determined that it is significant and an insignificant relationship among the variables with both stock market returns. The financial analyst, policymaker appreciate these findings, investors, shareholder, stock exchange editors, security exchange supervisors as well as for the Government.                                                                                          

scholarly journals Impact of Political Uncertainty on Pakistan Stock Exchange: An Event Study Approach

2020 ◽  
Vol 11 (2) ◽  
pp. 194
Author(s):  
Fiaz Ahmad SULEHRI ◽  
Amjad ALI
Keyword(s):  
Stock Market ◽  
Event Study ◽  
Abnormal Return ◽  
Stock Exchange ◽  
Stock Market Index ◽  
Study Approach ◽  
Market Index ◽  
Political Events ◽  
14Th Amendment ◽  
The Impact

Pakistan is struggling against many problems; out of which political instability and terrorism are crucial problems. These issues hindered the economic growth of the country as well as the confidence of investors. This study has investigated the impact of political events on Pakistan Stock Exchange. This paper uses a standard event study methodology. Data relating to the stock market index has been collected from the website of Pakistan Stock Exchange and relating to political events has been collected from the newspapers of Business Recorder and DAWN. A total of 18 political events was considered in the study out of which 08 events were coded as positive and other 10 were deemed negative. The first day abnormal return, a five-day cumulative abnormal return and ten-day cumulative return was calculated for all of the events. This study found evidence that political events affected the stock market in Pakistan, but their impact is different considering the economic and political implications of these events. Certain events had the strongest impact on the stock market like Nuclear tests for effective defense, the Supreme Court had revoked the Presidential order and Nawaz Sharif had been reinstated, General elections held in the country and the 14th amendment because 14th amendment was related to the elimination of corruption in political parties. Overall, this study laid the foundation to make further explorations into the phenomenon of uncertainty caused by political events in relevance to the stock market in Pakistan.

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