scholarly journals Does Macroeconomic Indicators Influence Stock Price Behavior? Evidence from Nigerian Stock Market

2019 ◽  
Vol 6 (2) ◽  
pp. 26
Author(s):  
Peter Ego Ayunku
Keyword(s):  
Stock Market ◽  
Significant Influence ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Unit Root Test ◽  
Series Data ◽  
Price Behavior ◽  
Market Growth ◽  
Integration Test

This paper investigate whether macroeconomics indicators influences stock price behavior in Nigerian stock market, using an annual time series data spanning from 1985-2015. The study employed some econometric tools such as Augmented Dicker Fuller (ADF) Unit Root test, Johansen’s co integration test, Vector Error Correction Model (VECM) to analyze the variables of interest. The study found out that Money Supply (MS) has an inverse but statistically significant  influence on stock prices in Nigerian stock market also Treasury Bill Rate (TBR) has an inverse and statistically insignificant influence on stock market prices. While on the other hand, Market Capitalization (MCAP) has a positive and statistically significant influence on stock prices while Exchange Rate (EXR) has positive but statistically insignificant relationship with stock prices in the Nigerian Stock Market. In view of the above, the study recommends amongst others that monetary authorities should try as much as possible to implement sound macroeconomic policies that would enhance stock market growth and development in Nigeria. 

scholarly journals Causal Correlation between Exchange Rate and Stock Index: Evidence from VN-Index

2016 ◽  
Vol 12 (8) ◽  
pp. 43
Author(s):  
Tri Dinh Nguyen ◽  
Quang Hung Bui ◽  
Tan Thanh Nguyen
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Index ◽  
Series Data ◽  
Sample Period ◽  
Integration Test ◽  
Adf Test

This paper will examine the causal correlation of exchange rates and stock prices in Vietnam. The data is collected daily from March 1<sup>st </sup>2007 to March 1<sup>st</sup> 2014. The whole sample period is divided into two sub-groups as before the stock market bottom, after stock market bottom and full sample period. Unit root tests are employed for checking the stationary of time series data such as ADF test, PP test and KPSS test. This paper employs the co-integration test and Granger causality test to identify the causal correlation between two variables. The results of paper prove that there is no causal correlation between exchange rate and stock price. It means that the stock price has no effect on exchange rate and vice versa. However, after stock market bottom from February 25<sup>th </sup>2009 to March 1<sup>st </sup>2014, this research finds that it has a long-run co-movement between these variables by applying the Johansen test.

A Sectoral Analysis of the Role of Stock Market Development on Economic Growth: Empirical Evidence from Indian Economy

2017 ◽  
Vol 18 (4) ◽  
pp. 911-923 ◽  
Author(s):  
Madhu Sehrawat ◽  
A.K. Giri
Keyword(s):  
Economic Growth ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Trade Openness ◽  
Series Data ◽  
Causality Test ◽  
Long Run ◽  
Short Run

The present study examines the relationship between Indian stock market and economic growth from a sectoral perspective using quarterly time-series data from 2003:Q4 to 2014:Q4. The results of the autoregressive distributed lag (ARDL) approach bounds test confirm the existence of a cointegrating relationship between sector-specific gross domestic product (GDP) and sector-specific stock indices. The empirical results reveal that sector-specific economic growth are significantly influenced by changes in the respective sector-specific stock price indices in the long run as well as in the short run. Apart from that, the control variables, such as trade openness and inflation, act as the instrument variables in explaining the variations in the sector-specific GDP of the economy. The results of Granger causality test demonstrate unidirectional long-run as well as short-run causality running from sector specific stock prices to respective sector GDP. The findings suggest that economic growth of the country is sensitive to respective sub-sector stock market investments. The findings highlight the reasons for cyclical and counter-cyclical business phase for the overall economy.

scholarly journals Dynamic Relationships among Crude oil price, exchange rate and BSE Sensex

2018 ◽  
Vol 13 (02) ◽  
Author(s):  
Roshan Kumar ◽  
Manisha Gupta
Keyword(s):  
Crude Oil ◽  
Stock Prices ◽  
Time Series Data ◽  
Research Work ◽  
Unit Root Test ◽  
Series Data ◽  
Causality Test ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Integration Test

The study examined Dynamic relationship among crude oil prices, exchange rates and stock prices in India for the duration January 2006 to December 2016 using daily data. The research work include the testing for a unit root test in time series data, then it testing the number of co-integrating vectors in the system. In the next step we use the johansen co integration test to examine the relationship among variables. At the last Granger causality test is used to estimating the direction of causality among the variables

scholarly journals PENGARUH RETURN ON EQUITY, DEBT TO EQUITY RATIO DAN SIZE TERHADAP HARGA SAHAM PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI)

BISMA ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Marzuki Marzuki
Keyword(s):  
Firm Size ◽  
Significant Influence ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
Manufacturing Companies ◽  
Return On Equity ◽  
Section Data

The objective of this study is to examine the effect of ROE, DER, and firm size on stock prices of the manufacturing companies listed on the Indonesia Stock Exchange (IDX). The data used in this study were panel data sourced from the combination of cross section data and time series data. This research used purposive sampling method with the sample consisted of 86 manufacturing companies listed on IDX in 2017. Data were analyzed using multiple linear regression. The results showed that ROE and firm size had a positive and significant influence on stock price. However, DER did not have a significant influence on stock price. Keywords : ROE, DER, company size, stock price

scholarly journals Impact of gold prices on stock exchange market: a case of Karachi stock exchange market of Pakistan

2016 ◽  
Vol 4 (1) ◽  
pp. 60 ◽  
Author(s):  
Muhammad Shaique Khan ◽  
Abdul Aziz ◽  
Gobind M. Herani
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Unit Root Test ◽  
Gold Price ◽  
Series Data ◽  
Exchange Market ◽  
Long Run ◽  
Domestic Capital ◽  
Integration Test

<p>The objective of the study is to examine the long-term relationship between gold prices and KSE-100 index of the Karachi stock market Pakistan. For the foreign and domestic capital investors, it is assumed that the gold is the safest heaven for making investment. On the other handstock markets are considered highly volatile. This study uses monthly data of two hundred forty eight months from October 1993 to May 2014. Time-series data of both variables Karachi Stock Exchange 100 index (KSE-100) and gold prices have been collected from the official website of Karachi stock market and Forex.com. To achieve the aims of the study, several econometric tests have been applied such as unit root test by using Augmented Dickey-Fuller test, Johnson Co-integration test and Vector Auto-regressive Model (VAR). This study finds that there is no long-run relationship between KSE 100 index and gold prices. It is concluded investors should not consider KSE 100 index and gold prices as close alternatives rather they should make their decisions on subjective knowledge by aligning them with empirical evidence. While making decisions about gold prices last month’s price must be taken into consideration because current gold price is significantly influenced by last month’s gold price. Whilst making decision regarding KSE 100 index last two months’ fluctuations taken into consideration.</p>

scholarly journals COINTEGRATING RELATION BETWEEN EXCHANGE RATE AND GOLD PRICE

2017 ◽  
Vol 5 (10) ◽  
pp. 263-269
Author(s):  
Ranjusha ◽  
Devasia ◽  
Nandakumar
Keyword(s):  
Exchange Rate ◽  
Time Series Data ◽  
Unit Root Test ◽  
Gold Price ◽  
Series Data ◽  
Annual Data ◽  
Causality Test ◽  
Long Run ◽  
Integration Test ◽  
The Relationship

The very purpose of this paper is to analyse the relationship between gold price and Rupee – Dollar exchange rate in India. The study utilises the annual data of exchange Rate (ER) and Gold Price (GP) from 1970 to 2015 to determine the relationship. Different econometric tools like Unit root test, Johansen co integration test, Vector error correction model, Granger causality test are used for detecting the long run relation, if any between the mentioned variables. The result shows that there exists a long run cointegrating relation between the variables. That is we can stabilise the Gold Price movement by controlling the exchange rate fluctuations. Likewise it also shows that Exchange rate doesn’t Granger cause to Gold price and vice versa. It means that the time series data of one vasriable cannot be used to predict another.

scholarly journals A Predictive Meta Model for Forecasting Stock Price using Time Series Data

2021 ◽  
Vol 10 (1) ◽  
pp. 345-356
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
Meta Model ◽  
Price Range ◽  
Stock Traders ◽  
The Right

Stock market prediction through time series is a challenging as well as an interesting research areafor the finance domain, through which stock traders and investors can find the right time to buy/sell stocks. However, various algorithms have been developed based on the statistical approach to forecast the time series for stock data, but due to the volatile nature and different price ranges of the stock price one particular algorithm is not enough to visualize the prediction. This study aims to propose a model that will choose the preeminent algorithm for that particular company’s stock that can forecastthe time series with minimal error. This model can assist a trader/investor with or without expertise in the stock market to achieve profitable investments. We have used the Stock data from Stock Exchange Bangladesh, which covers 300+ companies to train and test our system. We have classified those companies based on the stock price range and then applied our model to identify which algorithm suites most for a particular range of stock price. Comparative forecasting results of all algorithms in diverse price ranges have been presented to show the usefulness of this Predictive Meta Model

Terrorism and Stock Market Linkages: An Empirical Study from a Front-line State

2017 ◽  
Vol 18 (2) ◽  
pp. 365-378 ◽  
Author(s):  
Imtiaz Arif ◽  
Tahir Suleman
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Negative Impact ◽  
Stock Exchange ◽  
Series Data ◽  
Front Line ◽  
Long Run ◽  
Factor Index ◽  
The Impact

This article investigates the impact of prolonged terrorist activities on stock prices of different sectors listed in the Karachi Stock Exchange (KSE) by using the newly developed terrorism impact factor index with lingering effect (TIFL) and monthly time series data from 2002 (January) to 2011 (December). Johansen and Juselius (JJ) cointegration revealed a long-run relationship between terrorism and stock price. Normalized cointegration vectors are used to test the effect of terrorism on stock price. Results demonstrate a significantly mixed positive and negative impact of prolonged terrorism on stock prices of different sectors and show that the market has not become insensitive to the prolonged terrorist attacks.

scholarly journals Influence of Bank Credits on the Nigerian Economy

2019 ◽  
Vol 5 (1) ◽  
pp. 1-9
Author(s):  
Idachaba Odekina Innocent ◽  
Olukotun G. Ademola ◽  
Elam Wunako Glory
Keyword(s):  
Public Sector ◽  
Private Sector ◽  
Banking Sector ◽  
Time Series Data ◽  
Unit Root Test ◽  
Series Data ◽  
Long Run ◽  
Integration Test ◽  
Lending Rate ◽  
Negative Effect

The aim of this study is to examine the influence of bank credits on the Nigerian economy using time series data covering the period from 1980 to 2017.Gross domestic product was used as proxy for the economy while credits to the private sector, public sector and prime lending rate were used as proxies of Banks credits. Unit root test was used to test stationary which reveals that all the variables were stationary at first difference. The regression analysis result shows that credit to the private sector have positive effect on Nigerian economy while credit to public sector and prime lending rate have negative effect on the Nigerian economy. The result of co-integration test presented reveals that there exist among the variables co-integration which means long-run analysis. It is recommended that, policy makers should focus attention on long-run policies to promote economic growth such as development of modern banking sector, efficient financial market, infrastructures.

scholarly journals HINTERLAND MEDAN CITY BETWEEN BINJAI CITY: A GRAVITATION APPROACH

2019 ◽  
Vol 17 (1) ◽  
pp. 94
Author(s):  
Muhammad Nasir
Keyword(s):  
Confidence Level ◽  
Time Series Data ◽  
Impulse Response Function ◽  
Unit Root Test ◽  
Gravity Models ◽  
Series Data ◽  
Causality Test ◽  
Integration Test ◽  
Relationship Of ◽  
The City

Regional economy explains that there is an urban hierarchical relationship, cities that have higher hierarchy will serve cities that are below it as well as cities that are in hierarchy under supplying cities that are in the hierarchy above them, so there is a gravitational relationship between the two. This study aims to determine the gravitational relationship of Medan city to the hinterland of the city of Binjai. Furthermore, this study also wants to explain its influence on economic growth in both cities. This study uses time series data from 1990-2016, taken from North Sumatera BPS test equipment and analysis tools used are descriptive statistics, gravity models, unit root test, co-integration test, optimal lag, VECM, granger causality test, impulse response function and variance decomposition. The results showed that the city of Medan has a gravity style greater than the gravitational style of the city of Binjai. This is because the city of Medan has a larger area, population, income per capita compared to the city of Binjai. The VECM estimation results show that the gravitational variable in the city of Binjai in lag -1 and lag-2 has a positive and significant effect on the economy of Medan city with a confidence level of 95%. Then the economic variable of the city of Binjai itself in lag-1, the population of the city of Medan in lag-2 and the gravity of the city of Medan in lag-2 had a positive and significant effect on the economy of Binjai city with a confidence level of 95%. While the variable population of Binjai city in lag -1 and residents of the city of Medan in lag -1 negatively affected the economy of Binjai city with a confidence level of 95%.

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