Measuring the Effects of Major Macroeconomic Shocks on Stock Price: A Factor-Augmented Vector Autoregressive (FAVAR) Approach

2016 ◽  
Vol 10 (2) ◽  
pp. 21-48
Author(s):  
Hong, Woo-Hyung
Keyword(s):  
Stock Price ◽  
Macroeconomic Shocks ◽  
Vector Autoregressive

scholarly journals External macroeconomic shocks and stock price behavior in Nigeria

2021 ◽  
Vol 10 (6) ◽  
pp. 174-180
Author(s):  
Mojeed Olanrewaju Saliu
Keyword(s):  
Interest Rate ◽  
Stock Price ◽  
Real Interest Rate ◽  
Research Work ◽  
Estimation Method ◽  
Oil Price ◽  
Share Price ◽  
Price Behavior ◽  
Macroeconomic Shocks ◽  
Vector Autoregressive

This research work investigates the relationship between external macroeconomic shocks and stock price behavior in Nigeria. Variables such as exchange rate (EXR), US real interest rate (USRINTR), and world oil price (WOP) are adopted to capture external macroeconomic shocks while all share price index is used to proxy stock price. The research work uses Johansen cointegration and structural vector autoregressive model as the estimation method. Findings from the study confirm that no long-term co-movement exists between the stock price and the selected external shocks. Findings from the study equally show that both US real interest rate (USRINTR) and world oil price (WOP) are the major external shock predictors of the stock price in Nigeria.

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 DO MACROECONOMIC CONDITIONS MATTER FOR AGRICULTURE? THE INDIAN EXPERIENCE

2010 ◽  
Vol 55 (04) ◽  
pp. 647-670
Author(s):  
SHASHANKA BHIDE ◽  
B. P. VANI ◽  
MEENAKSHI RAJEEV
Keyword(s):  
Economic Growth ◽  
Foreign Exchange ◽  
Autoregressive Model ◽  
Agricultural Sector ◽  
Vector Autoregressive Model ◽  
Macroeconomic Shocks ◽  
Vector Autoregressive ◽  
Macroeconomic Conditions ◽  
Indian Experience ◽  
High Inflation

Macroeconomic instability, characterised by high inflation, fragile foreign exchange positions and high rates of interest, increases uncertainty and hence slows down economic growth. While this is generally accepted, the usual perception about the agricultural sector, particularly in India, is that it is immune to general macroeconomic shocks. In this paper, we examine this perception using a vector autoregressive model. The findings show that the agricultural sector is not insulated from macroeconomic shocks.

scholarly journals PENGARUH KRISIS EKONOMI AMERIKA SERIKAT TERHADAP BURSA SAHAM DAN PERDAGANGAN INDONESIA

2013 ◽  
Vol 15 (3) ◽  
pp. 89-103
Author(s):  
Mita Nezky
Keyword(s):  
Stock Market ◽  
Income Tax ◽  
Stock Price ◽  
Value Added ◽  
Vector Autoregressive ◽  
Production Index ◽  
Svar Model ◽  
Dow Jones Industrial Average ◽  
The Us ◽  
The Impact

This paper analyzes the impact of the financial crisis in United States 2008 on Indonesia’s economy, by using Structural Vector Autoregressive (SVAR) model of 5 variables; Dow Jones Industrial Average, exchange rate, composite stock price index (IHSG), production index and trade tax income. The result shows that the US crisis affects the capital market in Indonesia where the Dow Jones Industrial Average plays greater role in explaining the IHSG, compared to Rupiah rate, production index and the trade income tax. In addition, the US crisis affects the volume and the trade income tax in Indonesia. These empirical results bring policy implication for Bappepam-LK as stock market regulator to intervene or to suspend the trade when the volatility exceeds the psychological threshold. It also emphasizes the necessity to diversify the export country destination and to increase the quality and the value added of Indonesian export.Keywords : US Crisis, stock market, trade, SVAR.JEL Classification : G18

Investment in IT and the Business Performance of Financial Companies

2006 ◽  
pp. 1-23 ◽  
Author(s):  
Irene Henriques ◽  
Perry Sadorsky
Keyword(s):  
Information Technology ◽  
Financial Performance ◽  
Stock Price ◽  
Business Performance ◽  
Var Model ◽  
Strategic Investment ◽  
Vector Autoregressive ◽  
Landscape Information ◽  
General Business ◽  
The Relationship

Global information technology and competitive financial alliances are helping to reshape the business landscape. Information technology (IT) and well functioning financial markets play a crucial role in increasing economic growth and prosperity. The purpose of this study is to empirically investigate the relationship between investment in IT and the business performance of financial companies. A vector autoregressive (VAR) model is used to test hypotheses one (increased spending on IT increases financial performance) and two (increased financial performance increases spending on IT) where financial performance is assumed to be adequately measured by stock price returns. Control variables for general business cycle conditions are included in the analysis. Our results show that the greatest benefits from increases in technology accrue to insurance and other financial companies. Managers of these companies could increase their business performance through strategic investment and use of IT.

scholarly journals Macroeconomic Shocks and Changing Dynamics of the U.S. REITs Sector

2019 ◽  
Vol 11 (10) ◽  
pp. 2776 ◽  
Author(s):  
Rangan Gupta ◽  
Zhihui Lv ◽  
Wing-Keung Wong
Keyword(s):  
Monetary Policy ◽  
Decomposition Analysis ◽  
Monetary Policy Shocks ◽  
Macroeconomic Shocks ◽  
Vector Autoregressive ◽  
The Us ◽  
Policy Shocks ◽  
Time Regime ◽  
Variance Decomposition Analysis ◽  
The Impact

Unlike the existing literature, which primarily studies the impact of only monetary policy shocks on real estate investment trusts (REITs), this paper develops a change-point vector autoregressive (VAR) model and then analyzes, for the first time, regime-specific impact of demand, supply, monetary policy, and spread yield shocks, identified using sign-restrictions, on US REITs returns. The model first isolates four major macroeconomic regimes in the US since the 1970s and discloses important changes to the statistical properties of REITs returns and its responses to the identified shocks. A variance decomposition analysis revealed aggregate supply shocks to have dominated in the early part of the sample period, and monetary policy and spread shocks at the end. Our results imply that ignoring other possible shocks in the model is likely to lead to incorrect inferences, and over-reliance on (conventional) monetary policy in correcting for possible bubbles in the REITs sector, which it will fail to rectify, given the importance of other shocks driving the REITs sector.

scholarly journals Soft Computation Vector Autoregressive Neural Network (VAR-NN) GUI-Based

2018 ◽  
Vol 73 ◽  
pp. 13008 ◽  
Author(s):  
Hasbi Yasin ◽  
Budi Warsito ◽  
Rukun Santoso ◽  
Suparti
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Autoregressive Model ◽  
Stock Price ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Series Data ◽  
Percentage Error ◽  
Vector Autoregressive ◽  
Price Data

Vector autoregressive model proposed for multivariate time series data. Neural Network, including Feed Forward Neural Network (FFNN), is the powerful tool for the nonlinear model. In autoregressive model, the input layer is the past values of the same series up to certain lag and the output layers is the current value. So, VAR-NN is proposed to predict the multivariate time series data using nonlinear approach. The optimal lag time in VAR are used as aid of selecting the input in VAR-NN. In this study we develop the soft computation tools of VAR-NN based on Graphical User Interface. In each number of neurons in hidden layer, the looping process is performed several times in order to get the best result. The best one is chosen by the least of Mean Absolute Percentage Error (MAPE) criteria. In this study, the model is applied in the two series of stock price data from Indonesia Stock Exchange. Evaluation of VAR-NN performance was based on train-validation and test-validation sample approach. Based on the empirical stock price data it can be concluded that VAR-NN yields perfect performance both in in-sample and in out-sample for non-linear function approximation. This is indicated by the MAPE value that is less than 1% .

scholarly journals THE LONG-RUN RELATIONSHIP BETWEEN INFLATION AND REAL STOCK PRICES: EMPIRICAL EVIDENCE FROM SOUTH AFRICA

2012 ◽  
Vol 13 (4) ◽  
pp. 600-613 ◽  
Author(s):  
Riona Arjoon ◽  
Mariëtte Botes ◽  
Laban K. Chesang ◽  
Rangan Gupta
Keyword(s):  
South Africa ◽  
South African ◽  
Stock Prices ◽  
Stock Price ◽  
Positive Real ◽  
Vector Autoregressive ◽  
Price Response ◽  
Long Run ◽  
Short Run ◽  
Real Value

The existing literature on the theoretical relationship between the rate of inflation and real stock prices in an economy has shown varied predictions about the long run effects of inflation on real stock prices. In this paper, we present some time series evidence on this issue using South African data, by applying the structural bivariate vector autoregressive (VAR) methodology proposed by King and Watson (1997). Our empirical results provide considerable support of the view that, in the long run real stock prices are invariant to permanent changes in the rate of inflation. The impulse responses reveal a positive real stock price response to a permanent inflation shock in the long run, indicating that any deviations in short run real stock prices will be corrected towards the long run value. It is therefore concluded that inflation does not lower the real value of stocks in South Africa, at least in the long run.

scholarly journals THE GARCH MODEL VOLATILITY OF SHARIA STOCKS ASSOCIATED CAUSALITY WITH MARKET INDEX

2020 ◽  
Vol 1 (1) ◽  
pp. 18-28
Author(s):  
Endang Soeryana Hasbullah ◽  
Endang Rusyaman ◽  
Alit Kartiwa
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Garch Model ◽  
Test Method ◽  
Causality Test ◽  
Vector Autoregressive ◽  
Market Index ◽  
Causality Relationship ◽  
The Garch Model ◽  
The Relationship

The purpose of this paper is to examine the volatility of Islamic stocks related to the causality of the composite stock price index (CSPI). The aim is to investigate the causality of several levels of stock returns with the movement of the CSPI, and determine its volatility as a measure of risk. To determine the causality relationship is done by using the granger causality test method, with Vector Autoregressive (VAR) modeling. Whereas to determine the volatility is done using the Generalized Autoregressive Conditional Heteroscedastisiy (GARCH) model approach. The results of the causality test show that there is a direct relationship that affects and is influenced by the CSPI, and the relationship that affects each other between the company's stock market and the movement of the CSPI. While the volatility follows the GARCH model (1, 1). Based on the results of this study are expected to be used as consideration in making investment decisions in the analyzed stocks.

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