Information Spillover Between Crude Oil and Stock Markets: Evidence from Subsidy Cut for RON95 Fuel Price in Malaysia

2017 ◽  
Vol 19 (4) ◽  
pp. 889-901
Author(s):  
Go You-How ◽  
Chin Lai-Kwan ◽  
Kuah Yoke-Chin ◽  
Wei Chooi-Yi
Keyword(s):  
Crude Oil ◽  
Forecast Error ◽  
Composite Index ◽  
Oil Prices ◽  
Error Variance ◽  
Fuel Price ◽  
Forecast Error Variance ◽  
Retail Prices ◽  
The Government ◽  
Information Spillover

Malaysia has been enjoying fixed retail prices for research octane number (RON) 95 petrol and diesel as a form of subsidy from the government since 1983. As of December 2014, the pricing of RON95 and diesel officially went on a managed float mechanism. Therefore, this study examines how information on oil shocks is transmitted to FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBM KLCI) upon the announcement of subsidy cut for RON95 fuel price on 2 October 2014. The sample period of September 2013–December 2014 is separated into the pre-announcement (3 September 2013–1 October 2014) and post-announcement (2 October 2014–28 November 2014) periods. Using the forecast error variance decomposition, the results indicate that Brent crude oil prices dominate information spillover during the post-announcement period. From the perspective of investors’ behaviour, this study suggests that investors’ sensitivity towards information on oil price is elevated by the announcement of subsidy cut and steers their consciousness towards information on oil prices in making decisions.

scholarly journals Oil Prices and the U.S. Dollar Exchange Rate: Evidence from the Monetary Model

2018 ◽  
Vol 10 (4) ◽  
pp. 17
Author(s):  
Moayad H. Al Rasasi
Keyword(s):  
Exchange Rate ◽  
Forecast Error ◽  
Negative Relationship ◽  
Impulse Response Function ◽  
Decomposition Analysis ◽  
Oil Prices ◽  
Error Variance ◽  
Monetary Model ◽  
Forecast Error Variance ◽  
Positive Shock

This paper analyzes how changes in global oil prices affect the US dollar (USD) exchange rate based on the monetary model of exchange rate. We find evidence indicating a negative relationship between oil prices and the USD exchange rate against 12 currencies. Specifically, the analysis of the impulse response function shows that the depreciation rate of the USD exchange rate ranges between 0.002 and 0.018 percentage points as a result of a one-standard deviation positive shock to the real price of crude oil. In the same vein, the forecast error variance decomposition analysis reveals that variation in the USD exchange rate is largely attributable to changes in the price of oil rather than monetary fundamentals. In last, the out-of-sample forecast exercise indicates that oil prices enhance the predictability power of the monetary model of exchange rate.

scholarly journals Estimating fuel price volatility and spillover effects across different European countries

2019 ◽  
Vol 14 (4) ◽  
pp. 419-430
Author(s):  
Matei Kubinschi ◽  
Dinu Barnea ◽  
Iuliana Zlatcu
Keyword(s):  
Forecast Error ◽  
Price Volatility ◽  
Error Variance ◽  
Spillover Effects ◽  
Weak Links ◽  
Fuel Price ◽  
Eu Countries ◽  
Fuel Prices ◽  
Developed Economies ◽  
Forecast Error Variance

Abstract This paper analyses the volatility of retail fuel prices in nine different EU countries and the spillover effects between fuel prices across selected countries from Central and Eastern Europe and the Eurozone over the 2008-2019 period. In particular, we use the GARCH-GJR model in order to investigate fuel price volatility and identify potential asymmetric dynamics. Moreover, in order to assess the links between fuel prices across countries, we estimate a VAR model and compute spillover measures using the Generalised Forecast Error Variance Decomposition (GFEVD) approach formulated by Diebold and Yilmaz (2009). Our results provide evidence of weak links between retail fuel prices across EU countries, with slightly higher spillovers originating from some developed economies such as France and Italy.

scholarly journals DETERMINANT OF GOVERNMENT BOND YIELDS

2020 ◽  
Vol 1 (1) ◽  
pp. 86-99
Author(s):  
Priyo Adiwibowo ◽  
Pardomuan Sihombing
Keyword(s):  
Forecast Error ◽  
Impulse Response Function ◽  
Oil Prices ◽  
Error Variance ◽  
Government Bond ◽  
Bond Yields ◽  
Determinant Factors ◽  
Bank Rate ◽  
Forecast Error Variance

This study aims to analyze the influence of determinant factors: (i) exchange rates, (ii) inflation, (iii) CDS spreads, (iv) bid-ask spreads, (v) overnight rate, (vi) CB’s rate (Central Bank Rate), and (vii) oil prices on Government bond yields. The data used are monthly data in the period 2012 - 2018. The research method used is the Vector Auto Regression (VAR) approach. Our analysis indicated that the determinant factors have impact on government bond yields. Based on the analysis of the impulse response function (IRF), the yield is to respond to any shocks given by the long term. While through forecast error variance decomposition (FEVD) analysis, found that CDS spreads and oil prices contributed significantly to the movement of Government bond yields.

The influence of economic policy uncertainty and geopolitical risk on US citizens overseas air passenger travel by regional destination

2020 ◽  
pp. 135481662098119
Author(s):  
James E Payne ◽  
Nicholas Apergis
Keyword(s):  
Economic Policy ◽  
Forecast Error ◽  
Error Variance ◽  
Variance Decomposition ◽  
Air Travel ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Passenger Travel ◽  
Forecast Error Variance

This research note extends the literature on the role of economic policy uncertainty and geopolitical risk on US citizens overseas air travel through the examination of the forecast error variance decomposition of total overseas air travel and by regional destination. Our empirical findings indicate that across regional destinations, US economic policy uncertainty explains more of the forecast error variance of US overseas air travel, followed by geopolitical risk with global economic policy uncertainty explaining a much smaller percentage of the forecast error variance.

scholarly journals Predicting Water Availability in Water Bodies under the Influence of Precipitation and Water Management Actions Using VAR/VECM/LSTM

Climate ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 144
Author(s):  
Harleen Kaur ◽  
Mohammad Afshar Alam ◽  
Saleha Mariyam ◽  
Bhavya Alankar ◽  
Ritu Chauhan ◽  
...  
Keyword(s):  
Water Management ◽  
Short Term Memory ◽  
Forecast Error ◽  
Error Variance ◽  
Water Levels ◽  
Water Bodies ◽  
Economic Activities ◽  
Management Actions ◽  
Forecast Error Variance ◽  
Water Treatments

Recently, awareness about the significance of water management has risen as population growth and global warming increase, and economic activities and land use continue to stress our water resources. In addition, global water sustenance efforts are crippled by capital-intensive water treatments and water reclamation projects. In this paper, a study of water bodies to predict the amount of water in each water body using identifiable unique features and to assess the behavior of these features on others in the event of shock was undertaken. A comparative study, using a parametric model, was conducted among Vector Autoregression (VAR), the Vector Error Correction Model (VECM), and the Long Short-Term Memory (LSTM) model for determining the change in water level and water flow of water bodies. Besides, orthogonalized impulse responses (OIR) and forecast error variance decompositions (FEVD) explaining the evolution of water levels and flow rates, the study shows the significance of VAR/VECM models over LSTM. It was found that on some water bodies, the VAR model gave reliable results. In contrast, water bodies such as water springs gave mixed results of VAR/VECM.

scholarly journals KAJIAN AKTIVITAS EKONOMI LUAR NEGERI INDONESIA TERHADAP PERTUMBUHAN EKONOMI INDONESIA PERIODE 1998-2014

2017 ◽  
Vol 9 (2) ◽  
pp. 119
Author(s):  
Ryan Hawari ◽  
Fitri Kartiasih
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Exchange Rate ◽  
Direct Investment ◽  
Forecast Error ◽  
Foreign Debt ◽  
Trade Openness ◽  
Impulse Response Function ◽  
Error Variance ◽  
Forecast Error Variance

Indonesia is a developing country which adopts an “open economic”. That caused Indonesia economic is strongly influenced by factors that come from outside of Indonesia. External factors in this research is referred to foreign debt, foreign direct investment, trade openness and exchange rate of rupiah with USD. The analytical method in this research used Vector Error Correction Model (VECM) which will focused on Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD). Based on result of IRF, exchange rate had a positive effect to economic growth, while foreign debt, foreign direct investment and trade openness had a negative effect to economic growth. Based on result of FEVD, shock on economic growth in Indonesia affected by economic growth itself (43.21%), followed by foreign debt (26.30%), trade openness (14.16%), foreign direct investment (8.29%) and exchange rate (8.04%) Keywords: economic growth, trade openness, VECM, IRF, FEVD

THE PRICE OF COCAINE AND THE COLOMBIAN PESO: AN EMPIRICAL INVESTIGATION

2019 ◽  
Vol 19 (03) ◽  
pp. 1950015
Author(s):  
ALEXI THOMPSON ◽  
YAYA SISSOKO
Keyword(s):  
Forecast Error ◽  
Control Policy ◽  
Error Variance ◽  
Decomposition Methods ◽  
Nominal Exchange Rate ◽  
Policy Implications ◽  
Vector Error Correction ◽  
National Drug ◽  
Forecast Error Variance ◽  
National Drug Control Policy

While the underground economy is not explicitly included in the measure of (GDP), the cocaine trade has been a major source of revenue for Colombia. Using quarterly cocaine prices from 1982 to 2007 published by the Office of National Drug Control Policy, this paper uses vector error correction and forecast error variance decomposition methods to look at the relationship between cocaine prices and the peso/$ nominal exchange rate. Our results indicate cocaine prices affect the value of the Colombian peso, which leads to some interesting policy implications.

scholarly journals Alternative Model Selection Using Forecast Error Variance Decompositions in Wholesale Chicken Markets

2009 ◽  
Vol 41 (1) ◽  
pp. 227-240 ◽  
Author(s):  
Andrew M. McKenzie ◽  
Harold L. Goodwin ◽  
Rita I. Carreira
Keyword(s):  
Forecast Error ◽  
Error Variance ◽  
Autoregressive Models ◽  
Model Specification ◽  
Decomposition Approach ◽  
Vector Autoregressive ◽  
Forecasting Performance ◽  
Causality Tests ◽  
Forecast Error Variance ◽  
Variance Decompositions

Although Vector Autoregressive models are commonly used to forecast prices, specification of these models remains an issue. Questions that arise include choice of variables and lag length. This article examines the use of Forecast Error Variance Decompositions to guide the econometrician's model specification. Forecasting performance of Variance Autoregressive models, generated from Forecast Error Variance Decompositions, is analyzed within wholesale chicken markets. Results show that the Forecast Error Variance Decomposition approach has the potential to provide superior model selections to traditional Granger Causality tests.

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