Dynamics of crude oil price shocks and major Latin American Equity Markets: A study in time and frequency domains

2017

This paper studies how sensitive are the stock market returns of Argentina, Brazil, Chile, Colombia, Mexico, and Peru to international oil price fluctuations (West Texas Intermediate). A panel data analysis with a random effects model, using the world stock market index Morgan Stanley Capital International World Index, domestic money market rates, and currency exchange rates as control variables suggests that, after controlling for the individual countries non-observed characteristics, oil prices explain positively monthly returns of the stock markets. The rest of the control variables have the desired sign and statistical significance; the sample data includes monthly observations from 2000 to 2015. The main finding of this research is that it does not matter if countries are exporters (Brazil, México, Venezuela, Colombia and Argentina) or importers (Peru and Chile) of oil, in the region as a whole, an increase of oil prices has a positive effect on stock returns.

2014

Economic Modelling, 2012

This paper investigates the effects of oil price shocks on stock market returns in emerging countries. It differs from previous works in three main aspects: i) we distinguish three groups of countries, the largest net-oil importing countries, the moderately oil-dependent countries, and the largest net-oil exporting countries; ii) The potential influence of bullish and bearish market conditions on the causal relationship between oil and stock returns is controlled for in our analysis; iii) The empirical investigation is based on an analysis of long-term correlation and a conditional multifactor pricing model. Using data from twenty-five emerging countries, our results suggest that oil price risk is significantly priced in emerging markets, and that the oil impact is asymmetric with respect to market phases.

2018

The purpose of this research is to investigate the impact of oil price variation on stock returns and exchange rate on country's economy. It estimates a Vector Auto-Regressive model with Impulse Response function. In addition to that ADF test and granger causality test has also been applied. The countries under consideration are Russia, China, Brazil, Mexico, Saudi Arabia, and Venezuela. These are all oil producing and exporting countries with the exception of Brazil and China who only produce oil. Independent variable under consideration is crude oil price and dependent variables are stock market returns and exchange rate. Data was collected on monthly basis and data range is from January 2001 to July 2016 with 187 total observations. It is shown that oil price variation does not make significant impact on Russia, Mexico and Venezuela's Stock market returns and exchange rate. Saudi Arabia is the only country among oil exporters in which oil price volatility made a significa...

This paper analyzes the impact of oil prices on stock prices of selected major oil producing and consuming countries with nominal exchange rate as additional determinant. Daily stock prices, oil prices, and exchange rates for six countries (Mexico, Russia, Saudi Arabia, India, China, and the US.) from January 26, 2000 to January 22, 2010, are modeled as a cointegrated system in Vector Autoregressive analysis. Variance decompositions and impulse responses are also estimated. Our empirical results support unit root in all variables (except Saudi Arabia and the US exchange rates that are stationary in levels and first difference). Evidence of one long-run relationship (Mexico inconclusive) in Saudi Arabia, India, China and the US is supported, while Russia exhibits two long-run relationships. The results from the long-run exclusion test suggest all three variables cannot be eliminated from cointegrating space in all countries (except Mexico), while the weak exogeneity test reveals all variables to be responsive to deviation from long-run relationships (except China). Unlike the exchange rates, stock and oil prices are nonresponsive to deviations in the long-run in China. In all countries, variance decomposition and impulse response tests confirm existence of oil prices and exchange rates influences over stock prices.

arXiv: Statistical Finance, 2016

In this chapter we studied the nonlinear co-movements between the Mexican Crude Oil price, the Mexican Stock Market Index and the USD/MXN Exchange Rate, for the sample period from 1994 to date. We used a battery of nonlinear tests, cf. (Patterson & Ashley, 2000) and one multivariate test, in order to determine the dynamic co-movement exerted from the oil prices to the stock and exchange rate markets. Such co-movement and time windows are exposed using the Brooks & Hinich (1999) cross- bicorrelation statistical test. The effects of oil spills on other markets have been studied from different angles and on several financial assets. In this study, we focus our attention on the detection, not only of the correlations amongst markets but on the epochs in which such nonlinear dependence might occur. This is important in order to understand better, how the markets that drive the economy interact with each other. We hope to contribute to the literature with such findings, filling a gap in t...

Vilakshan - XIMB Journal of Management

Purpose This study aims to establish the dynamic relationship between international crude oil prices and Indian stock prices represented by the Bombay Stock Exchange (BSE) energy index. Design/methodology/approach Using Johansen’s cointegration test, vector error correction (VEC) model, impulse response function and variance decomposition test the study tries to ascertain the short-term and long-term dynamic association between the oil price shock and the movement of stock price and Granger causality test is applied to find out the nature of causality. Findings Considering vector autoregression estimation, the present study analyzes the relationship between the variables and tries to make a valid conclusion. The result of the co-integration test exhibits the presence of a long-term association between these two macro-economic variables during the period under study. Also, in the short-run VEC Granger causality result reveals that the movement of international crude oil price signifi...

Energy Economics, 2016

This study examines the relationship between oil price volatility and stock returns in the G7 economies (Canada, France, Germany, Italy, Japan, the UK and the US) using monthly data for the period 1970 to 2014. In order to measure oil volatility we consider alternative specifications for oil prices (world, nominal and real prices). We estimate a vector autoregressive model with the following variables: interest rates, economic activity, stock returns and oil price volatility taking into account the structural break in the year 1986. We find a negative response of G7 stock markets to an increase in oil price volatility. Results also indicate that world oil price volatility is generally more significant for stock markets than the national oil price volatility.

International Journal of Business and Management, 2013

The aim of this paper is to study the impact of oil price fluctuations on the stock markets and the interest rates from oil importing and oil exporting countries. To this end, Vector Autoregressive (VAR) models are estimated and pairwise Granger Causality tests are performed to the stationary series in order to analyse the short-term relationships among the variables. Also, the Johansen approach for multiple equations is carried out in order to test for cointegration among the series. Finally, the existence of cointegration set the estimation of Vector Error-Correction Models (VECMs) to investigate the long-term links between the financial variables and the oil prices. The major findings of this paper include: first, the interaction between the oil prices and the stock markets is much stronger than with the interest rates in the short and in the long-run. Second, the impact on oil importing countries is more significant than on oil exporting countries. Finally, it might be possible that the fluctuations in oil prices have different effects on developed and developing countries.

Cogent Economics & Finance , 2022

The study examines the vital connection between stock returns and oil price changes for oil-exporting/importing countries separately. We present evidence employing granger causality, impulse response, and error variance decomposition based on panel vector autoregression. The results of panel granger causality suggested that after the oil price crash owing to the covid-19 pandemic, the interdependence between oil and stock price changes increased. Similar results were revealed by impulse response graphs and forecast error variance decomposition. Specifically, in the period marked by the rapid outbreak of the covid-19 pandemic, causality from oil to stocks increased. Although we found that both oil-exporting and oil-importing countries were affected in a similar way, oil price changes had a larger impact on oil-exporting countries. The findings of the present study have implications for investors and fund managers. By incorporating crude oil price in the prediction models, the accuracy of the stock returns forecast can be improved.