Var Analysis On Mutual Relationship Between Stock Price Index And Exchange Rate And The Role Of World Oil Price And World Gold Price
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| Author | : Filus Raraga |
| Publisher | : |
| Total Pages | : 17 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
This study aims to analyze the influence of world oil price and world gold price on mutual relations between exchange rate and stock price index. This study uses monthly data of exchange rate (IDR/US$) and JCI from January 2000 to January 2013. Co integration test was used in analyzing long-term relationships between variables. VAR model was used in determining whether world oil prices and world gold price affect the exchange rate and stock index, and analyze the interrelationships between exchange rate and stock price index. Impulse Response Analysis is used to determine the response of exchange rate and the stock price index on world oil price shocks and world gold price shocks. Analysis of Variance Decomposition is used to determine the role of world oil prices and world gold prices in explaining the movement of exchange rate and JCI. Co integration analysis results show that all the variables, ie, world oil prices, gold prices, exchange rates and JCI have long run co integration. The analysis showed that the world oil price has significant effect on the exchange rate but has no effect on JCI; the world gold price has no effect on exchange rate and JCI; exchange rate has significant effect on JCI and vice versa. Granger causality test showed that JCI and exchange rate have bidirectional relationship. Impulse Response Analysis results indicate that the world oil price shocks responded negatively by exchange rate; shocks in world gold prices responded negatively by JCI and exchange rate; exchange rate changes responded positively by JCI, and JCI changes responded positively by exchange rate.
| Author | : Vanita Tripathi |
| Publisher | : |
| Total Pages | : 28 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
This paper examines the long run and short run dynamics among oil prices, exchange rates and stock prices in India (one of the fastest growing emerging markets in the world) over the most recent 15 year period 1997-2011. Using Johansen's Co integration test we find the existence of long run equilibrium relationship among oil market, foreign exchange market and stock market in India. The short term dynamics among the three markets are analyzed using Vector Autoregression (unrestricted as well as VECM), VAR causality/Block Exogeneity Wald test and Impulse response analysis. We find unidirectional causality from stock market to oil market. An impulse originating in foreign exchange market results in a profound drop in stock as well as oil prices and is statistically significant for about three weeks in oil market and two weeks in stock market. The domino effect of up-waves in stock market is positive for oil market and remains statistically significant for few weeks, while being of opposite tendency in foreign exchange market. The optimism of oil market bulls up stock market in India while creating bearish trends in foreign exchange market. An assessment of impulse response graphs in pre-crisis, during crisis and post crisis period exhibits that the riposte of all the variables to a shock generating from within stays for a relatively longer period during crisis as compared to pre and post crisis period. These results have wider implications for market integration, policy makers and investors at large. Since these markets are integrated rather than segmented, from the perspective of investments, risk reduction cannot be achieved in the long run by holding assets from these markets in the same portfolio. However diversification opportunities are not ruled out in the short run. Stock market turns out to be the leader in all the three markets especially after the recent financial crisis. Rapidly rising stock prices in India signal the expectation of higher economic growth ahead. If the stock prices get trapped in a bubble, however, oil prices will overshoot in relation to economic fundamentals.
| Author | : Joko Purnomo Raharjo |
| Publisher | : LAP Lambert Academic Publishing |
| Total Pages | : 68 |
| Release | : 2012 |
| Genre | : |
| ISBN | : 9783659105302 |
The study of the relationship between the exchange rate and the stock index has been a popular topic among the scholar around the world. Situations and variety in the data affected the findings of the studies. Daily data, monthly data and exchange rate type data yield different result. This thesis examined the sample period using the Johansen Cointegrative Method to determine whether there is a cointegrative relationship among the variables. A short run analysis was conducted by employing the VECM and VAR model. The cointegration analysis, exhibits evidence for the existence of a long run relationship among the JCI, the exchange rate of the Rupiah per Yen and also the N225. The findings are very important for policy makers. Anything that affects the stock market, especially for Indonesia, Japan and US, could have an effect on the Indonesia future due to the complexity and interest of the country. However, by understanding important facts that have been revealed from the study, policy makers could anticipate and maintain a good economic atmosphere.
| Author | : Danilo Pavlićević |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2022 |
| Genre | : Economic policy |
| ISBN | : |
Ever since crude oil became a lifeline to the world economy, there is no doubt that oil is the most traded commodity in the world’s stock markets. There have been numerous articles and research papers written about the relationship between oil prices and stock markets, and the correlation between the two. Vast majority of them have shown that there is a correlation between them, and that changes in one affect the other. However, very few have examined the determinants of co-movements between oil prices and stock markets using a vector autoregressive (VAR) model. This thesis examines determinants of co-movements between three oil importing countries stock market indices, as well as three oil exporting countries stock indices and the crude oil prices. What makes this study relevant is that it is not only examining stock indices of randomly selected countries, but it shows indices of three chosen oil importing and oil exporting countries. For the purpose of this research the oil importing countries used to demonstrate the effects in changes in determinants of co-movements between oil prices and stock markets are USA, China, and Germany. Each is chosen to represent certain parts of the world. For the oil exporting countries, we excluded countries whose entire GDP or at least huge portion of it, is only consistent of oil exports. Therefore, Norway, the European largest oil exporter, Russia, the world's second largest oil exporter, and Canada, largest North American oil exporter, are taken in order to reflect the effects of changes in determinants of co-movements in their respective stock markets. Economic policy uncertainty Index (EPU), Geopolitical Risk Index (GPR), the exchange rate between US dollar and all the other countries’ currencies. These are the factors affecting both oil prices and stock markets. EPU Index shows how often do national newspaper articles in a certain country write about issues pertaining to the economy uncertainty and policy-related matters. When it comes to GPR Index, it is based on measuring the frequency of words related to geopolitical tensions in leading international newspapers. The US dollar is the world’s most important currency; therefore, all the other countries in the world strive to maintain steady exchange rate between the US dollar and currencies of their own. By using vector autoregressive (VAR) model, this study will show the effects of each determinant on stock markets of US, Germany, China, Russia, Norway, and Canada.
| Author | : Eleftherios Ioannis Thalassinos |
| Publisher | : |
| Total Pages | : 10 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
Dollar devaluation creates a huge problem in the world oil industry, leading to a vast decrease in the revenues of the oil producers, though the local oil producers use the local currencies to operate and the oil price is evaluated in dollars. The depreciation of the US dollar reduces the effect of the high prices in oil, making it rather cheap for all the countries and especially for the Eurozone area. The record high exchange rate of the Euro vis-à-vis dollar followed by a subsequent high of the crude oil price, suggests on a relation between the price of the oil and the evaluation of the US dollar. The main aim of this research is to construct an restricted Vector Autoregressive estimation model to simulate the relation between the exchange rate of the U.S. dollar and Euro against the West Texas Intermediate (WTI) prices for light crude oil, in connection with the impulse response of the prices to the various shocks. Lastly, a co integration test will illuminate the possibility of simultaneous long term integration along with Granger causality test to estimate the direction of causality in variables.
| Author | : Yan Hu |
| Publisher | : |
| Total Pages | : 109 |
| Release | : 2017 |
| Genre | : Futures market |
| ISBN | : 9781369681000 |
When the crude oil price rocketed to $147 per barrel in July 2008 and then dropped to as low as $30 per barrel in December 2008, it catalyzed a hot debate about the factors of oil price fluctuations. A large number of papers argue that the main driver of the oil price fluctuations from 2003 to 2008 was due to economic fundamentals in the form of rapidly growing oil demand with stagnant oil supply. However, a different view is that speculation in the oil futures market caused the oil price to drift away from the level justified by the fundamental market forces of demand and supply because a large amount of investment flowed to the oil futures market during this period. This dissertation links the oil financial and spot markets through the oil futures-spot price spread and investigates if the financial activity in the oil futures market plays a critical role in oil spot price fluctuations between 2003 and 2008. In addition, this dissertation also discusses the recent oil price drop since July 2014 and studies whether the main driver of this recent oil price change is similar to that of the oil price change in 2008. ☐ Unlike other related literature that uses standard structural VAR, this dissertation applies a Time Varying Parameter Vector Autoregression (TVP-VAR) model with stochastic volatilities that can capture both time-varying relationships between economic aggregates and time-varying impacts of different oil shocks. This approach disentangles the oil financial speculation shock from economic fundamental shocks. In the meantime, the findings of the TVP-VAR model are compared with those of the Bayesian VAR with stochastic volatilities (BVAR-SV) model, a benchmark model in this dissertation, to see if incorporating time-varying coefficients in the model can give better results. The results of the comparison show that the time variations in coefficients are insignificant and imposing time varying coefficients in the model not only increases the estimation computation work load but also affects the model’s estimation accuracy. Therefore, the conclusion in this dissertation comes from the results of the BVAR-SV model. The results imply that the large proportion of the oil price changes from 2003 to 2008 can be explained by the oil demand shock but this proportion has been decreasing since 2005. In addition, the contribution of the oil financial speculation shock has increased substantially in recent years. In sum, the main driver of oil price change is oil demand from 2003 to 2008, whereas the main driver from 2014 to 2015 is oil financial speculation in the oil futures market.
| Author | : Naser Niknam Esfahani |
| Publisher | : |
| Total Pages | : 113 |
| Release | : 2016 |
| Genre | : |
| ISBN | : 9781369371543 |
Abstract : The purpose of this study is to investigate the impact of oil income and the gold price fluctuation on the stock market of Iran, and to examine whether consideration of the oil and the gold markets followed by other investment markets, such as the real estate market and the foreign exchange market have any significant impact on the stock market behavior. This study examines the impact of the oil income and gold price fluctuation, as well as other macroeconomic indicators such as housing construction, deposit interest rate, foreign exchange rate, consumer price index, and gross domestic products on the Iranian stock market, as measured by the quarterly data from January 1990 to December 2012. First, regression analysis was applied for oil revenue, housing activities, deposit interest rate, foreign exchange rate, CPI, and GDP to examine the stock market reaction to each market activity. After this, ceteris paribus, oil revenue was replaced with gold price to examine whether the price of gold without consideration of the oil revenue had any impact on the stock market activity. Finally, the model was run to examine the impact of all variables, including oil revenue and gold price, upon stock market activity. In a separate model, this paper also examines the relationship between all of the above-mentioned variables and stock market volatility. In the next phase, the impulse response function based on the vector auto-regression model was generated to examine the behavior of the stock market followed by a shock to each independent variable. Because Iran is an oil-exporting country—not an oil-importing country—economic forces, market structure as well as the investment culture and investing policies are different in Iran than in Western nations or other oil-importing countries, it may not be wise or productive to analyze investment in the Iranian stock market from the same perspective or with the same methods used when analyzing investment in Western countries. Because gold, foreign currencies, and the real estate market are the most popular and common investment markets in Iran for domestic investors, this paper aims to determine whether there is any relationship between those markets and the stock market in general from an investment point of view.
| Author | : Charbel N. Kiwan |
| Publisher | : |
| Total Pages | : 86 |
| Release | : 2011 |
| Genre | : Correlation (Statistics) |
| ISBN | : |
The study analyzes the correlation between gold, oil and US dollar index.The valuation of the three has been a global concern for large developed economies and small underdeveloped economies. Most of the previous studies have focused on the relationship between two of the above, hence this study shows how the weakness or strength in one will affect the other unlike previous studies. Major macroeconomic fundamentals are introduced in a model including gold, oil and exchange rate and the constant changes in these figures shows the impact magnitude on the prices at the market. The correlation between gold and oil, gold and exchange rate and oil and exchange rate is tested to determine the nature of the relationship between the three variables. In addition, the regression analysis will show the effect of price changes in each variable on the other, and how changes in macroeconomic fundamentals result in a price fluctuation of gold, oil and dollar rate. The dollar exchange rate serves as a medium through which gold prices and oil prices affect each other indirectly. Several political and economical events occur, leading to stuctural breaks in the relationship of the variables but the positive correlation remains dominant. As a result, gold serves best as a reserve currency than the US dollar since it is not directly related to the situation of the US economy, but whenever there is a shock in the market, an investor should diversify his portfolio into non-US financial assets since oil, gold and US dollar prices are affected by the US economic performance.
| Author | : Sakib Bin Amin |
| Publisher | : |
| Total Pages | : 16 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
The link between stock market prices and oil prices has drawn considerable attention in recent decades because the risk and uncertainties associated with oil price volatility affect investor's portfolios, particularly, those investors seeking to make optimal portfolio allocations. This paper investigates the relationship between the oil price and the stock market index in South Asia. Based on a sample of four countries, namely Bangladesh, India, Pakistan, and Sri Lanka for the period 1997-2017, we use the nonlinear Autoregressive distributed model estimated by Pooled Mean Group (PMG) estimator. We show that there is a positive relationship between the world oil price and stock market index; and that the response of stock market index to positive and negative oil price shocks are asymmetric. Counter to prior research in developing countries, our findings imply that higher oil prices in the world market stimulate stock prices which suggests that the stock markets in the South Asian region do not follow the Efficient Market Hypothesis (EMH) for which the shocks in the crude oil market are not rationally signaled in the financial market. Another plausible justification of this movement in the same direction, as explained by Bernanke (2016), is that both oil price and stock prices are reacting to a change in some common underlying factor, which he calls the global aggregate demand and market risk aversion.
| Author | : Toros Sajian |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2005 |
| Genre | : Consumer price indexes |
| ISBN | : |
This paper demonstrates an empirical link between gold price, consumer price index, Euro exchange rate, the Brent oil price and the Dow Johns industrial average. The research shows that there is a relationship between the gold price and each of the other variables, each one alone and all together. In the first part, simple regression models are used to find out the relationship between the gold and the other variables. In the last part of the paper, we do a multiple regression model by taking all the dependent variables together to find their relationship with the gold price, using economic data from 1997 to 2005.
