The Impact of Macroeconomic Factors on the US Stock Exchange

The impact of gold and crude oil prices on stock market in Turkey: Empirical evidences from ARDL bounds test and combined cointegration

The interaction between oil and stock market returns is one of the most important relationships that have a significant influence on the economy of any country all over the world. Therefore, this paper investigates the impact of crude oil prices on the Chinese stock market and selected industries by using the VAR-DCC-GARCH model over the period from December 26, 2001, to April 30, 2019. The empirical results show that the impact of Brent crude oil prices on the Shanghai Composite Index and selected industries is significant. However, there are some variations in these relationships and the degree of influence on each differs during different sample periods. Brent crude oil prices exert substantial influence on some specific industries, like mining, chemical, nonferrous metals, and steel. Whereas, the volatility spillover effect of Brent crude oil prices is stronger within the mining, chemical, steel, nonferrous metal, building materials, building decoration, electrical equipment, electrical equipment, textile and garment, light manufacturing, public utility, and transportation industries than within other industries. When oil prices change abruptly, the risk of spillover impacts of oil prices on stock markets will also increase. In conclusion, the impact of Brent crude oil prices on the Chinese stock market is generally positive. Furthermore, the subsequent volatility of Chinese stock market prices will, in turn, influence the volatility spillover of Brent crude oil prices on the indexes. The result is an ongoing back and forth of changes in price volatilities.

This paper investigates factors affecting Vietnam’s stock prices including US stock prices, foreign exchange rates, gold prices and crude oil prices. Using the daily data from 2005 to 2012, the results indicate that Vietnam’s stock prices are influenced by crude oil prices. In addition, Vietnam’s stock prices are also affected significantly by US stock prices, and foreign exchange rates over the period before the 2008 Global Financial Crisis. There is evidence that Vietnam’s stock prices are highly correlated with US stock prices, foreign exchange rates and gold prices for the same period. Furthermore, Vietnam’s stock prices were cointegrated with US stock prices both before and after the crisis, and with foreign exchange rates, gold prices and crude oil prices only during and after the crisis.

This paper examines the impact of the exchange rate, oil price and gold price on the Kuwaiti stock market using a wavelet analysis, namely, cross-wavelet coherency and partial cross-wavelet coherency. This method is used to test for nonlinear causality and decompose the data into various time frequencies to better understand various investment horizons. These interactions were examined based on daily observations from 02 January 1996 to 28 September 2017. The findings show a positive relationship between stock market and exchange rate in all frequencies. This relationship is being remarkably weak once the impact of oil price is removed. Besides, the correlation between the stock market and oil price is positive in low-frequency bands and will be reduced after eliminating the effect of the exchange rate. Regarding gold price, there is only a negative short-term relationship with the stock market during crisis periods. In summary, the impact of oil price is indirectly positive on the stock market by leading the movement of the exchange rate.

PurposeThe purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.Design/methodology/approachThis study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.FindingsThe findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.Research limitations/implicationsThis study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.Practical implicationsThese findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.Social implicationsThese findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.Originality/valueUsing a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

Purpose The purpose of the study is to find out the impact of gold and oil prices on the stock market. Design/methodology/approach This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test. Findings The data analysis results showed that gold and oil prices have a significant impact on the stock market. Research limitations/implications Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set. Originality/value This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

Oil Prices and Profitability Performance: Sector Analysis

The dynamic linkages among crude oil price, climate change and carbon price in China

The effects of oil and gold prices on oil-exporting countries

Research background: The effects of oil price fluctuations on the macroeconomic performance in oil-importing and oil-exporting countries have stimulated considerable research activity. However, the debate is far from being closed. Purpose of the article: This paper revisits the impact of crude oil price on economic activity in the Gulf Cooperation Council oil-exporting countries. The study covers a relatively long period spanning from 1960 to 2018. Methods: The empirical investigation accounts for structural breaks, nonlinearity, and non-normal ?distribution of data. The Kapetanios (2005) structural breaks unit root test?? and ?Saikkonen?Lütkepohl (2000a, b, c) cointegration test with structural shifts are implemented to examine the stationary properties of data and the presence of cointegration between variables, respectively. Moreover, the quantile regression is employed to assess whether the impact of oil price on real GDP differs across different states of the economy. Findings & Value added: Empirical results suggest the absence of long-run cointegrating relationships between oil price and GDP in all countries. The quantile regression reveals that oil price does not affect real GDP in the same way across countries and for different business cycle phases. More specifically, the symmetric quantile regression findings reveal that oil price exerts a positive impact on GDP in all countries and that the effect is higher during the recession than expansion states. The asymmetric quantile regression shows that GDP reacts to positive oil price changes in all countries. However, only the Emirati and Omani GDPs are affected by negative oil price changes.

This paper has made an attempt to evaluate the combined impact of crude oil prices and exchange rate on the performance of Indian stock market. As the impact of dollar nominated oil prices on stock prices may not be quite relevant for Indian context. Therefore, in this study WTI Crude oil prices per Dollars along with the USD/Rupee exchange rate would be more meaningful and relevant to understand the impact of oil prices on stock market by using monthly data from 2003 to 2016 for S&P CNX Nifty Index, WTI Crude oil prices per Barrel (Dollars) and Dollar/Rupee Exchange rate. All the series were found to be stationery at First difference. The Granger causality tests revealed that there exists a Bi directional causality between stock prices and exchange rates in the short run i.e. stock prices lead exchange rates in the short run, but result of Johansen cointegration suggested that there is no long run relationship between these two financial variables. The results of the Johansen cointegration test suggest absence of any long term relationship between WTI crude oil price, USD/Rupee exchange rate and stock prices in India. The result of forecast error variances suggested that USD/Rupee exchange rate is influenced by Stock market performance. The forecast error variances of USD/Rupee exchange rate is significantly explained by the value of Nifty. Results also indicate that the values of oil price and exchange rate are comparatively less exogenous than the Indian stock market. Particularly, the contribution of Stock market shocks to the USD/Rupee exchange rate is greater than that of WTI Crude oil price shocks in all the periods.

This study investigates the impact of oil, gold, and natural gas prices on clean energy stock prices using a comprehensive set of statistical techniques. Daily and monthly data for the period 2013–2023 were obtained from Yahoo Finance, S&P Dow Jones Indices, and Investing.com. Correlation, pairwise regression, multivariate regression, and ANOVA analyses were performed. The strongest association was identified between clean energy stocks and gold prices (r = 0.82), while weaker correlations were observed with oil (r = 0.22) and natural gas (r = 0.27). Pairwise regression analysis confirmed the significance of gold as a predictor (R² = 0.72, p < 0.01), whereas models involving oil and gas were found to be statistically insignificant (R² < 0.15, p > 0.2). A multivariate regression model incorporating gold indices and prices yielded R² = 0.83 with all variables statistically significant at p < 0.05, confirming gold’s dominant explanatory power. The statistical robustness of the selected factors was further validated through ANOVA tests (F-statistics > F-critical, p < 0.01). The findings indicate that gold functions as a safe-haven asset with a measurable influence on clean energy stock valuations, while oil and gas prices exert negligible effects. The results highlight the importance of incorporating gold-related indicators into clean energy investment models and provide a quantitative foundation for future macroeconomic and policy-oriented analyses.

Impact of oil and gold prices on Bitcoin price during Russia-Ukraine and Israel-Gaza wars

This paper aims to examine the impact of crude oil price on firm value in two green energy industries, namely solar photovoltaic industry (hereafter, SOLAR) and LED lighting application (hereafter, LED) in Taiwan and the U.S. This paper applies and extends Ohlson (1995)'s valuation model to examine the role of oil price as a pricing factor in the valuation models in two green energy industries between two countries. The empirical results support that oil price has positive association with firm value of green energy industries. The positive relationship between oil price and firm value is different across industries and across countries. Compared with that in LED, the link is more positive in SOLAR only in the U.S. Further: the link is more positive in the U.S. than in Taiwan, especially for the solar industry.

Oil has been one of the primary wellsprings of Indonesia's revenue, either from government spending plan or balance of payments purpose of perspectives. Because of supply and demand of oil on the planet market, prices of oil, either ICP, Brent UK, or WTI, had been decay of late. Oil prices and economic wellbeing are essential markers to see the achievement of Indonesia's improvement execution. The utilization of oil as the world's fundamental energy source when all is said in done and Indonesia specifically is driven by industrialization. The more ventures, the more prominent the energy resources required. In a similar setting, economic wellbeing will likewise expand oil demand. Oil has a strategic nature and is a vital ware that influences the world economy. Both oil exporters and merchants are probably going to feel the impacts of oil price advancements. Oil prices dropped pointedly since June 2014 finishing a four – year time of relative price strength. The size and speed of decay has been noteworthy yet not remarkable. This exploration plans to analyze the impact of crude oil prices on economic wellbeing in Indonesia. Data on crude oil prices and economic growth are yearly time series data stretching from 1987 to 2016. The aftereffects of co-integration tests demonstrate that there is no long-term connection between crude oil prices and economic wellbeing. In any case, the estimation of the autoregressive distributed lag (5.0) model demonstrates that in the short term, there is the impact of crude oil prices toward economic wellbeing. Keywords: Crude oil, oil price, growth, Autoregressive distributed lag model, Indonesia JEL Classifications: E31, A10DOI: https://doi.org/10.32479/ijeep.8311