Dynamic Connectedness Among Oil Prices, Exchange Rate and Consumer Inflation: New Evidence from India

Understanding the concept of time scales is crucial when modeling economic and financial decisions. Within the time-frequency domain, this study delves into the relationship between fluctuations in oil prices and exchange rates across major oil-importing and exporting countries. The investigation employs various cross-wavelet techniques within the continuous wavelet transform framework, with a particular focus on wavelet coherence and phase-difference over the period 2000 to 2020. The results underscore a notable diversity in the connection between the oscillations of oil prices and exchange rates across diverse countries. This relationship is subject to temporal variations and is contingent upon the specific time horizon under consideration. In particular, our analysis reveals strong co-movements between oil prices and exchange rates across various time intervals and frequencies. Importing oil countries like New Zealand, Singapore, Brazil, and Taiwan exhibit particularly pronounced co-movements. Similarly, exporting oil countries such as Kuwait, Mexico, Russia, and Canada also display strong associations between oil prices and exchange rates. These correlations are intricately tied to key macroeconomic events, further highlighting the complex interplay between oil prices and exchange rate movements in different global regions. While a robust connection is evident in numerous countries, the strength of the relationship appears significantly weaker in several others. This variance underscores the nuanced nature of the association between the fluctuations in oil prices and exchange rates across the global landscape.

The study aims to analyze the co-movement between oil prices, BRICS nations’ exchange rates, and stock markets. Grasping these interrelationships is essential for understanding how global energy price shifts broadly affect the economies, particularly those of developing nations.The study employs wavelet coherency analysis on daily data, examining the association between crude oil (Brent crude), exchange rates (Brazilian Real, Russian Rubble, Indian Rupee, Chinese Yuan, and South African Rand), and stock markets (BOVESPA of Brazil, Moscow Exchange of Russia, Nifty50 of India, Shanghai Composite of China, and JSE FTSE of South Africa) across both temporal and frequency domains.This study reveals strong comovements, especially during periods of global economic instability, such as the impact of the COVID-19 pandemic and the Russia-Ukraine war. During such periods, oil prices and stock market indices tend to move in tandem, while oil prices and exchange rates show an inverse relationship. The study also reveals a decoupling of crude oil from both share markets and exchange rates during normal economic conditions. This decoupling suggests that outside of a chaotic period, the relationships weaken. However, the co-movements among the variables for China are notably weaker, even during economic upheavals, than in other BRICS nations. Understanding these relationships can aid in informed decision making and strategies in the face of global economic turmoil. AcknowledgmentThis study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2025/R/1446).

We study connectedness and causality between oil prices and exchange rates dynamically. Using data on the WTI and exchange rate returns for six countries in which oil production is a major production activity, we show that oil prices are net receptors of spillovers from excahnge rate markets. Connectedness exhibits important time variation and presents a positive trend during our sample period. We find evidence of bidirectional causality between oil prices and exchange rates, which presents also considerable time-variation. Causality is identified for longer periods of time from oil prices to exchange rates. However, we also find evidence of reverse causality, mainly in the period after the Subprime Financial Crisis. Our results provide evidence supporting the hypothesis of the financialization of oil markets.

PurposeThis paper aims to examine the relationship between exchange rate and oil prices in Algeria over the period 2004Q1–2019Q4.Design/methodology/approachThe nonlinear autoregressive distributed lag method is used to capture the potential asymmetric relationship among oil prices and the exchange rate. Frequency domain spectral Granger causality test is also applied to investigate the causal linkage between the two variables. The wavelet coherence is applied to analyze the evolution of this relationship both in time and frequency domains.FindingsThe empirical results reveal evidence of long-run asymmetric effects of oil price on Algeria’s real effective exchange rate (REER), implying that an increase in oil price causes a real exchange rate to appreciate, while a decrease in oil price leads to a real exchange rate to depreciate. More specifically, it is found that the impact of negative oil price shocks is higher than the one associated with positive shocks. The spectral Granger causality results further indicate that there is unidirectional causality running from oil price to REER in both medium and long run. The wavelet coherence findings provide evidence of some co-movement between the REER and oil price and point out that the oil price is leading real exchange rate in the medium and long terms.Originality/valueThis study contributes to the literature by investigating the asymmetric impact and the time domain causal linkage between oil price fluctuations and real exchange rate in Algeria.

The concept of time scales is essential for modeling financial decisions. This paper investigates time–frequency relationships across time scales between stock market returns, crude oil prices and exchange rates by applying wavelet analysis technique over the period 1999 to 2021. We find evidence of several strong co-movements between oil price and stock market and between oil price and foreign exchange rate in India. Each of these associations is linked with some important macroeconomic events. This implies economic shocks in developed market have a spillover effect on Indian market. The phase relationships indicate stock returns are in phase with oil prices and exchange rates are in out of phase with oil prices. We find that the impact of volatility at lower scale has a short term effect on the variables. Further, the wavelet coherency at high scale has slower changes with long term effect on the relationship between the variables of our interest. These results are useful for investors aiming specific time horizon of their investment and preferences, for portfolio managers and in risk assessment. Understanding the leading and lagging relationships will also help in business cycle based investing by detecting the subsequent business cycle fluctuations and forecasting the trend.

The study examines the co-movement between oil price and macroeconomic indicators such as exchange rate and stock indices of major oil importing countries. We differ from previous studies by examining the macroeconomic dynamics of major oil-importing countries during all economic cycles across different frequencies, using wavelet coherence analysis. We use nominal price rather than real price to make the results more meaningful for traders and institutional investors. Our analysis is based on 3012 observations covering the period 2003-14 for fifteen major oil importing countries. Wavelet coherence analysis indicates a high coherence between oil price and macroeconomic indicators across all the countries during the financial crisis. The nominal exchange rates tend to have a negative relationship with benchmark oil prices except Japan in the long run and South Korea in the medium run. Stock indices tend to have a positive relationship with benchmark oil prices in both long and medium run. S&P is leading the oil price, whereas SSE50, Nikkei 225, NIFTY, KOPSI, DAX, CAC, IBEX, FTSSI, FTSEMIB, AEX, TWSE, XU 100, LQ45 and BEL 20 are lagging the oil price in the long run. In the medium term, except for NIFTY, oil price is leading the stock market index. Overall, the results indicate that the oil price and stock indices of the major oil-importing countries are correlated in the long and medium term, but not in the short term. The lead–lag relationship between oil price and macroeconomic indicators are observed to change across frequency and time. While exchange rate offers diversification benefits, stock market indices provide no diversification avenues, since the pattern of co-movement of stock market indices and oil prices are similar across all oil importing countries. The results have implications for individual traders and institutional investors while designing their portfolio for short, medium and long term time horizons.

Cointegration test of oil price and us dollar exchange rates for some oil dependent economies

The study evaluates the channel of volatilities and returns between global oil prices and exchange rates of 21 developing countries. The structural vector autoregression (SVAR) findings are that oil-producing and exporting countries would have their exchange rates fluctuate slightly due to changing oil prices. For Markov-regime switching estimations, whereas, exchange rate volatility does not significantly influence volatility in oil prices at both regimes of flexible and fixed exchange rates, there is the presence of significant volatility spill-over from oil prices to exchange rates. Oil price movements do significantly induce appreciation or depreciation of exchange rates. In effect, volatilities in exchange rates do not trigger volatilities in oil prices but positively and considerably influenced crude oil returns in the fixed regime by 0.59%. Notwithstanding the 0.092 low transition probability, all other probabilities that the influence of volatility in the exchange rate on oil market volatility would persist are high for both flexible and fixed regimes of exchange rates. The significant positive coefficients of exchange rates together with high transition probabilities reported are indicative of rising exchange rates, implying devaluation and hence, a negative influence on oil returns and prices. Market agents can therefore diversify risks by investing in oil markets and forex markets independently.

This paper examines the relationship and related causality patterns of oil price volatility and exchange rate volatility of a group of oil-dependent economies before and after the 2008–2009 global financial crisis. We employed weekly time-series data of oil price and exchange rates for 2000–2007 (pre-crisis) and 2010–2016 (post-crisis). United States dollar exchange rates are for Ghanaian cedi, Nigerian naira, Russian ruble, Indian rupee, South African rand, and the Euro. To investigate the volatility impacts that exist between oil price and exchange rates during both sub-sample periods, we merged Vector Autoregressive (VAR) with GARCH and EGARCH models in the form of Bivariate VAR-GARCH and VAR-EGARCH. We further adopted the Toda-Yamamoto causality test to investigate related causality patterns. Empirical findings revealed both bidirectional and unidirectional relationship between oil price volatility and the exchange rates volatility of four out of the six oil-dependent economies considered for the study. These findings were more prevalent in the post-crisis period than the pre-crisis period. We also confirmed both bidirectional and unidirectional causality pattern between oil price volatility and exchange rate volatility of the same four currencies as observed with the VAR results in both sub-sample periods.

Exchange rate fluctuations, oil price shocks and economic growth in a small net-importing economy

Purpose This study aims to analyze the volatility spillover effects of crude oil, gold price, interest rate (yield) and the exchange rate (USD (United States Dollar)/INR (Indian National Rupee)) on inflation volatility in India.Design/methodology/approach This study uses the multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models (Baba, Engle, Kraft and Kroner [BEKK]-GARCH and dynamic conditional correlation [DCC]-GARCH) to examine the volatility spillover effect of macroeconomic indicators and strategic commodities on inflation in India. The monthly data are collected from January 2000 till December 2020 for the crude oil price, gold price, interest rate (5-year Indian bond yield), exchange rate (USD/INR) and inflation (wholesale price index [WPI] and consumer price index [CPI]).Findings In BEKK-GARCH, the results reveal that crude oil price volatility has a long time spillover effect on inflation (WPI). Furthermore, no significant short-term volatility effect exists from crude oil market to inflation (WPI). However, the short-term volatility effect exists from crude oil to inflation while considering CPI as inflation. Gold price volatility has a bidirectional and negative spillover effect on inflation in the case of WPI. However, there is no price volatility spillover effect from gold to inflation in the case of CPI. The price volatility in the exchange rate also has a negative spillover effect on inflation (but only on CPI). Furthermore, volatility of interest rates has no spillover effect on inflation in WPI or CPI. In DCC-GARCH, a short-term volatility impact from all four macroeconomic indicators to inflation is found. Only crude oil and exchange rate have long-term volatility effect on inflation (CPI).Practical implications In an economy, inflation management is an essential task. The findings of the current study can be beneficial in this endeavor. The knowledge of the volatility spillover effect of all the four markets undertaken in the study can be significantly helpful in inflation management, especially for inflation-targeting policy.Originality/value It is observed that no other study has addressed this issue. We do not find any other research which studies the volatility spillover effect of gold, crude oil, interest rate and exchange rate on the inflation volatility. The current study is novel with a significant contribution to the vast knowledge in this context.

This study examined the relationship among oil price, exchange rates and stock market returns before [1990- 2008] and after [2009-2023] global financial crisis in the net oil exporting African countries. Data for the study were sourced from Energy Information online database, International Monetary Fund [IMF] online database and World Bank development indicator online database. Data sourced were estimated by non-linear Autoregressive Distributed Model, ARCH and GARCH, Vector Autoregressive Model and Panel Granger Causality Tests. Results from unit root test showed that variables of interests were integrated of mixed orders 1[0] and 1[1]. The result from NARDL revealed that there is co-integration and non-linear long run connection among oil price, exchange rates and stock market returns in net oil exporting African Countries. The results from panel NARDL further showed that exchange rate appreciate significantly during positive oil price but depreciate mildly during negative oil price. Also, empirical result further revealed that positive oil price did not impact stock market returns significantly while negative oil price has significant negative influence on stock market returns during the study period. The result from panel pairwise granger causality revealed that causality running from oil price to exchange rate and stock market returns but causality did not run from exchange rate and stock market. However, the study found that the effect of negative oil price on exchange rate and stock market returns after global financial crises was more pronounced. That is, negative oil price had more adverse effect on both exchange rate and stock market return during the study period.Based on these findings, the study concludes that both stock market returns and exchange rate are sensitive to the behavior of oil price at international oil market. The study recommends that investors and monetary authority should monitor the behavior of oil price at international oil market when designing their policies.

Purpose: Policy makers, academics and journalists have frequently discussed the link between oil prices and exchange rate in recent years. After the 2014 World’s biggest oil price drop that plunge CEMAC oil exporting countries into an external liquidity strain, due to the pressure raised on Euro to which CFA franc is pegged, this paper revisits the dependence between crude oil price changes and exchange rate.
 Methodology: Crude oil price is the main independent variable, though other independent variables have been considered. The change in crude oil price is captured through differentiation of average yearly crude oil prices. The real effective exchange rate (RER) is the dependent variable, captured with the consumer’s price index (CPI), which describes the strength of a currency relative to a basket of other currencies. The data used in this study were extracted from Word Bank Development Indicators (WBDI, 2020) and World Bank Commodity Price Data. The study covers the period 1990-2018. The main channels of transmission used in this paper are the terms of trade channel, the wealth or portfolio channel and the anticipation or expectation channel. A panel autoregressive distributive lag (ARDL) model was used.
 Findings: The result shows that there is a short run positive and insignificant effect of oil price changes on exchange rate of CEMAC oil producing countries. In the long-run, there is rather a negative and significant impact of oil price changes on exchange rate. More concretely, a unit increase in oil prices depreciates exchange rate of these countries by 0.4340 units and this is significant at 1%. The short run Cross-country analysis shows that the effect is negatively significant for Cameroon and Chad; positive and significant for Democratic Republic of Congo and Equatorial Guinea; but positive and not significant for Gabon. These results are likely linked to structural differences between countries as the dependence on oil revenue and the security situation are concerned.
 Recommendations: Given this negative long run damage of oil prices on exchange rate of CEMAC oil producing countries, it is highly advisable these countries increase direct investments in key economic non-oil sectors in order to reduce dependence. On the other hand, considering the unidirectional causality from exchange rate to oil prices, a policy of exchange rate anchor by BEAC is suitable in order to absorb the shock of oil price changes on exchange rate and eventually inflation in the these economies.

This paper examines the dynamic linkage between crude oil prices and exchange rates from a global perspective. Unlike the conventional cointegration specification used in earlier works, we evaluate long- and short-run relations based on the pooled mean group approach. Taking monthly data of real oil prices and real exchange rates from the period January 1997 to July 2015, we classify 81 countries by their net oil import status (i.e., oil-importing and oil-exporting) and exchange rate arrangement systems (i.e., free-floating and managed floating), presenting results that the long-run relationship between oil prices and exchange rates depends on country-specific circumstances. For countries adopting free-floating systems, oil importers reveal a significantly negative bidirectional correlation, while oil exporters show no correlation between oil prices and exchange rates. As for managed floating systems, only exchange rates have predictive content for oil prices no matter in the cases of oil importers or exporters. Knowledge of these relationships can guide government policy development to prevent sudden and substantial shocks from crude oil price and exchange rate movements.

The deepest downturn has been recently faced by oil industry. This sinking price was first observed in June 2014 and it moved further down. This change affected the investment pattern of many companies and leads to a decline in corporate margins and influence investments in stock markets. Keeping in view this important relationship, here, we propose to study the movement of crude oil prices and volatility spill over affect on Indian Stock market and on Exchange rate. Daily data for the period from June 01, 2014 to August 31, 2016 of stock market, exchange rate and crude oil prices was taken. BSE S&P has been taken to represent Indian stock market. US/INR is used as exchange rate. Beside, doing descriptive statistics, Unit Root, Johansen Cointegration and correlation test, we used Garch (1, 1) model. Preliminary results suggested that apart from different degrees of correlations between exchange rate, stock market and crude oil prices are found to be significant. We found that there are some markets from where there is significant flow of volatility. Affect of historic crude price movement on stock markets is also significant.