1. Introduction
Oil, which is used in a wide range from electricity production to transportation, from industrial production to agriculture, is a strategic and vital commodity for many economies. Nowadays, oil price movements behaving out of expectations have been affecting the whole economy including the real sector and financial markets. As an example, the financial market and oil price movements in the first quarter of 2020 are among the unusual behavior due to the massive downward pressure of the COVID-19 outbreak on the price of crude oil. Amid the COVID-19 pandemic in late 2019 and early 2020, oil consumption has reduced in China and the rest of the world because of decreasing industrial production and transatlantic transportation. On the other hand, the oil conflict between Saudi Arabia and Russia in March 2020 also led to increased supply while decreasing prices. With the impact of unprecedentedly falling demand and rising supply, the WTI entered the negative zone for the first time in its history. In the oil market, both supply and demand shocks have an effect on the prices of macroeconomic and financial variables. Oil price variations have a major impact on the dynamics of global energy markets, as well as global financial markets, owing to the financialization of commodities.
As the above-mentioned example suggests, oil price shocks might be among the most common sources of volatility in the stock markets around the world. Strong oscillations in the price of oil have impacts on financial asset returns in addition to their impacts on expectations and the economy. The growing convergence of stock and oil markets has reduced the benefits of diversity, forcing investors to seek out an alternative asset that lowers portfolio risk [
1]. Based on this quest for alternative assets, gold is extensively presented as an asset to obtain improvement in the diversification of a portfolio [
2] in addition to providing a hedge [
3] against excessive movement of stock indices and returns which particularly occurs in times of high volatility [
4]. Further, gold is seen as a safe-haven asset class for many nations, predominantly in the MENA area, in addition to being highly demanded during political turmoil and economic crises throughout the world. Therefore, gold demand is strong in emerging countries in addition to strong financial uncertainties. As shown by [
5], there is a clear relationship between the drop in oil prices and the demand for gold in the MENA countries (see for MENA countries [
5]. According to Connolly et al. [
6] and Chiang et al. [
7], stock and bond market volatility rises when stock market uncertainty rises. Hence, a decline in global stock markets can increase current gold demand in these countries. These relations can exhibit different structures in the longer periods compared to the very short term.
Oil prices can also have an impact on stock returns, either indirectly through the discount rate or directly through predicted cash flows. Oil price shocks affect stock returns, according to several empirical studies that use flexible graphical models that allow for extensions to higher dimensions. The increase in oil prices, on the other hand, is anticipated to improve the total trade imbalances in the petrol-importing economies. Expectations of exchange rate depreciation and increased inflation will rise as the trade gap rises.
According to the literature, oil prices have a variety of effects on stock markets and the direction, and the size of these effects depends on the structure of the economy in addition to the type of oil shock [
8]. Basher et al. [
9] further emphasize that the stock price formulation necessitates the anticipated present value of discounted future cash flows which is drastically lowered after sharp oil price shocks resulting in lower stock prices. Moreover, policymakers respond to rising oil prices by increasing the interest rates to control inflation expectations which affect the discount rate in the stock pricing formula leading to lower stock market prices [
9]. As discussed by Bayer and Filion [
10], Hammoudeh et al. [
11], the hikes in oil prices raise operating costs leading to negative effects since increases in oil prices lead to lower earnings and for non-oil-related industries, the substitution of oil in the short and medium run is not possible for businesses. Huang et al. [
12] show that the impact of crude oil movements on stock markets can be completely explained by their effect on current and future real cash flows. According to Faff and Brailsford [
13], there is a markup effect of oil prices that causes businesses to raise the prices of their goods which has a negative influence on stock markets as long as the increasing production costs due to oil price hikes are passed on to customers. Le and Luong [
14] emphasize that the oil price hike’s effect depends on the structure of the economy, for importers of oil, losses occur for businesses resulting in a decline in realized stock returns, whilst countries that export oil might experience the opposite consequences. Rahman [
15] evaluates the asymmetric responses of stock markets to oil price shocks and according to the findings, responses to positive and negative oil price shocks differentiate, and this asymmetric response is driven by the oil price volatility which has negative effects on stock returns. Wen et al. [
16] confirm that the type of shock matters for stock markets’ response and while oil demand shocks lead to a positive stock-risk association, oil risk shocks affect the stock-risk relation negatively. Maghyereh and Abdoh’s [
17] findings emphasize the extreme level of dependence among these variables in GCC countries.
VIX is a barometer for worldwide investors and its level influences decision-making [
18]. The prices of gold, stock, oil, exchange rates, and VIX are all under the influence of macro and microeconomic factors, as well as non-economic factors such as geopolitical tensions, wars, as well as speculative activities. More volatility and uncertainty in oil and gold prices, stock returns, VIX, and exchange rates result from increased speculative activity. Moreover, uncertainty and volatility in gold and oil prices may affect the decisions of manufacturers for industrial production and investors for portfolio allocation. Gold price, stocks, exchange rate, VIX, and oil may exhibit evidence of dependence, persistency, and nonlinear behavior. As put forth by Hamilton [
19], nonlinear and/or asymmetric behavior occurs when, for example, an economic crisis is on stage or high volatility regime is less persistent than the boom stage, or when the periods of economic expansion take longer than the crisis stage. Under such conditions, investigation of regime dependency has strong implications for the effectiveness of policy decisions.
The movements of oil, gold, VIX, exchange rate and stock return cannot be analyzed by traditional methods such as VAR, GARCH, and cointegration, since they are sensitive to many economic and non-economic factors such as COVID-19, geopolitical events, wars, internal conflicts, etc. This study attempts to contribute to the literature in the areas of theory, methodology, and application. Following the discussion above, it is critical to assess whether there exists contagion and causality relations between oil prices, stock markets, investor sentiment, exchange rates, and gold prices, however, the traditional methods become biased under the sensitivities stated above. Further, the series analyzed are subject to heteroskedastic behavior in addition to nonlinearity. Therefore, it is important to construct models to capture nonlinear tail dependence contagion relations in addition to regime-dependent causal links. For this purpose, the paper contributes to the utilization of Markov switching generalized autoregressive conditional heteroskedasticity copula and causality (MS-GARCH-copula causality) methodologies. The models to be utilized allow the assessment of nonlinear dependence and persistency structures, in addition to regime-dependent contagion and causality behavior among oil and gold prices, VIX investor fear index, exchange rates, and stock markets in an emerging market, Turkey.
The use of the copula method is not new. However, the extension of the copula analysis to nonlinear Markov switching causality is a hybrid approach proposed. In the paper, the MS-GARCH copula method will be advanced to the MS-GARCH copula causality to contribute to various aspects. The existing literature on contagion in terms of both tail dependence coefficients and copula parameters were discussed in [
20,
21,
22,
23]. Bildirici [
24] by TAR-TR-GARCH and TAR-TR-TGARCH copula methods found evidence of nonlinear tail dependence and Bildirici’s [
25] results indicated chaotic behavior in oil price, VIX, and stock returns in addition to contagion [
26,
27] did not conduct but could be thought of favoring the necessity of simultaneous analysis of the direction of causality. On the other hand, a few numbers of papers used copula-causality tests such as Lee and Yang [
28] and Hu and Liang [
29]. However, these papers did not analyze the different structures and the direction of causality among the regimes. Since each regime has a different characteristic, every economic regime needs regime-specific policies instead of common ones. If it is not taken into regimes, the direction of causality and policy recommendations determined by the causality results will be incorrect. In the application aspect, the MS-GARCH copula causality method provides tests for the presence of causality, asymmetric behavior, persistence, and contagion impact simultaneously for managers and policymakers.
The study has five parts. The second part contains the literature review. The data and methodology are given in the third section. The analysis and results are reported in
Section 4. Discussion, implications, and policy suggestions are in the fifth section. The last section concludes.
5. Discussion, Implications, and Policy Suggestions
The traditional linear approaches that do not take regime-dependency and neglected nonlinearity has important effects on the linear estimators. The oil, VIX, EX and BIST series are under the influence of many factors that lead to deviations from linearity and these factors include economic crises, shocks, disputes, political events and not to mention the COVID-19. Therefore, the utilization of MS-GARCH-copula and the nonlinear Granger causality method derived from the former is a necessity. The utilization of these methods led to important regime dependent contagion and causality relations.
Given that Turkey is a net oil importer, the findings obtained in the study with respect to oil and stock market relations coincide with the findings of Bouri and Demirer [
46], which suggest volatility spillover from oil to stock markets. As pointed out by Ji et al. [
47], the oil–stock relation is time-varying, and our findings confirm this nature of the relationship due to the non-rejection of regime-switching tests. Further, the regime-dependent copula results in a more than three times larger effect in terms of the contagion effect in the first regime compared to the second. The results obtained confirm Shaikh and Padhi [
69] in terms of VIX-stock market relations associating investor fear with stock market drops and volatility rises. In addition, the findings obtained in our study further extend this finding into regime-dependency: copula parameter estimates are high and close in both regimes suggesting a significant degree of contagion in both regimes in addition, the direction of causality in both regimes is determined as being unidirectional from VIX to BIST stock index. In terms of oil–stock relations, our results also confirm that oil price hikes lead to declines in stock markets which are in line with the findings of Chiou and Lee [
38], Miller and Ratti [
39], Nandha and Faff [
40] and Park and Ratti [
41]. The effects of noise on Granger causality modeling is evaluated in [
84]. Our findings show the necessity of modeling regime-dependent heteroskedasticity within this respect. The findings also confirm Thai Hung [
86].
As shown by Bildirici and Ersin [
87,
88], oil price volatility necessitates importance of modeling nonlinearity and regime-dependency. The results revealed that the normality assumption is also not appropriate for modeling VIX, gold prices, and the exchange rates. Hence, neither financial nor economic decisions would be inefficiently achieved by the use of models assuming normality. MS-GARCH copula causality method does not assume normality and allows the application of optimal policies for the government’s stock market investors, in addition to strategists focusing on the management of risk and optimal portfolio selection.
Our results determined that the returns of oil and gold can have an impact on price trends and expectations. The price movements of gold and oil are important for inflation targeting policy since their persistence can affect the ones of inflation and can lead to a rise in inflationary pressure and asset investments. In the presence that the magnitude and source of and return are a significant dimension of risk management in financial markets, our results across the international oil and gold markets, VIX, and Turkish stock market and exchange rate emphasize the importance of hedging instruments to reduce financial market risks.
Following the findings of the study, several recommendations are obtained. For the researchers and for practice, the regime-dependency and time-varying correlations between oil, stock, gold, VIX, and exchange rates should be kept in consideration, and generalizations to linear approaches should be avoided. For society, individuals, as well as investors, should consider that given the fact that oil, gold, and VIX are externally determined for an emerging economy, the fluctuations in these variables should be closely followed while considering the regime that the stock market is at the given period of time. Depending on the low or high volatility regime of the financial market, it should be always kept in mind that the relations between exchange rates, stock market, gold, oil, and VIX become drastically different. For regulators, the strong fluctuations in oil and gold in addition to VIX should be closely followed since they lead to various alterations in the analyzed variables. Therefore, policies should consider eliminating (if possible) or at least lowering the negative effects due to the level of contagion to the stock markets in the economies. Further, from a macroeconomic perspective, policies focusing on price stability in economies should also be coupled with policies focusing on the limitation of pass-through mechanisms from external factors to domestic financial markets.
6. Conclusions
This paper suggested and investigated the regime-dependent causality and contagion relation between oil prices, gold prices, VIX investor sentiment, BIST100 stocks, and TL dollar exchange rates for a period of 4 January 2000–13 March 2020 by the MS-GARCH copula causality method. The MS-GARCH copula causality models for return series allow the determination of the presence of comovement, persistency, dependence, contagion, and causality in different regimes such as low and high volatility regimes and low and high return regimes.
If the results are evaluated in terms of the consequences for Turkey’s financial markets, as expected, the BIST does not Granger cause the returns of oil and TL dollar exchange rates to have no effects on the oil prices determined in the world markets. However, the reverse is not true, oil prices have strong causal effects in both regimes on BIST and exchange rates in Turkey. Further, BIST does not Granger cause the gold prices and VIX. On the other hand, there is bidirectional causality between EX and BIST in both regimes, and there is significant evidence of contagion and tail dependence.
The relations between oil and gold prices and the exchange rates and the BIST100 stock markets cannot be effectively analyzed by various traditional methods assuming linearity and ignoring the regime dependency. In addition, linear models, by overly simplifying the relations by assuming an overall linear relation, are under the influence of many economic and non-economic factors such as COVID-19, geopolitical events, and disputes. Moreover, comovement, dependence, and the direction of causality cannot be determined by traditional methods in cases of inefficiencies of the parameter estimators under such factors.
The results have important implications. First, the normality assumption is not suitable for modeling the analyzed variables, and policy and economic decisions in addition to investment decisions may not be efficient if traditional approaches are utilized. The findings favor the use of the MS-GARCH copula causality method which takes nonlinearity into consideration in addition to producing improved policies for stock market investors. Second, the finding favored that oil and gold have significant impacts on the price trends and expectations, which is also an important finding in terms of the anti-inflationary policies. Further, inflationary pressures play important roles in asset investment decisions. Third, in terms of risk management in financial markets, our results regarding the relations between oil and gold markets, VIX, and Turkish stock market and exchange rates emphasize the importance of effective use of hedging instruments to reduce financial market risks in the case of a net oil importer economy.