Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

Autoregressive conditional durations: An application to the Surinamese dollar versus the US dollar exchange rate

The parallel market nominal exchange rate of the United States dollar vis-à-vis the Surinamese dollar (USD/SRD) exhibited periods of severe volatility which were often followed by episodes of stability, usually at a cost of sharp depreciations. This study seeks to model this exchange rate using autoregressive conditional duration models. These models are suitable for modelling events occurring with irregular intervals. Exchange rates in developing countries have distinct features compared to exchange rates in countries with well-established and accessible financial markets. A key feature is that for these developing countries, exchange rates only occasionally experience jumps. Our findings suggest that past exchange rate changes appear to be a significant driver of future exchange rate jumps. Furthermore, our results show that money, international reserves, and commodity prices can explain jumps in the market USD/SRD exchange rate.     

Energy prices and exchange rates of the U.S. dollar: Further evidence from linear and nonlinear causality analysis

The causality relationships between energy prices and exchange rates have been investigated in many existing studies. Previous investigations ignore the possible nonlinear behaviors which may be caused by asymmetry, persistence or structural breaks. To fill this gap, we apply both linear and nonlinear causality tests to examine the causal relationships between energy prices and exchange rates of the U.S. dollar. Our results show that in the period before recent financial crisis, unidirectional linear causality running from petroleum prices to exchange rates and unidirectional nonlinear causality running from exchange rates to natural gas prices are revealed. In the period after the financial crisis, the bidirectional nonlinear causality relationships between petroleum prices and exchange rates can be found and there are no causality between exchange rates and natural gas prices. Moreover, we examine the source of nonlinear behaviors of causality relationships. Our evidence indicates that both volatility spillover and regime shift contribute to nonlinear causality and the explanation power of the former one is much stronger.     

Interpreting the movement of oil prices: Driven by fundamentals or bubbles?

Based on the historical data of crude oil, diesel and gasoline markets during November 2001–December 2015, this paper employs the state-space model and log-periodic power law (LPPL) model to explore the dynamic bubbles of oil prices and predict their crash time. The results indicate that, first, oil price bubbles only exist during November 2001–July 2008, and crude oil and diesel prices are significantly driven by bubbles, whereas gasoline prices are mainly driven by fundamentals. Second, the state-space model captures the time-varying bubbles of crude oil and diesel prices. Finally, the LPPL model well predicts the crash time of bubbles.     

The relationship between stock prices and exchange rates in South Africa and Nigeria: structural breaks analysis

The relationship between stock prices and exchange rates has continued to generate interest from both the academia and financial industry players for many years. This study conducts an empirical investigation into the relationship between stock prices and exchange rates for the two largest economies in Sub-Saharan Africa – South Africa and Nigeria. Our methodology accounts for structural breaks in the data and the long-run relationship between stock and foreign exchange markets. The results of multivariate causality tests with structural breaks showed that causality runs from exchange rates to domestic stock prices in Nigeria (flow channel) while in South Africa, no causality exists between domestic stock prices and exchange rates. The results also reveal that there is causality from the London stock market to both countries’ stock markets, thus showing that international stock markets are driving both the Nigerian and South African stock markets.     

The Monetary Approach to the Exchange Rate Determination for a “Petrocurrency”: The Case of Norwegian Krone

This paper, by following vector error correction modeling, empirically investigates some of the popular monetary models of the NOK/USD rate. The empirical results suggest that there is some scope for the monetary approach to explain the development of the NOK/USD during the period from 1997 to 2008. The coefficients in the co-integration equation of both money and output differentials are statistically significant and consistent with any of the forms of the monetary models. Moreover, empirical evidence for the proportionality between the exchange rate and relative money is provided. Our findings are robust across different measures of inflation expectations. Although there is no clear evidence regarding the exact version of the monetary model, the estimated unrestricted error correction models can fit the actual NOK/USD exchange rate. Finally, the short-term dynamics of the exchange rate are significantly affected by changes in crude oil prices.     

On the influence of US monetary policy on crude oil price volatility

Forecasting oil prices is not straightforward, such that it is convenient to build a confidence interval around the forecasted prices. To this end, the principal ingredient for obtaining a reliable crude oil confidence interval is its volatility. Moreover, accurate crude oil volatility estimation has fundamental implications in terms of risk management, asset pricing and portfolio handling. Generally, current studies consider volatility models based on lagged crude oil price realizations and, at most, one additional macroeconomic variable as crude oil determinant. This paper aims to fill this gap, jointly considering not only traditional crude oil driving forces, such as the aggregate demand and oil supply, but also the monetary policy rate. Thus, this work aims to contribute to the debate concerning the potential impact of (lagged) US monetary policy as well as the other crude oil future price (COFP) determinants on daily COFP volatility. By means of the recently proposed generalized autoregressive conditional heteroskedasticity mixed data sampling model, different proxies of the US monetary policy alongside US industrial production (proxy of the US aggregate demand) and oil supply are included in the COFP volatility equation. Strong evidence that an expansionary (restrictive) variation in monetary policy anticipates a positive (negative) variation in COFP volatility is found. We also find that a negative (positive) variation of industrial production increases (decreases) COFP volatility. This means that volatility behaves counter-cyclically, according to the literature. Furthermore, the out-of-sample forecasting procedure shows that including these additional macroeconomic variables generally improves the forecasting performance.     

Petroleum spreads and the term structure of futures prices

We employ the term structure of gasoline and heating oil prices, proxied by convenience yields, to explain the variation in the spread between the prices of gasoline and crude oil and the prices of heating oil and crude oil. We demonstrate that the marginal convenience yields in the gasoline and heating oil markets explained much of the variation in the spreads between 1986 and 1999. The evidence indicates the importance of a disaggregated treatment of the term structure of prices: the convenience yield is found to explain a substantially higher amount of the variation in the spread when it is decomposed by maturity, even after controls for seasonality and inventory levels are implemented. These findings support the notion that the futures term structure contains information beyond what can be garnered via obvious or easily available proxies of current supply and demand. The findings are also supported in an alternate specification that tests for the origins of information spillover (leadership) between the commodities: it is demonstrated that decomposed convenience yields explain a substantial portion of the volatility spillover from the gasoline and heating oil markets to the crude market.     

Exchange rate uncertainty and import prices in the euro area

This paper analyzes the effects of exchange rate uncertainty on the pricing behavior of import firms in the euro area. Uncertainty is measured via the volatility of the structural shocks to the exchange rate in a nonlinear vector‐autoregressive model framework and is an important determinant of import prices. An increase in exchange rate uncertainty is associated with a fall in prices on average, which suggests that the exchange rate risk is borne by the importers. Controlling for the origin of imports (within or outside the euro area) is important for assessing the impact of exchange rate movements on prices.     

国际石油价格与通货膨胀的溢出效应及动态相关性

国际石油价格大幅波动不可避免地给全球经济带来了一定程度的冲击和影响。文章采用向量自回归、多元GARCH-BEKK和DCC-GARCH模型对中美两国通货膨胀与国际石油价格之间的均值溢出效应、波动溢出效应及动态相关关系进行了实证检验。检验结果表明,国际石油价格与中国通货膨胀不存在任何方向的均值和波动溢出效应,美国通货膨胀与国际油价则存在双向显著的均值和波动溢出效应;中国通货膨胀与国际油价的动态相关关系显著弱于美国,不易受到国际油价的冲击和影响。从整体上看,当前中国通货膨胀与国际石油价格的关联性并不显著,但随着我国石油消费对进口依赖程度的不断提高,石油安全问题在可预见的未来将成为中国需要应对的一个现实挑战。因此,相关部门应及早采取有效措施,应对未来石油冲击对宏观经济的影响。     

Identifying the dynamic relationship between tanker freight rates and oil prices: In the perspective of multiscale relevance

The tanker shipping market has been treated as the key extension of the world oil market and inevitably, its uncertainty is correlated to volatility of the oil market, besides supply and demand factors. Therefore, for improving operational management and budget planning decisions, it is essential to understand the inherent relevance between freight rates and crude oil prices. Taking time-dependent features into account, this paper focuses on the multiscale correlation between freight rates and oil prices. Given the complexity and mutability of tanker freight rate process, this paper first extracts the intrinsic mode functions from the original data using the Ensemble Empirical Mode Decomposition model and then reconstructs two separate composite functions: high-frequency and low-frequency components, plus the residual as the long-term trend. Secondly, correlations of the multiscale components of freight rates and oil prices are examined based on relevance structure. Empirical results show that tanker freight rates and oil prices exhibit different multiscale properties with true economic meaning and are significantly correlated in the medium and the long term when taking the relevance structure into account. These findings offer some useful information to better understand the correlations between these two markets and more importantly, propose a novel perspective to investigate the dynamic relationship between two markets.     

Macroeconomic dynamics in Macedonia and Slovakia: Structural estimation and comparison

This paper estimates a structural macroeconomic model using data for Macedonia and Slovakia to characterize possible challenges Macedonia can face concerning macroeconomic stabilization during its transition process. A comparison of the estimated model parameters suggests that, in Slovakia, the output gap is less sensitive to real interest rate movements and prices experience greater inertia. The estimated monetary policy reaction functions show Macedonia and Slovakia as inflation targeters, with Macedonia as the more conservative one, despite its officially applied exchange rate targeting regime. The differences in the estimated parameters imply differing transmission mechanisms for Macedonia and Slovakia. Consequently, the variance of domestic variables in Slovakia is most influenced by monetary policy shocks, while there is no single dominating shock explaining the volatility of Macedonia's macroeconomic variables. The exchange rate shock, the monetary policy shock and the demand shock are jointly important in determining the volatility of Macedonia's variables. The model simulations indicate that Macedonia experiences lower output gap and inflation volatility than Slovakia. This comes, nevertheless, at the cost of higher interest rate and real exchange rate volatility in Macedonia, which could be an indication of more volatile financial markets with possible negative implications for financial stability.     

Can asymmetric conditional volatility imply asymmetric tail dependence?

In this article, we investigate two types of asymmetries, that is, the asymmetry of conditional volatility and the asymmetry of tail dependence in the crude oil markets. We employ the two different sample datasets in which each dataset covers the time period of stable and unstable oil prices, individually. A variety of different copulas and three asymmetric GARCH regression models are used in order to capture the two types of asymmetries. In particular, we extend the TBL-GARCH model proposed by Choi et al. (2012) to the asymmetric GARCH regression type model. The findings from the two different approaches are congruent, in that there is no asymmetry of tail dependence and no asymmetric conditional volatility in crude oil returns over the two different sample periods. Our study reconfirms the findings of Aboura and Wagner (2016) by showing that asymmetric conditional volatility relates to asymmetric tail dependence.     

Exchange rate volatility and the demand for money in the U.S.

This paper examines the effect of changes in the level and volatility of exchange rates on the demand for money. It hypothesizes that exchange rate volatility exerts a negative influence on money demand separate from the effect of the level of exchange rates. Using U.S. data covering the period from 1974.1 to 1990.4, it is found that, regardless of whether the adjustment process is modeled as an error-correction or a partial-adjustment model, exchange rate volatility is negatively related to the demand for real M2 balances. This relationship is found to be more pronounced when exchange rates are expressed in real terms. The results imply that money demand responds to both the volatility of domestic prices relative to foreign prices and to the volatility of nominal exchange rates. Little evidence is found in support of the hypothesis that the level of exchange rates exerts a significant influence on money demand.     

The comovement between exchange rates and stock prices in the Asian emerging markets

This study investigates the comovement between exchange rates and stock prices in the Asian emerging markets. The sample covers major institutional changes, such as market liberalization and financial crises, so as to examine how the short-term and long-term relations change after such events. The autoregressive distributed lag (ARDL) model proposed by Pesaran et al. (2001) is adopted, which allows us to deal with structural breaks easily, and to handle data that have integrals of different orders. Interest rates and foreign reserves are also included in the analysis to reduce potential omitted variable bias. My empirical results suggest that the comovement between exchange rates and stock prices becomes stronger during crisis periods, consistent with contagion or spillover between asset prices, when compared with tranquil periods. Furthermore, most of the spillovers during crisis periods can be attributed to the channel running from stock price shocks to the exchange rate, suggesting that governments should stimulate economic growth and stock markets to attract capital inflow, thereby preventing a currency crisis. However, the industry causality analysis shows the comovement is not stronger for export-oriented industries for all periods, such as industrials and technology industries, thus implying that comovement between exchange rates and stock prices in the Asian emerging markets is generally driven by capital account balance rather than that of trade.     

Real exchange rate volatility,financial crises and exchange rate regimes

This article examines real exchange rate (RER) volatility in 80 countries around the world, during the period 1970 to 2011. Two main questions are raised: are structural breaks in RER volatility related to changes in exchange rate regimes or financial crises? And do these two events affect the permanent and transitory components of RER volatility? To answer these, we employ two complementary procedures that consist in detecting structural breaks in the RER series and decomposing volatility into its permanent and transitory components. Our results suggest that structural breaks in RER volatility coincidence with financial crises and certain changes in nominal exchange rate regimes. Moreover, our findings confirm that RER volatility does increase with the global financial crises and detect that the more flexible the exchange rate regime, the higher the volatility of the RER using a de facto exchange rate classification.     

Fourier ADL cointegration test to approximate smooth breaks with new evidence from Crude Oil Market

Economic data is typically subject to a number of different forms of structural breaks. Ignoring structural breaks in a model can lead to misspecification issues and false conclusions. This paper proposes a new Autoregressive Distributive Lag (ADL) cointegration test in the presence of nonlinear breaks approximated by a Fourier function. The test offers a simple way to capture smooth structural change in time series data. Exact break dates are not required, and the suggested methodology can accommodate unknown number and form of gradual structural change. The testing procedure circumvents the potential power loss which can result from adding more dummy variables in the testing equation. Simulation results show that our procedure has good size and power properties. We demonstrate our test on the empirical example of real oil prices, oil production, and real economic activity, which are subject to structural breaks. The new test suggests that variables are cointegrated, while a conventional ADL test ignores structural breaks and concludes the opposite. This result casts some doubt on conventional oil price models.     

Investigating Intraday Interdependence Between Gold,Silver and Three Major Currencies: the Euro,British Pound and Japanese Yen

In this study, the interrelationship between major exchange rate returns (namely EUR/USD, GBP/USD, JPY/USD) and precious metal returns (gold and silver) is examined using a vector autoregressive model in a multivariate asymmetric GARCH framework on the intraday frequency. Our findings indicate a unidirectional volatility transmission from the majority of our currencies (EUR/USD, GBP/USD) to precious metals. The sluggish response of silver volatility to currency volatility shocks permits implementation of intraday profitable strategies, providing implications against market efficiency when analyzing intraday data. In the case of the British pound and Japanese yen, a volatility shock affects silver volatility more than gold volatility. Crisis events such as the Greek default and US credit rating downgrade reduce significantly the correlation of EUR/USD and gold/silver. The covariance between EUR/USD and silver increases after a volatility shock in EUR/USD. The same happens with JPY/USD and silver. These findings are important for portfolio managers and monetary authorities.     

A common factor of stochastic volatilities between oil and commodity prices

This article analyses the multivariate stochastic volatilities (SVs) with a common factor influencing volatilities in the prices of crude oil and agricultural commodities, used for both biofuel and nonbiofuel purposes. Modelling the volatility is crucial because the volatility is an important variable for asset allocation, risk management and derivative pricing. We develop a SV model comprising a latent common volatility factor with two asymptotic regimes with a smooth transition between them. In contrast to conventional volatility models, SVs are generated by the logistic transformation of latent factors, which comprise two components: the common volatility factor and an idiosyncratic component. We present a SV model with a common factor for oil, corn and wheat from 8 August 2005 to 10 October 2014, using a Markov chain Monte Carlo method to estimate the SVs and extract the common volatility factor. We find that the volatilities of oil and grain markets are persistent. According to the estimated common volatility factor, high volatility periods match the 2007–2009 recession and the 2007–2008 financial crisis quite well. Finally, the extracted common volatility factor exhibits a distinct pattern.     

Volatility spillovers and determinants of contagion: Exchange rate and equity markets during crises

We study the hourly volatility spillover between the equity markets of New York (DJI), London (FTSE 100) and Tokyo (N225) and their exchange rates (USD, EUR, GBP and JPY) for the period of 2001 through 2013 covering the non-crises period, the global financial crisis and the euro debt crisis. First, we find a general increase in spillover between the equity and exchange rate markets during the crisis periods. Second, pure contagion (attributable to irrational investors’ behavior) and fundamental contagion (measured by macroeconomic fundamentals) explains the increased spillover between the FTSE 100, N225 to the DJI during the global financial crisis and from the exchange rate markets to the DJI during the euro debt crisis.