Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates

Ciner, Cetin; Gurdgiev, Constantin; Lucey, Brian M.

doi:10.1016/j.irfa.2012.12.001

Cited by 586 publications

(297 citation statements)

References 25 publications

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“…Using the uncertainty measures developed by Brogaard and Detzel (2015), we concentrate on the dollar-based exchange rates for both developed and developing countries/regions namely: Australia, Brazil, Canada, China, Euro area, Hong Kong, India, Japan, Malaysia, Mexico, Russian Federation, South Korea, South Africa, Sweden, Switzerland and UK. The choice of dollar-based exchange rates when analysing uncertainty is clear, given the widely-accepted safe-haven notion associated with the U.S. dollar (see Ciner et al, (2013) for a detailed discussion in this regard). The causality-in-quantiles test that we employ in this paper, combines the frameworks of k-th order causality of Nishiyama et al, (2011) and quantile causality of Jeong et al, (2012), and hence, can be considered to be a more general version of the former.…”

Section: As Reported In the Triennial Survey Of Global Foreign Exchanmentioning

confidence: 99%

Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

et al. 2016

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Recent studies have analysed the ability of measures of uncertainty to predict movements in macroeconomic and financial variables. The objective of this paper is to employ the recently proposed nonparametric causality-in-quantiles test to analyse the predictability of returns and volatility of sixteen U.S. dollar-based exchange rates (for both developed and developing countries) over the monthly period of 1999:01-2012:03, based on information provided by a news-based measure of relative uncertainty, i.e., the differential between domestic and U.S. uncertainties. The causality-in-quantile approach allows us to test for not only causality-in-mean (1 st moment), but also causality that may exist in the tails of the joint distribution of the variables. In addition, we are also able to investigate causality-in-variance (volatility spillovers) when causality in the conditional-mean may not exist, yet higher order interdependencies might emerge. We motivate our analysis by employing tests for nonlinearity. These tests detect nonlinearity, as well as the existence of structural breaks in the exchange rate returns, and in its relationship with the EPU differential, implying that the Granger causality tests based on a linear framework is likely to suffer from misspecification. The results of our nonparametric causalityin-quantiles test indicate that for seven exchange rates EPU differentials have a causal impact on the variance of exchange rate returns but not on the returns themselves at all parts of the conditional distribution. We also find that EPU differentials have predictive ability for both exchange rate returns as well as the return variance over the entire conditional distribution for four exchange rates.

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Section: As Reported In the Triennial Survey Of Global Foreign Exchanmentioning

confidence: 99%

Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

et al. 2016

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“…However, no formal portfolio allocation exercise is performed by [52], which is what we aim to address in this paper based on a MS-DCC-GARCH model, i.e., a variant of the original DCC-GARCH model of [53], with Markov-switching (as detailed in [54]). Note that these types of models have also been widely used in analyzing hedges and safe-haven properties of various assets (see [55] for a detailed discussion in this regard) and also comparing Islamic and conventional equities (see for example, [56] for further details), with the latter being somewhat related to our analysis, given the importance of Sharia rules imposed on screening the equities included in Islamic indices.…”

Section: Literature Reviewmentioning

confidence: 99%

Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations

2017

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This paper explores the potential diversification benefits of socially responsible investments for conventional stock portfolios by examining the risk spillovers and dynamic correlations between conventional and sustainability stock indexes from a number of regions. We observe significant unidirectional volatility transmissions from conventional to sustainable equities, suggesting that the criteria applied for socially responsible investments do not necessarily shield these securities from common market shocks. While significant dynamic correlations are observed between sustainable and conventional stocks, particularly in Europe, the analysis of both in-and out-of-sample dynamic portfolios suggests that supplementing conventional stock portfolios with sustainable counterparts improves the risk/return profile of stock portfolios in all regions. The findings overall suggest that sustainable investments can indeed provide diversification gains for conventional stock portfolios globally.

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“…Financial media often refers to precious metals, such as gold, silver, platinum and palladium, as safe havens in periods of financial crises (FT, 2014). The resilience of precious metals (with a particular emphasis on gold, silver, platinum and palladium) markets to financial crises has been recently accentuated also by academic scholars, including Lucey and Li (2015), Batten et al (2015), Baur and Lucey (2010), Baur and McDermott (2010), Ciner et al (2013) and Agyei-Ampomah et al (2014). Hillier et al (2006) and Belousova and Dorfleitner (2012) show that the inclusion of precious metals in an equity portfolio can reduce systematic risk of investment and accrue diversification benefits, particularly in periods of elevated equity market volatility.…”

Section: Introductionmentioning

confidence: 99%

“…Conceptually, our research resembles Ciner et al (2013) and Lucey and Li (2015), who build upon the dynamic conditional correlation (DCC) methodology of Engle (2002), and Aboura and Chevallier (2014), who draw on a more advanced factor dynamic conditional correlation (FDCC) methodology of Zhang and Chan (2009) to study time-varying conditional correlations between various asset classes. A distinctive feature of our research is that, building upon a VAR model, we estimate and study dynamic rather than only static transmission.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic spillovers between commodity and currency markets

Antonakakis

Kizys

2015

International Review of Financial Analysis

212

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In this study, we examine the dynamic link between returns and volatility of commodities and currency markets. Based on weekly data over the period from January 6, 1987 to July 22, 2014, we find the following empirical regularities. First, our results suggest that the information contents of gold, silver, platinum, and the CHF/USD and GBP/USD exchange rates can help improve forecast accuracy of returns and volatilities of palladium, crude oil and the EUR/CHF and GBP/USD exchange rates. Second, gold (CHF/USD) is the dominant commodity (currency) transmitter of return and volatility spillovers to the remaining assets in our model. Third, the analysis of dynamic spillovers shows time-and event-specific patterns. For instance, the dynamic spillover effects originating in gold and silver (platinum) returns and volatility intensified (degraded) in the period marked by the global financial crisis. After the global financial crisis, the net transmitting role of gold and silver (platinum) returns shocks weakened (strengthened), while the net transmitting role of gold, silver and platinum volatility shocks remained relatively high. Overall, our findings reveal that, while the static analysis clearly classifies the aforementioned variables into net transmitters and net receivers, the dynamic analysis denotes episodes wherein the role of transmitters and receivers of return (volatility) spillovers can be interrupted or even reversed. Hence, even if certain commonalities prevail in each identified category of commodities, such commonalities are time-and event-dependent.

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Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates

Cited by 586 publications

References 25 publications

Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test

Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations

Dynamic spillovers between commodity and currency markets

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