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Volatility Linkages Among Gold Futures in Emerging Markets
Abstract
We aim to detect the cross-border volatility linkages among gold futures in emerging markets, which still remain an untapped area. China, India, Japan, Taiwan, Turkey, and U.S. futures markets are included in the sample. The volatility linkage analyses confirm the existence of volatility transmission among the majority of the sample countries’ gold futures. This article carries vital inferences and implications for policy makers and investors. The policy making is particularly important for China, which is a relatively isolated market. From investors’ perspective, the results indicate that the risk diversification and cross-market hedging opportunities in the emerging gold futures markets are quite limited.
... VaR is the maximum loss of a given asset portfolio over a specific time horizon with a pre-specified confidence level. Although volatility is a traditional measure of risk and its spillover effects are widely investigated in the literature (e.g., Cheung & Ng, 1996;Hong, 2001;Batten & Lucey, 2010;Baur, 2012;Baklaci et al., 2016), VaR is chosen rather than volatility because it overcomes two drawbacks when using volatility, i.e., (i) the risk of loss measured by volatility is usually underestimated and symmetrical, and (ii) volatility cannot model extreme risk. When the actual loss of a given asset portfolio exceeds the VaR at the given confidence level (e.g., 95%), we say the risk happens at the fixed confidence level. ...
... The authors conclude that (i) the Shanghai gold market is an isolated market; (ii) the New York and London gold markets are the strongest integrated pair of gold markets; and (iii) the Tokyo gold market is clearly influenced by the New York and London gold markets and has no significant and consistent effect on other markets. Baklaci et al. (2016) detect the cross-market volatility linkages among the New York, Tokyo, Shanghai, India, Turkey, and Taiwan gold markets from 2 September 2008 to 20 December 2012. Using the VECH-MGARCH model they find that (i) remarkable volatility spillover effects exist among Shanghai, Indian, and Taiwan gold markets; (ii) there is a long-run volatility linkage between the New York gold market and all the other markets except Shanghai; and (iii) the Shanghai gold market is relatively isolated. ...
... The first group of methods uses linear regression, including VAR, VAR-GARCH, VECM, and VECM-GARCH, to examine the Granger causality in mean or volatility and is widely used to study spillover effects in gold markets (see, e.g., Kumar & Pandey, 2011;Chang et al., 2013;Fuangkasem et al., 2014;Baklaci et al., 2016). However this linear regression approach (i) considers only the influence of a limited lag and the linear correlation and fails to detect the complex causality between highly heterogeneous financial time series, and (ii) its accuracy can be strongly affected by the "stylized facts" of financial time series, including autocorrelation, non-stationarity, multicollinearity, and heteroscedasticity. ...
Using the approach of Granger causality in risk, we investigate extreme risk spillover effects among four major world gold markets (London, New York, Tokyo and Shanghai) before and after the recent global financial crisis. We find (i) that there are strong extreme risk spillover effects between London and New York, and London and Shanghai, (ii) that most of the extreme risk spillovers to Tokyo and Shanghai are from New York rather than from London, but London leads New York in risk spillovers, (iii) that extreme risk spillover effects from Tokyo and Shanghai to New York are limited, but those to London play an important role, and (iv) that extreme risk spillover effects between Tokyo and Shanghai are weak or negligible. We also find that extreme risk is more quickly transmitted in the post-crisis era than in the pre-crisis era, an effect that is related to the safe-haven or risk-hedging property or the speculative value of gold.
... No. of commodities/stocks/indices taken as sample for international and Indian studies (see online version for colours) Figure 7 shows the number of commodities/stock/commodity indices considered for each paper as sample data. The results that were drawn from Table 8 are that out of 84 international studies, 73 studies covered the number of commodities that lies between 0-5 (Baklaci et al., 2016;Chan et al., 2004;Zhong et al., 2004) and 6-10 (Bampinas and Panagiotidis, 2015;Cartwright and Riabko, 2015;Cavaliere et al., 2015;Chang et al., 2016;Dhineshni and Dhandayuthapani, 2016;Ganneval, 2016;Kang and Yoon, 2016;Kavussanos and Nomikos, 2003;Khalfaoui et al., 2015;Khoury and Yourongov, 1993;Lyocsa and Molnar, 2016;Mattos and Garcia, 2004;Peri et al., 2013;Todorova et al., 2014;Vasantha and Mallikarjunappa, 2015;Xu and Fung, 2005;Zhang and Wei, 2010) relative frequencies. For the remaining 11 international studies, the number of commodities lie between the 11-15 (Arouri et al., 2012;Azizan et al., 2007;Bhar and Hamori, 2005;Boonyanuphong and Sriboonchitta, 2014;Figuerola-Ferretti and Gonzalo, 2010;Fortenbery and Zapata, 1993;Hernandez et al., 2014;Karbuz and Jumah, 1995;Mensi et al., 2013;Moosa, 2002), 16-20 (Arouri et al., 2012;Azizan et al., 2007;Bhar and Hamori, 2005;Boonyanuphong and Sriboonchitta, 2014;Figuerola-Ferretti and Gonzalo, 2010;Fortenbery and Zapata, 1993;Hernandez et al., 2014;Karbuz and Jumah, 1995;Mensi et al., 2013;Moosa, 2002), 21-25 (Dimpfl et al., 2017;Nazlioglu et al., 2012;Tully and Lucey, 2007), 26-30 (Antonakakis and Kizys, 2015;Belgacem et al., 2015;Jia et al., 2015) and 31-35 (Krehbiel and Adkins, 1993). ...
The purpose of this paper is to organise the present status of
researches conducted on commodity market relationship, price discovery and volatility spillovers by reviewing the available literature. Other objectives of the present study are to classify the past studies under various categories, to provide an inclusive bibliography on the said topic and to evaluate the results of the studies taken into consideration by various researchers. Different sources were probed to review the past studies and out of thousands of paper, 130 research papers were considered, forming the sample for the present study.
It was found that the research work on this topic has surged from 2010 to 2017, thus gaining consistently higher attention since then. The present study will aid academicians, practitioners future researchers, policy makers and other relevant stakeholders in studying the existing research work, as well as in setting the directions for future research work related to same subject area and use of such
data in any field that can be contribute in a resourceful manner
... No. of commodities/stocks/indices taken as sample for international and Indian studies (see online version for colours) Figure 7 shows the number of commodities/stock/commodity indices considered for each paper as sample data. The results that were drawn from Table 8 are that out of 84 international studies, 73 studies covered the number of commodities that lies between 0-5 (Baklaci et al., 2016;Chan et al., 2004;Zhong et al., 2004) and 6-10 (Bampinas and Panagiotidis, 2015;Cartwright and Riabko, 2015;Cavaliere et al., 2015;Chang et al., 2016;Dhineshni and Dhandayuthapani, 2016;Ganneval, 2016;Kang and Yoon, 2016;Kavussanos and Nomikos, 2003;Khalfaoui et al., 2015;Khoury and Yourongov, 1993;Lyocsa and Molnar, 2016;Mattos and Garcia, 2004;Peri et al., 2013;Todorova et al., 2014;Vasantha and Mallikarjunappa, 2015;Xu and Fung, 2005;Zhang and Wei, 2010) relative frequencies. For the remaining 11 international studies, the number of commodities lie between the 11-15 (Arouri et al., 2012;Azizan et al., 2007;Bhar and Hamori, 2005;Boonyanuphong and Sriboonchitta, 2014;Figuerola-Ferretti and Gonzalo, 2010;Fortenbery and Zapata, 1993;Hernandez et al., 2014;Karbuz and Jumah, 1995;Mensi et al., 2013;Moosa, 2002), 16-20 (Arouri et al., 2012;Azizan et al., 2007;Bhar and Hamori, 2005;Boonyanuphong and Sriboonchitta, 2014;Figuerola-Ferretti and Gonzalo, 2010;Fortenbery and Zapata, 1993;Hernandez et al., 2014;Karbuz and Jumah, 1995;Mensi et al., 2013;Moosa, 2002), 21-25 (Dimpfl et al., 2017;Nazlioglu et al., 2012;Tully and Lucey, 2007), 26-30 (Antonakakis and Kizys, 2015;Belgacem et al., 2015;Jia et al., 2015) and 31-35 (Krehbiel and Adkins, 1993). ...
The purpose of this paper is to organise the present status of researches conducted on commodity market relationship, price discovery and volatility spillovers by reviewing the available literature. Other objectives of the present study are to classify the past studies under various categories, to provide an inclusive bibliography on the said topic and to evaluate the results of the studies taken into consideration by various researchers. Different sources were probed to review the past studies and out of thousands of paper, 130 research papers were considered, forming the sample for the present study. It was found that the research work on this topic has surged from 2010 to 2017, thus gaining consistently higher attention since then. The present study will aid academicians, practitioners future researchers, policy makers and other relevant stakeholders in studying the existing research work, as well as in setting the directions for future research work related to same subject area and use of such data in any field that can be contribute in a resourceful manner.
Oil and gold are considered as the most vigor influencer for any economy. In this research volatility spillover networking among the oil (energy), gold, and Asian leading emerging stock markets are constructed by the coalescence of two approaches BEKK-GARCH and complex networking. The data consists of the daily return of sixteen Asian countries’ stock markets, an index of the Asia Pacific, and future prices of oil and gold contracts for the period of 01–01-2010 to 31-05-2020. It covers all the recent shocks of the current decade to study the impact of these crises. The data is further divided into four sub-periods as well for this research. The results of our total period detect that commodities of oil and gold receive more volatility spillover than transfer it to stock indices of Asia Pacific countries. Moreover, it is also observed that, as compared to oil, gold had more strong significant spillover linkages. Among all Asian economies, the Chinese stock markets had more influence on the price movement of oil and gold. Whereas, India had more significant correlations with other neighboring stock indices. The results of this research not only provide the facts about the interconnection of oil, gold, and Asian Pacific countries in the current scenarios but also give very useful directions for future researchers, investors, and hedgers, as well as for policymakers interested in the Asian region.
Gold futures trading in the emerging and developed nations have been of prime importance among the commodities. This paper aims to determine the linkages between the Indian and Chinese gold futures markets by finding the return and volatility spillover effects. Using weekly data from 1 April 2009 to 31 March 2021, granger causality is found using the Toda Yamamoto approach. VAR (1) GARCH (1,1) model is used to know the spillover effects in the return and volatility of the markets. The granger causality result suggests a unidirectional causal relationship from MCX (Multi Commodity Exchange) to SHFE (Shanghai Futures Exchange). The estimates of the mean equation of VAR (1), GARCH (1,1) also state that the return in the Chinese market is unidirectionally impacted by the returns in the Indian market. Further, there is bidirectional volatility spillover between the markets. Overall, the results suggest that there is significant information transmission between the markets. The paper finds its importance in studying the linkages of the precious metal futures in the two largest emerging economies.
As the leading component of the financial market, the price formation mechanism of gold futures has been attracting extra attention of financiers and scholars. However, the data of gold futures price be-longs to time series, and its forecast is very challenging owing to its chaotic, noisy, and non-stationary characteristics in data. A new forecast model named SGRU-AM, based on the special gated recurrent unit (SGRU) and attention mechanism (AM) is proposed in this paper to tackle these challenges. SGRU is the rectified model of gated recurrent unit (GRU) though executing the 1-tanh function on the reset gate output of the basic GRU to transform the value range of the reset gate value and adjusting the memory ratio between the current moment and the previous moment. Firstly, SGRU has the advantage of capturing long-distance information and can forecast the closing price of gold futures in the next trading day. Then, AM is introduced to adjust the SGRU time dimension’s feature expression, so that the model can obtain more comprehensive feature information, learn the importance of current local sequence features and improve the forecast accuracy. Taking China’s gold futures as an example, the gold futures data of the Shanghai Futures Exchange are selected from January 9, 2008, to May 31, 2021. Compared with the baseline methods, the experimental results show that SGRU-AM has the best performance among all baseline models in forecast efficiency and forecast accuracy.
Gold exchange‐traded funds (ETFs) have amassed massive inflows from institutional investors globally. We examine intraday price discovery and volatility connectedness among three gold instruments—spot, futures, and ETF—across mature and emerging gold markets in domestic and international settings from 2010 to 2018. Using the network approach, we find that gold futures are a global leader in price discovery and volatility spillover. However, during 2016–2018, physical‐gold‐backed ETF and spot challenge the futures' leadership in New York and Shanghai. Intraday variation in price discovery leadership is due to liquidity, hedging effectiveness, price jumps, investor attention, and macroeconomic states.
This article examines information linkages between gold spot market in India and gold futures at India’s Multi Commodity Exchange (MCX) and five international platforms [i.e., Commodity Exchange (COMEX), Dubai Gold and Commodity Exchange (DGCX), Tokyo Commodity Exchange (TOCOM), Hong Kong Exchange (HKE) and Singapore Mercantile Exchange (SMX)] from August 2008 to March 2015. Cointegration procedure and vector error correction model (VECM), supported by Granger causality, are employed to study price discovery process, and bivariate EGARCH-BEKK model is used to examine volatility spillover process. At domestic level, spot market dominates the futures in information transmission process. Internationally, DGCX leads all other exchanges in price discovery process, while COMEX leads in volatility spillovers. In price discovery, MCX leads only TOCOM till August 2013, while price discovery is absent thereafter. In volatility spillovers, MCX dominates TOCOM and HKE till this period and only HKE afterwards. Thus, information linkages between MCX and international exchanges appear to have been impacted severely since August 2013. The study highlights the need to re-establish price and volatility linkages between Indian and international exchanges, and also provides significant suggestions for policymakers. The study is relevant for investors, researchers and the academia. It contributes to market efficiency and information transmission literature for commodity markets.
This paper examines the economic consequences of Commodity transaction tax (CTT) for the Indian commodities market. We use daily data on 5 sample commodities, namely gold, aluminum, copper, zinc and crude oil from 1st May 2010 to 31st August 2016. MCX has been used as a reference commodity exchange for India, while we use COMEX and DGCX for gold, LME and SHFE for base metals and NYMEX and ICE for crude oil for international comparison. We find that CTT imposition has weakened the price discovery and volatility spillover process, thus reducing the price and hedging efficiency of the Indian commodities market. International information linkages seem to have been more adversely impacted, owing to lower cost competitiveness. CTT has also substantially decreased commodity market liquidity and increased return volatility. Analysing the impact of CTT on total tax revenue, involving transaction tax, income tax and service tax, we conclude that CTT has been revenue negative. Additionally, CTT is found totally unjustified on the grounds of market parity and curbing speculation. Based on the economic and market related arguments, the study suggests a phased withdrawal of CTT, which would not only boost the growth and development of Indian commodities market but also imply greater fiscal revenues besides bringing in economic competitiveness among commodities stakeholders.
This study investigates the international price relationship and volatility transmissions betweenstock index and stock index futures of Malaysia, Hong Kong and Japan. Vector Autoregression(VAR) GJR-GARCH model was applied to the nine years daily price. Japanesemarkets are the main information producer to the market price changes. International marketinterdependence only affected the domestic volatility transmission of spot and futuresmarket in Hong Kong. Asymmetric effects exist in all markets and the volatility persistence ineach market is high. Finally, the overall conditional correlation estimates for spot and futuresmarkets are higher in the unrestricted model form compared to the restricted modelform.Keywords: spot-futures, lead-lags, volatility, VAR GJR-GARCH, Asian financial markets
This paper investigates the cross market linkages of Indian commodity futures for nine commodities with futures markets outside India. These commodities range from highly tradable commodities to less tradable agricultural commodities. We analyze the cross market linkages in terms of return and volatility spillovers. The nine commodities consist of two agricultural commodities: Soybean, and Corn, three metals: Aluminum, Copper and Zinc, two precious metals: Gold and Silver, and two energy commodities: Crude oil and Natural gas. Return spillover is investigated through Johansen’s cointegration test, error correction model, Granger causality test and variance decomposition techniques. We apply Bivariate GARCH model (BEKK) to investtigate volatility spillover between India and other World markets. We find that futures prices of agricultural commodities traded at National Commodity Derivatives Exchange, India (NCDEX) and Chicago Board of Trade (CBOT), prices of precious metals traded at Multi Commodity Exchange, India (MCX) and NYMEX, prices of industrial metals traded at MCX and the London Metal Exchange (LME) and prices of energy commodities traded at MCX and NYMEX are cointegrated. In case of commodities, it is found that world markets have bigger (unidirectional) impact on Indian markets. In bivariate model, we found bi-directional return spillover between MCX and LME markets. However, effect of LME on MCX is stronger than the effect of MCX on LME. Results of return and volatility spillovers indicate that the Indian commodity futures markets function as a satellite market and assimilate information from the world market.
Purpose
– The purpose of this paper is to investigate empirically the price discovery and volatility spillovers in Indian spot-futures commodity markets.
Design/methodology/approach
– The study has used four futures and spot indices of Multi-Commodity Exchange, Mumbai. The study also employs vector error correction model (VECM) and bivariate exponential Garch model (EGARCH) to analyze the price discovery and volatility spillovers in Indian spot-futures commodity market.
Findings
– The VECM shows that agriculture future price index (LAGRIFP), energy future price index (LENERGYFP) and aggregate commodity index (LCOMDEXFP) effectively serve the price discovery function in the spot market implying that there is a flow of information from future to spot commodity markets but the reverse causality does not exist. There is no cointegrating relationship between metal future price index (LMETALFP) and metal spot price index (LMETALSP). Besides the bivariate EGARCH model indicates that although the innovations in one market can predict the volatility in another market, the volatility spillovers from future to the spot market are dominant in the case of LENERGY and LCOMDEX index while LAGRISP acts as a source of volatility toward the agri-futures market.
Research limitations/implications
– The results are aggregate in nature. Further study at disaggregated level will provide further insights on behavior of specific commodity prices and the price discovery process.
Originality/value
– The paper provides useful information about the evolution and structures of futures commodity trading in India, related literature and relevant methodology concerning the hypotheses.
The short-run interdependence of prices and price volatility across three major international stock markets is studied. Daily opening and closing prices of major stock indexes for the Tokyo, London, and New York stock markets are examined. The analysis utilizes the autoregressive conditionally heteroskedastic (ARCH) family of statistical models to explore these pricing relationships. Evidence of price volatility spillovers from New York to Tokyo, London to Tokyo, and New York to London is observed, but no price volatility spillover effects in other directions are found for the pre-October 1987 period. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
Existing time-varying covariance models usually impose strong restrictions on how past shocks affect the forecasted covariance
matrix. In this article we compare the restrictions imposed by the four most popular multivariate GARCH models, and introduce
a set of robust conditional moment tests to detect misspecification. We demonstrate that the choice of a multivariate volatility
model can lead to substantially different conclusions in any application that involves forecasting dynamic covariance matrices
(like estimating the optimal hedge ratio or deriving the risk minimizing portfolio). We therefore introduce a general model
which nests these four models and their natural “asymmetric” extensions. The new model is applied to study the dynamic relation
between large and small firm returns.
Existing time-varying covariance models usually impose strong restrictions on how past shocks affect the forecasted covariance matrix. In this article we compare the restrictions imposed by the four most popular multivariate GARCH models, and introduce a set of robust conditional moment tests to detect misspecification. We demonstrate that the choice of a multivariate volatility model can lead to substantially different conclusions in any application that involves forecasting dynamic covariance matrices (like estimating the optimal hedge ratio or deriving the risk minimizing portfolio). We therefore introduce a general model which nests these four models and their natural "asymmetric" extensions. The new model is applied to study the dynamic relation between large and small firm returns.
This paper examines the international transmission mechanism of gold market movements by using the daily spot-contract data from Australia, Switzerland, and the U.S. over the period 1997-2004. With the intraday return as the variable in regression models, we find that the Australian market positively affects the Swiss market, that the Swiss market positively affects the U.S. market, and that the U.S. market positively affects the Australian market. When using the variable of the intraday return volatility in further analysis, the above three lead-lag relationships become much stronger. These results have important implications for investment strategies, portfolio management, option markets, and policy making. Overall, the new evidence contributes to the existing literature in financial market integration by suggesting that three gold markets are interrelated in terms of intraday returns and that there are high degrees of return volatility linkages among the Australian, Swiss, and U.S. gold markets.
This paper employs univariate and bivariate GARCH models to examine the volatility of gold and oil futures incorporating structural breaks using daily returns from July 1, 1993 to June 30, 2010. We find strong evidence of significant transmission of volatility between gold and oil returns when structural breaks in variance are accounted for in the model. We compute optimal portfolio weights and dynamic risk minimizing hedge ratios to highlight the significance of our empirical results. Our findings support the idea of cross-market hedging and sharing of common information by financial market participants.
This study attempts to examine the price discovery process and volatility spillovers in Gold futures and spot markets of National Commodity Derivatives Exchange (NCDEX) by employing Johansen’s Vector Error Correction Model (VECM) and the Bivariate ECM-EGARCH model. The empirical result confirms that the spot market of Gold plays a dominant role and serves as effective price discovery vehicle. Besides the study results show that the spillovers of certain information take place from spot market to futures market and the spot market of gold have the capability to expose the all new information through the channel of its new innovation.
In this article, we provide a detailed characterization of the intraday return volatility in gold futures contracts traded on the COMEX division of the New York Mercantile Exchange. The approach allows the study of intraday patterns, interday ARCH effects, and announcement effects in a coherent framework. We show that the intraday patterns exert a profound impact on the dynamics of return volatility. Among the 23 U.S. macroeconomic announcements, we identify employment reports, gross domestic product, consumer price index, and personal income as having the greatest impact. Finally, by appropriately filtering out the intraday patterns, we find that the high-frequency returns reveal long-memory volatility dependencies in the gold market, which have important implications on the pricing of long-term gold options and the determination of optimal hedge ratios. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:257–278, 2001
We tested the price linkage, the law of one price (LOP) condition, and the causality of the price linkage between the U.S. and Japanese gold and silver futures markets with consideration of structural breaks in the price series. The LOP condition did not hold for both the gold and silver markets when structural breaks were not considered but it sustained in some periods when it was tested for the break periods. We found from the causality test that the price linkage between the U.S. and Japanese gold and silver futures markets were led by the U.S. market.
This study examines futures price and volatility transmissions among three major wheat production and exporting regions, the United States (US), Canada and the European Union (EU) over the recent six-year study period of 1996 - 2002. The price transmission pattern shows that Canadian prices are much more influenced by the US prices than the US prices are influenced by Canadian prices. The EU is highly self-dependent and may exert some influence on the US prices in the long run but not vice versa. The volatility transmission pattern, however, shows that volatility is transmitted from Canada and the EU to the US but not vice versa. The volatility is also transmitted from the EU to Canada but not vice versa. Overall, there is no distinctive leadership role in international wheat markets, with all three markets exhibiting features of price leadership to some extent.
As GARCH models and stable Paretian distributions have been revisited in the recent past with the papers of Hansen and Lunde
(J Appl Econom 20: 873–889, 2005) and Bidarkota and McCulloch (Quant Finance 4: 256–265, 2004), respectively, in this paper
we discuss alternative conditional distributional models for the daily returns of the US, German and Portuguese main stock
market indexes, considering ARMA-GARCH models driven by Normal, Student’s t and stable Paretian distributed innovations. We find that a GARCH model with stable Paretian innovations fits returns clearly
better than the more popular Normal distribution and slightly better than the Student’s t distribution. However, the Student’s t outperforms the Normal and stable Paretian distributions when the out-of-sample density forecasts are considered.
We use a bivariate asymmetric GARCH model to examine patterns of across-market information flows for gold, platinum, and silver futures contracts traded in both the U.S. and Japanese markets. Our results indicate that pricing transmissions for these precious metals contracts are strong across the two markets, but information flows appear to lead from the U.S. market to the Japanese market in terms of returns. There are strong volatility spillover feedback effects across both markets, and their impacts appear to be comparable and similar. There is evidence that intraday pricing information transmission across the two precious metals futures markets is rapid, as offshore trading information can be absorbed in the domestic market within a trading day.
This paper examines the information transmission mechanism between corn futures traded in Tokyo and Chicago for the 1993–1995 period. Corn futures contracts traded on the Chicago Board of Trade (CBT) and the Tokyo Grain Exchange (TGE) have almost identical specifications. Different trading systems are used by the two exchanges, and their trading times do not overlap. Dynamic vector autoregression models are employed to test for price and volatility spillovers between the markets. The results indicate that the TGE is dependent on the CBT for information generation, which is reflected in the opening price of the TGE.
This study employs a bivariate GARCH model to examine the dynamic relationships between two gold futures markets (COMEX and TOCOM) before and during gold's recent uptrend of the past few years. Results show that the performance of COMEX is better than TOCOM. However, TOCOM leads COMEX in the mean return. Volatility transmission effects exist in both COMEX and TOCOM. While the responses to good news and bad news are symmetrical in TOCOM, they are asymmetric in COMEX.
The aim of this paper is to examine the role of gold in the global financial system. We test the hypothesis that gold represents a safe haven against stocks of major emerging and developing countries. A descriptive and econometric analysis for a sample spanning a 30Â year period from 1979 to 2009 shows that gold is both a hedge and a safe haven for major European stock markets and the US but not for Australia, Canada, Japan and large emerging markets such as the BRIC countries. We also distinguish between a weak and strong form of the safe haven and argue that gold may act as a stabilizing force for the financial system by reducing losses in the face of extreme negative market shocks. Looking at specific crisis periods, we find that gold was a strong safe haven for most developed markets during the peak of the recent financial crisis.
The capital asset pricing model provides a theoretical structure for the pricing of assets with uncertain returns. The premium to induc e risk-averse investors to bear risk is proportional to the nondivers ifiable risk, which is measured by the covariance of the asset return with the market portfolio return. In this paper, a multivariate, gen eralized-autoregressive, conditional, heteroscedastic process is esti mated for returns to bills, bonds, and stocks where the expected retu rn is proportional to the conditional covariance of each return with that of a fully diversified or market portfolio. It is found that the conditional covariances are quite variable over time and are a signi ficant determinant of the time-varying risk premia. The implied betas are also time varying and forecastable. Copyright 1988 by University of Chicago Press.
A multivariate time series model with time varying conditional variances and covariances, but constant conditional correlations is proposed. In a multivariate regression framework, the model is readily interpreted as an extension of the Seemingly Unrelated Regression (SUR) model allowing for heteroskedasticity. Parameterizing each of the conditional variances as a univariate Generalized Autoregressive Conditional Heteroskedastic (GARCH) process, the descriptive validity of the model is illustrated for a set of five nominal European U.S. dollar exchange rates following the inception of the European Monetary System (EMS). When compared to the pre- EMS free float period, the comovements between the currenciess are found to be significantly higher over the later period. Copyright 1990 by MIT Press.
This paper examines if the Indian stock market moves with other markets in Asia and the United States in an era of capital market reforms and the sustained interest of foreign investors in that market. By using techniques of cointegration, vector autoregression, vector error-correction models, and Granger causality, we find that, though there is definite information leadership from the U. S. market to all Asian markets, the U. S. indexes do not uniquely influence the integration of Asian markets, while Japan is found to play a unique role in the integration of Asian markets. The U. S. market is seen not only to influence, but also to be influenced by information from most of the major Asian markets. The Indian stock return in recent times is definitely led by major stock index returns in the United States, Japan, as well as other Asian markets, such as Hong Kong, South Korea, and Singapore. More important, returns on the Indian market are also seen to exert considerable influence on stock returns in major Asian markets.
This paper summarizes theoretical and empirical research on the roles and functions of emerging derivatives markets and the resulting implications on policy and regulations. Previous studies revealed that commodity derivatives markets offered an effective and welfare-improving method to deal with price volatility. Financial derivatives markets have helped to support capital inflows into emerging market economies. On the other hand, the use of financial derivatives has led to exacerbated volatility and accelerated capital outflow. There is a consensus that derivatives are seldom the cause of a financial crisis but they could amplify the negative effects of the crisis and accelerate contagion. Previous studies of derivatives markets have supported the hedging role of emerging derivatives markets. Empirical results from a few emerging countries suggest a price discovery function of emerging futures markets. The findings on the price stabilization function of emerging derivatives markets are mixed. Finally, recent research has documented that constructive development of derivatives markets in emerging market economies needs to be supported by sound macroeconomic fundamentals as well as updated financial policies and regulations.
This study assesses the market qualities of alternative price-formation processes for an emerging futures marketâthe Taiwan futures market. In 2002, the price formation process in the market changed during the period of trade between call auction and continuous auction. The performances of call auction and continuous auction are compared using intraday data. Empirical results show that the market is more liquid, and volatility is slightly lower, under continuous auction than under call auction. Also, there is robust evidence that continuous auction improves informative efficiency. The study suggests that for an emerging futures market like that of Taiwan, continuous auction offers a better trading environment for futures trading. In addition to demonstrating the virtue of continuous auction, this study also finds that the asymmetry in volatility is related to the price formation process. The asymmetry effect exists under continuous auction, but not under call auction.
Using a bivariate GARCH model, we examine patterns of information flows for three commodity futures traded in both the developed U.S. market and the emerging China market (copper, soybeans and wheat). For copper and soybeans, the two commodities that are subject to less government regulation and fewer import restrictions in China, we find that the U.S. futures market plays a dominant role in transmitting information to the Chinese market, a result that confirms the importance of the U.S. role as a leader in the global financial market. For the heavily regulated and subsidized wheat commodity, our empirical results indicate that the U.S.-China futures markets are highly segmented in pricing, although information transmission via volatility spillover across markets is present. Copyright 2003 by Kluwer Academic Publishers
In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996-2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.
We investigate the nature of volatility linkages in the stock, bond, and money markets. We develop a simple model of speculative trading that predicts strong volatility linkages in these markets due to common information, which simultaneously affects expectations across markets, and information spillover caused by cross-market hedging. To measure these linkages, we estimate a stochastic volatility representation of our trading model using GMM. The results indicate that our specification explains many of the observed characteristics of the data, and that the volatility linkages between the three markets are indeed strong. Moreover, we find that the linkages have become stronger since the 1987 stock market crash.
This study empirically examines volatility in US and Japanese commodity futures markets. The US futures market, COMEX, is double auction with continuous trading, whereas the Japanese futures market, TOCOM, was Walrasian with discrete trading until April 1991. We find intraday volatility for gold futures contracts to be significantly higher on COMEX than TOCOM throughout the sample period and is attributable to differences in information flows and market micro-structures. Evidence is also provided that exchange volume conveys information both within and across markets, which is consistent with the French and Roll, 1986 (French, K.R., Roll, R., 1986. Stock return variances: The arrival of information and the reaction of traders. Journal of Financial Economics 17, 5–26) private-information based rational trading model. Finally, daily variance and autocorrelation estimates within COMEX are consistent with the extant literature on equity markets.
This paper presents theoretical results in the formulation and estimation of multivariate generalizedARCH models within simultaneous equations systems. A new parameterization of themultivariate ARCH process is proposed and equivalence relations are discussed for the variousARCH parameterizations. Constraints sufficient to guarantee the positive definiteness of the conditionalcovariance matrices are developed, and necessary and sufficient conditions for covariancestationarity are presented. ...
Traditional econometric models assume a constant one-period forecast variance. To generalize this implausible assumption, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced in this paper. These are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances. For such processes, the recent past gives information about the one-period forecast variance. A regression model is then introduced with disturbances following an ARCH process. Maximum likelihood estimators are described and a simple scoring iteration formulated. Ordinary least squares maintains its optimality properties in this set-up, but maximum likelihood is more efficient. The relative efficiency is calculated and can be infinite. To test whether the disturbances follow an ARCH process, the Lagrange multiplier procedure is employed. The test is based simply on the autocorrelation of the squared OLS residuals. This model is used to estimate the means and variances of inflation in the U.K. The ARCH effect is found to be significant and the estimated variances increase substantially during the chaotic seventies.
According to the 2012 World Gold Council Report, the daily average trading volumes in Japanese and U.S. gold futures markets are USD 1
- Currently Argentina
- Brazil
- China
- India
- Indonesia
- Korea
- Nepal
- Philippines
- Romania
- Russia
- Turkey Taiwan
Currently, gold futures are traded in twelve emerging market derivatives exchanges: Argentina, Brazil,
China, India, Indonesia, Korea, Nepal, Philippines, Romania, Russia, Taiwan, and Turkey.
2. According to the 2012 World Gold Council Report, the daily average trading volumes in Japanese and U.S.
gold futures markets are USD 1.8 billion per day and USD 20.8 billion per day, respectively.
A tale of two index futures: The intraday price discovery and volatility transmission processes between the China financial futures exchange and the Singapore exchange. Emerging Markets Finance and Trade
- B Guo
- Q Han
- M Liu
- D Ryu
Guo, B., Q. Han, M. Liu, and D. Ryu. 2013. A tale of two index futures: The intraday price discovery and volatility transmission
processes between the China financial futures exchange and the Singapore exchange. Emerging Markets Finance and Trade
49, no. s4: 197-212. doi:10.2753/REE1540-496X4905S414.
Volatility dynamics in Dubai gold futures market
- R Nekhili
- M Thorpe
Nekhili, R., and M. Thorpe. 2011. Volatility dynamics in Dubai gold futures market. International Research Journal of Applied
Finance 2, no. 11: 1303-13.
According to the 2012 World Gold Council Report, the daily average trading volumes in Japanese and U.S. gold futures markets are USD 1.8 billion per day and USD 20.8 billion per day
- Argentina
- Brazil
- China
- India
- Indonesia
- Korea
- Philippines
- Romania
- Taiwan Russia
Currently, gold futures are traded in twelve emerging market derivatives exchanges: Argentina, Brazil,
China, India, Indonesia, Korea, Nepal, Philippines, Romania, Russia, Taiwan, and Turkey.
2. According to the 2012 World Gold Council Report, the daily average trading volumes in Japanese and U.S.
gold futures markets are USD 1.8 billion per day and USD 20.8 billion per day, respectively.
3. The price series are collected from Bloomberg's Database.