The volatility dynamics of spot and futures gold prices: Evidence from Russia

We examine the long memory property and structural break in the spot and futures gold volatility in Russia from 2008 through 2013. We find strong evidence of long memory in the volatility of both spot and futures gold series. The break dates are associated with the recent global financial crisis. Moreover, we investigate the volatility spillover effect between the Russian spot and futures gold markets using the corrected Dynamic Conditional Correlation model (cDCC). The findings show relatively high level of conditional correlation between spot and futures gold returns. This outcome decreases the portfolio diversification benefits for gold investors.     

Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures

We provide empirical evidence on the patterns of intra- and inter-regional transmission of information across 10 developed and 11 emerging markets in Asia, the Americas, Europe and Africa using both stock indices and stock index futures. The main transmission channels are examined in the period from 2005 to 2014 through the analysis of return and volatility spillovers around the most recent crises based on the generalized vector autoregressive framework. Our findings demonstrate that markets are more susceptible to domestic and region-specific volatility shocks than to inter-regional contagion. A novel result reported in our study is a difference in patterns of international signals transmission between models employing indices and futures data. We conclude that futures data provide more efficient channels of information transmission because the magnitude of return and volatility spillovers across futures is larger than across indices. Our findings are relevant to practitioners, such as stock market investors, as well as policy makers and can help enhance their understanding of financial markets interconnectedness.     

国内外黄金市场价格间的联动关系稳定吗?——基于外部冲击视角的分析

在全球金融市场不断开放和融合的大背景下,黄金市场不但与外部市场频繁互动,其系统内部的联动关系也变得极为多元和复杂,黄金市场间的价格联动反映了信息和风险在不同市场间的传递过程。黄金价格通常会受到外部因素干扰而产生波动,但市场间的联动关系是否会因此而改变是值得重点关注的问题,黄金市场功能的有效性及稳固的市场关系是投资者利用全球黄金市场进行对冲和避险的先决条件,同时也关系到整个金融市场的稳定性。本文将研究重点聚焦于黄金市场内部,在研究中外各主要黄金市场间动态相关性和波动溢出效应的同时引入外部冲击以检验不同因素对黄金期货、现货市场间联动关系的影响从而探讨国内外黄金市场间价格联动的稳定性问题。结果表明:中国与全球主要黄金期货、现货市场间整体上保持了正相关关系,同时与各主要黄金市场间均存在显著的波动溢出效应。在一般市场条件下,外部冲击并没有显著改变中国与全球主要黄金期货、现货市场间的联动关系,表明黄金市场内部的价格联动具有较强的稳定性。     

A Model of Returns and Trading in Futures Markets

This paper develops an equilibrium model of a competitive futures market in which investors trade to hedge positions and to speculate on their private information. Equilibrium return and trading patterns are examined. (1) In markets where the information asymmetry among investors is small, the return volatility of a futures contract decreases with time-to-maturity (i.e., the Samuelson effect holds). (2) However, in markets where the information asymmetry among investors is large, the Samuelson effect need not hold. (3) Additionally, the model generates rich time-to-maturity patterns in open interest and spot price volatility that are consistent with empirical findings.     

Information connectedness of international crude oil futures: Evidence from SC,WTI, and Brent

The first Yuan (RMB) denominated crude oil futures contract, SC, was launched in the Shanghai International Energy Exchange (INE) on 26 March 2018, which is extremely meaningful for China and other Asian countries by offering a new option of oil price risk management. To identify the information connectedness among this emerging contract and those mature WTI and Brent oil futures, we provide return and volatility directional connectedness evidence among them in both the time and frequency domains. The empirical results show that, firstly the three oil futures of SC, WTI, and Brent present high degree of total connectedness in the return and volatility series, implying tight information transfer among them. Secondly, the net directional connectedness results suggest that the SC can provide competitive information on oil returns and is a net and powerful contributor to volatility shocks. In addition, from a frequency-specific perspective, we find that the SC appears to be not only a net transmitter of return shocks on the medium- and long-term frequencies but also a net transmitter of volatility shocks consistently across the whole frequency ranges. The overall evidence suggests that China's new oil futures is an active participant in the international oil futures market, and may become an important product in information transmission across international crude oil futures markets by providing effective hedging instrument for crude oil producers, refiners, consumers, and investors, especially those in Asia.     

Shock and Volatility Transmission in the Futures and Spot Markets: Evidence from Turkish Markets

This paper examines the volatility transmission mechanism between the futures and corresponding underlying asset spot markets, focusing on Turkish currency and stock index futures traded on the lately established Turkish Derivatives Exchange (TURKDEX). Employing multivariate generalized autoregressive conditional heteroskedasticity modeling, which allows for potential spillovers and asymmetries in the variance-covariance structure for the market returns, the paper investigates the volatility interactions among each of the three futures-spot market systems. For all market systems under study, the volatility spillovers are found to be important and bidirectional. For the stock index market system, in line with the previous literature, volatility shows asymmetric behavior and strong asymmetric shock transmission. The main implication is that investors need to account for volatility spillovers and asymmetries among the futures and the spot markets to correctly build hedging strategies.     

Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect

Future markets play vital roles in supporting economic activities in modern society. For example, crude oil and electricity futures markets have heavy effects on a nation’s energy operation management. Thus, volatility forecasting of the futures market is an emerging but increasingly influential field of financial research. In this paper, we adopt big data analytics, called Extreme Gradient Boosting (XGBoost) from computer science, in an attempt to improve the forecasting accuracy of futures volatility and to demonstrate the application of big data analytics in the financial spectrum in terms of volatility forecasting. We further unveil that order imbalance estimation might incorporate abundant information to reflect price jumps and other trading information in the futures market. Including order imbalance information helps our model capture underpinned market rules such as supply and demand, which lightens the information loss during the model formation. Our empirical results suggest that the volatility forecasting accuracy of the XGBoost method considerably beats the GARCH-jump and HAR-jump models in both crude oil futures market and electricity futures market. Our results could also produce plentiful research implications for both policy makers and energy futures market participants.     

Time and frequency dynamics of connectedness and hedging performance in global stock markets: Bitcoin versus conventional hedges

Some studies have revealed the hedging ability of Bitcoin against stock markets, but the knowledge of how it compares with other hedges is in its infancy. This paper presents the first study on time-frequency domain connectedness and hedging among five hedges (Bitcoin, crude oil, commodities, gold and the U.S. dollar (USD) index) and four stock indices (developed markets ex U.S., emerging markets ex China, U.S. and China). We find that the connectedness between hedges and stock markets varies by time across time horizons. Specifically, the connectedness between Bitcoin and stock indices is the smallest among all hedges, especially for the short horizon. Gold and USD are isolated from other markets at longer horizons. The hedging ratio, optimal portfolio weights and hedging effectiveness also vary across investment horizons. For short-term investment, gold has better hedging effectiveness, especially for emerging stock markets and the U.S. stock market. For median- and long-term investment, USD has better performance, especially for developed markets ex U.S. and emerging stock markets. Additionally, although Bitcoin has good hedging properties, it has high volatility compared with other hedging assets. In other words, if Bitcoin is included in a portfolio, investors should pay attention to its wide variation. These empirical findings highlight the important role that gold and USD play in hedging against global stock markets.     

Volatility spillovers across NFTs news attention and financial markets

The aim of this study is to investigate the volatility spillover connectedness between NFTs attention and financial markets. This paper firstly proposes a new direct proxy for the public’s attention in the NFT market: the non-fungible tokens attention index (NFTsAI), based on 590m news stories from the LexisNexis News & Business database and applies the historical decomposition to assess the historical variations of the NFTsAI. Then the empirical analysis is performed via a TVP-VAR volatility spillover connectedness model. The empirical results show that NFTsAI indicates NFT markets are dominated by cryptocurrency, DeFi, equity, bond, commodity, F.X. and gold markets. And NFT markets are volatility spillover receivers. In addition, NFT assets could impede financial contagion and have significant diversification benefits. Employing a panel pooled OLS regression model as a supplementary analysis and a GARCH-MIDAS model as a robustness test. This study reveals that NFTsAI has sufficient power to explain the return of NFT assets from a fixed effect perspective, and NFTsAI contains useful forecasting information for both short and long-term volatility of NFT markets, separately. The new NFTsAI and the empirical findings contain useful insights for risk-averse investors, portfolio managers, institutional investors, academics and financial policy regulators.     

Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis

We study the simultaneity impact of the European Central Bank news on the daily realized volatility transmission mechanism (spillovers) among various US spot and futures markets. To this end, we apply a bias-corrected vector autoregressive model via Wild bootstrap simulation. We use minute-by-minute intraday data to construct daily realized volatility. We consider 429 news form the ECB as important events employing two major classifications, namely, a country classification with the highest total number of days related ECB news and a type of ECB news classification. We find that investors in futures markets react more vigorously and mainly for the ECB news that is associated with the group of EMU member states applied structural reforms. Yet, more importantly, we show that the US stock markets response heterogeneously to the ECB news, as we find key disagreements in the reactions both across the US markets and the types of ECB news studied. Such evidence is consistent with the explanation of the differential interpretation of information among market participants. From a practical point of view, we suggest that investors in the US spot market can effectively use two or more futures contracts to minimize their exposure to volatility risk associated with that news.