Journal of Futures Markets最新文献

This study is the first to examine China's Crude Oil options market. Using high-frequency data and three different price discovery measures, we undertake a rigorous analysis and find that after its first 8 months of operation, China's Crude Oil options market contributes meaningfully to price discovery. Factors including volatility, spread, and speculation levels are shown to impact its price discovery ability. We also find a unique phenomenon in China's Crude Oil derivatives markets in that speculation adds more to the price discovery of the futures market compared with the options market, which is consistent with previous findings for the Chicago Mercantile Exchange Natural Gas derivatives market.

We consider European option pricing when the volatility of the underlying stock is stochastic and affected by economic cycles. We further assume that market liquidity risks have a significant impact on the price of the stock that is not negligible, and stock prices should be adjusted according to a liquidity discounting factor. For the purpose of option pricing, we transform the established model dynamics under the physical measure into those under a risk-neutral measure, which forms a foundation in the subsequent closed-form derivation of the characteristic function. An analytical option pricing formula is then obtained, and numerical tests together with sensitivity analysis are also performed. Through an empirical analysis, we demonstrate that our model, which incorporates stochastic liquidity, significantly outperforms the version with constant liquidity.

In this article, we consider basket spread options with default risk in a pricing model, where GARCH-jump processes are employed to describe the dynamics of all the underlying assets, and default risk is incorporated in a reduced form model. After successfully deriving the approximate pricing formula, we utilize the average cumulative default rates provided by Moody's spanning from 1970 to 2015 to estimate the parameters in the default intensity. Finally, we illustrate the impact of jump risk and default risk on basket spread options after checking the accuracy and efficiency of the approximate prices via Monte Carlo simulation methods.

This paper investigates the interplay between speculative and price volatility in the energy futures markets over various cycles, utilizing wavelet coherence and a double-layer network approach. Contrary to conventional wisdom, we find that long-term price volatility in individual futures markets, driven by extreme events, persistently leads to increased speculative trading, partly associated with increased hedging and risk management activity. The connectedness of the two-layer network system is dominated by speculation and volatility spillovers in the short and long term, respectively. The cross-layer spillover effects between price volatility and speculation are more pronounced in the long term. The direct and network effects of speculation reinterpret the interaction patterns among various futures markets. Specifically, the crude oil market, as a net receiver of spillover effects, exhibits an impact of speculation on price volatility driven primarily by network effects. However, the natural gas market is dominated by the direct effects of speculation.

In this study, we propose measures for the risk of commodity price crash. Building on the recent phenomenon of financialization of commodities, we advocate the use of down-to-up volatility (DUVOL) and a negative coefficient of skewness (NCSKEW) using 1-min and daily data, respectively. We find that the crash risk is the highest for natural gas, sugar, and coffee and remains low to moderate for most precious metals. Subsequently, we explore the commodity-specific drivers of crash risk upon controlling for macro-economic variations. We find that speculation and hedging pressure exacerbate the crash risk of most commodities, whereas basis risk alleviates the crash risk of commodities. We document that crash risk is priced in the cross-section of commodity returns. We also find that the crash risk spillovers are asymmetric, remaining low at 33% at the median and peaking at approximately 88% during the extremities.

The launch of the Shanghai International Energy Exchange crude oil futures (INECOFs) is a milestone in China's path to a dominant position in the global energy market. As INECOFs attract more and more investors, understanding the long-term correlations between INECOFs and global and regional benchmarks, as well as the driving forces of these correlations, is of paramount interest to investors wishing to conduct risk management and portfolio diversification. This article makes the first attempt to explore the determinants of such correlations using the mixed-frequency approach. Our results show that INECOFs are highly correlated with the regional benchmarks and less correlated with the global benchmarks. China's crude oil imports, RMB internationalization, the RMB index, economic and trade policy uncertainty, and geopolitical risks significantly impact the dynamics of the correlations in question. China's gross industrial product and price levels cannot drive the movements of all the studied correlations.