Journal of Futures Markets最新文献

We present a model to explain the diversification benefits of incorporating commodities into a portfolio of traditional assets from the perspective of domestic investors. Utilizing a sample of 38 countries from 2000 to 2020, we show that investors in high-commodity dependence countries generally do not benefit from adding commodities to their portfolios while investors located in low-commodity dependence countries usually do. Our results thus show that local contexts matter and that commodities may augment a diversified portfolio if investors are not excessively exposed to commodity risk through their country's economic structure.

We report a significant downward trend in the convenience yield for holding physical inventory in agricultural commodity futures markets, attributing this negative trend to speculative demand shocks, which in turn, leads in decreasing agricultural convenience yields. Moreover, agricultural convenience yields appear negative on average during the recent financialization (of commodities) period. We additionally show that the response of agricultural convenience yields to commodity price uncertainty and supply shocks is much less pronounced in magnitude and persistence compared to that of hedging demand shocks. Overall, our analysis verifies the Keynesian theory of normal backwardation by showing a long-lasting positive response of agricultural convenience yields to a hedging demand shock, thereby leaving the hedging demand as the most significant factor explaining the less frequently observed backwardations in agricultural futures markets.

This study clarifies discrepancies in previous research on the contribution of regulated Bitcoin futures to price discovery, where conclusions have varied between futures leading over spot markets or vice versa. We identify potential reasons behind these conflicting findings, including the choice of price discovery measures, sampling frequencies, modeling windows, futures contracts, and spot exchanges. Using 1-s sampling frequencies to accurately capture price discovery in the fast-paced markets and accounting for substantial noise differences between spot and futures markets, we find that the futures market generally leads spot markets, though this price leadership exhibits daily fluctuations. Moreover, we observe a pronounced increase in the futures market's contribution to price discovery around macroeconomic surprises and Tether stablecoin minting tweets.

This paper investigates the interdependence between economic policy uncertainty (EPU) and implied market volatility using a Bayesian copula network. The results indicate that market-implied volatilities serve as more reliable forward-looking indicators of uncertainty compared to newspaper-based EPU. Through a complex partial wavelet coherence approach, the study further explores the dynamic interdependence between these variables, revealing the specific time-domain patterns of their effects on economic uncertainty and the conditions under which they can be distinguished as measures of risk aversion and ambiguity aversion. Notably, the findings suggest that, in the short time scales, the media tends to generate ambiguity, contributing to belief divergence among market participants. However, over longer time scales, EPU increasingly reflects economic uncertainty. These insights are valuable for gaining a deeper understanding of the media's role in conveying information and the behavioral traits influencing economic decision-making.

We apply the regression-based affine term structure model to estimate the term structure of commodity futures. This model is advantageous in that it has a simple and fast algorithm, can accommodate a variety of observable and unspanned factors, and can be applied to daily and even real-time observations. The results show that the model appropriately captures time-series variations across different maturities and exhibits satisfactory performance in capturing cross-sectional variations for specific months. Furthermore, we investigate the relationship between the existing commodity risk factor returns and the risk premiums inferred by the model. Our analysis reveals that different risk factor returns explain the spot and term premiums differently. Therefore, using the advantages of the model, we can better understand the term structure and risk premiums in commodity futures.

This paper studies the pricing of vulnerable options with systematic and idiosyncratic factors incorporated. Variance gamma processes are employed to model price jumps caused by the arrivals of systematic and idiosyncratic relevant information. A parsimonious pricing measure is developed and Laplace transforms of option price and Greek letters are given. Numerical results are obtained by a two-sided Euler inversion method in an efficient and accuracy way. It shows that in contrast to idiosyncratic factors, the effect of systematic factors on vulnerable options is strongly affected by the skewness and leptokurtosis features of systematic variance gamma processes.