Journal of Futures Markets最新文献

The least squares Monte Carlo (LSM) algorithm proposed by Longstaff and Schwartz (2001) is widely used for pricing Bermudan options. The LSM estimator contains undesirable look-ahead bias, and the conventional technique of avoiding it requires additional simulation paths. We present the leave-one-out LSM (LOOLSM) algorithm to eliminate look-ahead bias without doubling simulations. We also show that look-ahead bias is asymptotically proportional to the regressors-to-paths ratio. Our findings are demonstrated with several option examples in which the LSM algorithm overvalues the options. The LOOLSM method can be extended to other regression-based algorithms that improve the LSM method.

This study develops a novel approach for improving stock return volatility forecasts using volatility index information with the entropic tilting technique. Unlike traditional linear heteroskedasticity autoregressive methods with option-implied information, we first derive predictive densities from traditional models, and then tilt using both the first and second moments of the risk-neutral distribution, which enables us to capture the nonlinear effect in our specification. The empirical findings demonstrate a substantial enhancement in the forecasting accuracy of all models once the first- and second-moment information is considered, where the improvement is both statistically and economically significant. These results have important implications for risk management in well-established derivatives markets.

Climate-change futures provide a platform for low-carbon portfolios and energy market risk hedging. Climate changes induce uncertainty in energy-commodity markets. We investigate the potential of diversifying and hedging energy-commodity market risk with climate-change futures, using dynamic conditional correlation (DCC)-ordinary least squares (OLS) incorporating quantile-dummies and cross-quantilogram (CQ) approaches. DCC-OLS models reveal that the World and USA climate-change futures exhibit that they can be diversifiers for oil, ethanol, gasoil, and gasoline. These futures also exhibit hedging features for natural gas, coal, and heating oil. Euro climate-change futures demonstrate hedging capabilities for all energy commodities except oil and gasoil. World, USA, and Euro climate-change futures have the potential to serve as safe-haven financial instruments in the face of the high volatility of Brent crude oil, gasoil, and heating oil. The CQ reveals that World, USA, and Euro climate-change futures exhibit hedging and safe-haven capacity against oil, natural gas, coal, gasoil, gasoline, and heating futures. Climate-change futures may protect financial investments during extreme volatility in energy commodities.

To address the ongoing contention surrounding the impact of financialization, this study adopts a ripple-spreading network model to analyze the transmission of information across 13 globally significant commodity markets. By juxtaposing the pre- and postfinancialization periods, notable disparities in spillover magnitude are discerned, with overall effects registering at 58% and 85%, respectively. Moreover, the postfinancialization period exhibits accelerated spillover dynamics, necessitating a reduced timeframe (less than 1000 units) in contrast to the prefinancialization period (approximately 2000 units). Furthermore, a heightened interconnectedness among energy, metal, and agricultural futures is evident in the postfinancialization period. These findings furnish compelling evidence regarding the ramifications of financialization on commodity markets.

Delta-hedged option selling strategies typically yield positive returns, owing to the volatility risk premium embedded in the option price. Recent research based on S&P 500 options has found a day–night asymmetry in option returns. We find a similar disparity in the returns for short Nifty option strategies. Positive and significant overnight option returns are accompanied by negative intraday returns. The day–night asymmetry is robust across option categories and subsamples but weaker on days with significant jumps in the underlying. We confirm that the variance risk premium earned by option sellers is mainly a reward for overnight risk.

Based on the formation and evolution of systemic risk, we study the high-low volatility spillovers between economic policy uncertainty (EPU) and commodity futures and identify the source of risk accumulation and risk outbreak, as well as the corresponding contagion mechanisms. Upon comparing topological characteristics on each volatility layer, our results demonstrate that high and low volatility spillover networks have different network characteristics and evolution behaviors. At the system level, high volatility spillovers are relatively stronger than spillovers in in low volatility network, while the risk propagation efficiency in the low volatility network is higher. At the market level, EPU is not only an important risk-emitter but also a risk-recipient most of the time. Additionally, compared with high volatility network, low volatility network characteristics have greater predictive ability for risk spillover among commodity futures, which means that it contains additional information and provides early warning signals for financial stress.