The focus of this research is commoditizing environmental credits into standardized units by guaranteeing the provenance of the credit through the application of blockchain technology. The commoditization occurs by creating a decentralized clearing process using blockchain for the environmental credit market. The cleared standardized commodity units can then potentially be traded without the risk of rejection by the U.S. Environmental Protection Agency (EPA) because of production fraud or errors. The removal of the rejection risk would allow for small farmers, municipal wastewater plants and landfills to enhance their profitability by producing green electricity from biogas and receiving market tradable environmental credits. The complexity of the pathway requires blockchain, which creates an immutable ledger holding production and distribution data for the environmental credit. This immutable ledger supplies provenance that can eliminate counterparty risk when combined with the concept of decentralized clearing of the credits.

In 2021, an average 35.5 billion cubic feet per day (Bcf/d) of natural gas was consumed in China, more natural gas than in any previous year. More than half of the natural gas consumed in China in 2021 came from domestic production, but China also imported record amounts of natural gas by pipeline and as liquefied natural gas (LNG), surpassing Japan as the largest LNG importer for the first time, based on data from Global Trade Tracker and China’s General Administration of Customs. After becoming the world’s largest LNG importer in 2021, China reduced its LNG imports by approximately one-third in the first seven months of this year. LNG imports in China have decreased this year for the first time since 2015. The decline in LNG imports was driven in part by the slower economic growth, high spot LNG prices, robust growth in hydro and non-hydro renewable power generation that displaced more expensive gas-fired power-generation, as well as government policies, which this year reprioritized supply security and economic stability over emissions targets.

This article develops a theory of multiproduct hedging which serves to formalize Keynes’s hedging pressure hypothesis that the need to attract speculative capital to match hedgers’ trades creates a difference between the futures and expected maturity price. The authors test the theory empirically in the context of the soybean complex which has speculators and hedgers in soybeans, soybean meal and soybean oil. The focus is on the crush spread because it is unlikely that hedgers will want to make simultaneous trades on the opposite side of soybean crushers in all three markets. The findings reveal that there is a significantly positive return to speculators for providing this liquidity.

Commodity style-integration is appealing because by forming a unique long-short portfolio with simultaneous exposure to mildly correlated factors, a larger risk premium can be captured over time than with any of the underlying standalone styles. A practical decision that a commodity style-integration investor faces at each rebalancing time is the relative weight of the predictive- or sorting-signal that underlies each standalone style. The authors of this paper develop a new Bayesian optimized integration (BOI) method that accounts for estimation risk in the style-weighting decision. Focusing on the problem of a commodity investor that seeks exposure to the carry, hedging pressure, momentum, skewness, and basis-momentum factors, they demonstrate that the BOI portfolio outperforms not only a battery of parametric style-integrations motivated by the portfolio optimization literature, but also the highly effective equal-weight integrated portfolio. The findings survive the consideration of transaction costs, alternative commodity scoring schemes, and long estimation windows.