Economies of diversification and stochastic dominance analysis in French mixed sheep farms

Farm diversification is mainly driven by risk mitigation effects and economic gains related to complementarities between production activities. By combining these two aspects, we investigate diversification economies in a sample of French mixed sheep farming systems and rank these systems using stochastic dominance criteria. Partially diversified systems (Sheep-Grass, Sheep-Crop, Sheep-Landless) and fully diversified systems (Sheep-Grass-Crop-Landless) were evaluated. We find a high degree of diversification diseconomies in the sheep farming systems considered. The results also indicate that the fully diversified system is driven by its risk-reducing effects (including downside risk exposure) and that Sheep-Crop is the dominant system in terms of risk-adjusted returns.

A model for measuring distruption risk in the prefabrication supply chain

Use of prefabrication in construction projects is increasing due to the benefits in cost, time, quality, and safety. However, utilizing prefabrication introduces uncertainties inherent with the supply chain of the process. These uncertainties, if not managed, can disrupt the prefabrication process and result in schedule delays and cost overruns. This study proposes a model to measure disruption risks in the prefabrication process. The model was used in measuring the disruption risks of prefabrication of headwalls in patients’ rooms for a healthcare project as a pilot study. The risk model could successfully identify the disruption risks originating anywhere in the supply chain based on input information such as required material quantity, batch sizes of material deliveries, production rates, and batch sizes of transporting the headwall units. Using the model, the project team identified two uncertainties that could lead to possible disruptions: the start of the prefabrication processes and the required production rate to meet the on-site schedule. This is a first step to developing a risk exposure model that can prove valuable to the risk managers to analyse and manage the impact of disruptions. This will help the risk managers in making informed decisions about where to focus their limited resources.

Sukuk Performance Using Comparison of Return and Risk Through Calculation of Market Price and Fair Price

Sukuk investors’ important information used by investors of Sukuk (proof or claim of ownership on assets) is the market price of the Sukuk issued by the IDX and the fair price of the Sukuk issued by the Indonesian Securities Price Appraiser (PHEI). This is a signal or initial information for investors in considering the decision to invest in Sukuk. The measured performance returns as measured by Holding Period Yield (HPY), Yield To Maturity (YTM), and Sharpe Index, while Risk of Sukuk is measured based on its standard deviation. Corporate Sukuk are classified into financial and non-financial sectors and have short, medium, and long maturities. Comparative analysis is conducted using an Independent Sample t-test and ANOVA. The results showed that the average Sukuk return was calculated at a higher market price than the fair price. Sukuk return results in a pattern of movement that tends to be inversely proportional to the market price or fair price of the Sukuk, while the risk of Sukuk based on price issuing institutions had a movement pattern that tends to be in the same direction as the price. Furthermore, corporate Sukuk in the non-financial sector had a higher average return but was more susceptible to risk than the financial sector. Corporate Sukuk with long maturities had a higher average yield and risk exposure than medium and short-term Sukuk. Hypothesis testing showed a significant difference between the market price and the fair price of corporate Sukuk.

A VaR-Based Methodology for Assessing Carbon Price Risk across European Union Economic Sectors

The latest European Union measures for combating climate adopted in the “Fit for 55 package” envisage the extension of the Emissions Trading System, the first “cap-and-trade” system in the world created for achieving climate targets, which limits the amount of greenhouse gas emissions by imposing a price on carbon. In this context, our study provides an integrated assessment of carbon price risk exposure of all economic sectors in the European Union Member States, thus supporting decision making in determining the energy transition risk. We propose a novel approach in assessing carbon risk exposure using the Value at Risk methodology to compute the carbon price under the EU ETS, based on historical price simulation for January–August 2021 and ARMA-GARCH models for the October 2012–August 2021 period. We further built a value erosion metric, which allowed us to establish each sector’s exposure to risk and to identify differences between Eastern and Western EU countries. We find that the refining sector appears to be highly vulnerable, whereas there is higher potential for large losses in the energy supply and chemical sectors in Eastern EU Member States, given a different pace of industry restructuring.