Moderating Effect of Environmental Uncertainties on the Relationship between Risk Hedging Supply Chain Strategy and Performance of Manufacturing Firms in Kenya

The manufacturing sector in Kenya is faced by the challenges of performance and unstructured supply chain strategy. Further, the manufacturing sector growth in 2014 was 3.4% compared to a 5.6% growth in 2013 (Waiguru, 2015). This slow growth in manufacturing sector performance can be attributed to several environmental uncertainties such as the general election, high production costs, supply disruptions, political stability, unavailability of raw materials or demand fluctuations, technological changes, employees’ strikes, financial risk, terrorism and competition from imported goods (KNBS, 2018).The purpose of the study was to determine the moderating effect of environmental uncertainties on the relationship between risk hedging supply chain strategy and performance of manufacturing firms in Kenya. The study utilized descriptive research design. The target population was 829 managers from manufacturing firms around the country. A sample of 270 managers was selected using stratified random sampling. Results indicated that risk hedging supply chain strategy explained 63.8% of the total variations in performance of manufacturing firms. In addition, risk hedging supply chain strategy had a positive and significant effect on firm performance (β=0.675, P < .000). With introduction of moderating variable (environmental uncertainties); risk hedging supply chain strategy explained 34% of the total variations in performance of manufacturing firms. This denoted those environmental uncertainties had a negative moderating effect on the relationship between risk hedging supply chain strategy and performance of manufacturing firms in Kenya. The study concluded that risk hedging supply chain strategy had a positive and statistically significant effect on performance of manufacturing firms in Kenya. The study further concluded that environmental uncertainties lower the effect of risk hedging supply chain strategy on firm performance. The study recommends that manufacturing firms should strengthen aspects related to risk hedging supply chain strategy. The firms should particularly strengthen safety stock, suppliers’ management and quality. The improvement of these aspects is expected to enhance performance of the manufacturing firms. This study further recommends that manufacturing firms should factor in environmental uncertainties related to demand, supply and technology when implementing supply chain strategies.

Research on Financial Hedging Decision Based on Exchange Rate Risk in Transnational Supply Chain

This paper considers a three-echelon manufacturer-retailer-supplier supply chain, the purpose of which is to investigate the influence of the bilateral exchange rate risks of import and export and the leading company’s financial hedging on the decision-makers of the supply chain. Firstly, it constructs the profit function and the financial hedging decision-making model of each member in the decentralized supply chain. Secondly, it introduces the incentive mechanism of exchange rate risk hedging in the centralized supply chain. Thirdly, from the perspective of wholesale price agreements and revenue-sharing contracts, it discusses the impact of financial hedging behavior and bilateral exchange rate risks on the decision-making process of each member through mathematical modeling. Finally, it explores the relationships of decision variables through simulation analysis. The results illustrate that (i) for decentralized and centralized decision-making, the manufacturer’s expected profit and profit variance decrease with the increase of the fluctuations of import and export exchange rates under the hedging strategy for exchange rate risks; (ii) compared with the decentralized supply chain, the manufacturer’s expected profit in the centralized supply chain decreases slightly under the revenue-sharing contract; (iii) in the centralized supply chain, if the manufacturer’s risk hedging ratio is high, its profit variance is smaller than that of the decentralized supply chain and the expected profits of the retailer and the supplier will increase significantly; and (iv) for the members of the transnational supply chain, centralized decision-making is better than decentralized decision-making.

Implied volatility estimation of bitcoin options and the stylized facts of option pricing

The recently developed Bitcoin futures and options contracts in cryptocurrency derivatives exchanges mark the beginning of a new era in Bitcoin price risk hedging. The need for these tools dates back to the market crash of 1987, when investors needed better ways to protect their portfolios through option insurance. These tools provide greater flexibility to trade and hedge volatile swings in Bitcoin prices effectively. The violation of constant volatility and the log-normality assumption of the Black–Scholes option pricing model led to the discovery of the volatility smile, smirk, or skew in options markets. These stylized facts; that is, the volatility smile and implied volatilities implied by the option prices, are well documented in the option literature for almost all financial markets. These are expected to be true for Bitcoin options as well. The data sets for the study are based on short-dated Bitcoin options (14-day maturity) of two time periods traded on Deribit Bitcoin Futures and Options Exchange, a Netherlands-based cryptocurrency derivative exchange. The estimated results are compared with benchmark Black–Scholes implied volatility values for accuracy and efficiency analysis. This study has two aims: (1) to provide insights into the volatility smile in Bitcoin options and (2) to estimate the implied volatility of Bitcoin options through numerical approximation techniques, specifically the Newton Raphson and Bisection methods. The experimental results show that Bitcoin options belong to the commodity class of assets based on the presence of a volatility forward skew in Bitcoin option data. Moreover, the Newton Raphson and Bisection methods are effective in estimating the implied volatility of Bitcoin options. However, the Newton Raphson forecasting technique converges faster than does the Bisection method.

How fiduciary duty law incentivises investors to manage sustainability risks

The compatibility of Environmental, Social and Governance (ESG) risk management with the investment management requirements under the investors’ fiduciary duties (FD) figures among the key questions in today’s context of a rapid growth of sustainable investment strategies. Despite some legal developments, namely, in Europe, investors still have no clear answer to this question, which leaves them inert in the face of these new, unconventional types of risk. In our research, we explore the recent advancements in the EU and the US legal practice with the objective to establish to what extent the FD actually requires investors to consider ESG risks in their investment management decisions. Through analysis, we define a theoretical decision-making pattern for ESG risk management set by the current FD law as applied to investors and identify: 1) ESG risk materiality and 2) the effectiveness of ESG risk hedging as its fundamental elements. Then, we design a theoretical representation of ESG risk materiality under the FD legal constraints and identify that the current FD law binds investors to assimilate ESG risks to financial risks; thus, their management is required only if they are financially material for investments. We show that this principle equally applies to long-term ESG risks (like climate change); investors are incentivised to manage only those that are sufficiently financially material considering the applied hypothetical discount rate. Also, through the case study of a recent US ERISA ESOP lawsuit, we reveal that risk aversion towards probability to successfully hedge material ESG risks could impede efficient risk management by incentivising investors not to hedge a material ESG risk, i.e. to breach their FD.

Hedge effectiveness assesment in non-financial organizations: economic approach

The existing approaches to assessing the effectiveness of risk hedging with derivatives according to various criteria have been considered. As a result it was found that in economic literature it is not paid enough attention to the development of assessment methodology, which take into account the impact of risk hedging on the overall performance of the organization. In this regard, an economic approach to assessing the effectiveness of hedging has been proposed; it is based on the comparison two basic categories of the efficiency theory – the achieved effects and the associated costs. Within the framework of this approach the effects of hedging that affect the overallresult of the organization’s activities were proposed. Also the costs associated with hedging were systematized into external and internal. The essential content of the proposed economic approach is presented in comparison with other approaches, which contributes to understanding the criteria for assessment hedge effectiveness in each specific case. The application of the proposed economic approach in non-financial organizations will contribute to improving the quality of risk hedging by using performance assessment criteria that meet the current goals of the organization and the requirements of senior management.

Governance of Artificial Intelligence in Water and Wastewater Management: The Case Study of Japan

The integration of artificial intelligence into various aspects of daily life is developing at a rapid pace in Japan. Discussions to govern applications of artificial intelligence to the field of social infrastructure are also critical and need to match the rapid pace of development. However, the legal implications and risks of applying artificial intelligence to the management of lifelines such as drinking water supply and wastewater treatment have not yet been fully explored. This paper reviews the existing legislations and ongoing discussions on governance regarding applications of artificial intelligence to water and wastewater management. Based on the review, we discuss the ability of legislative frameworks in Japan to respond to the applications of artificial intelligence, as well as identifying potential gaps and challenges thereof, including access to accurate data, demarcation of rights and responsibilities, risk hedging and risk management, monitoring and evaluation, and handling of intellectual property rights. This paper concludes with key recommendations to national and local governments to support the application of artificial intelligence in the field of water and wastewater.