This work looks for the optimal allocation of different assets, namely, the G7 stock indices, commodities (gold and WTI crude oil), cryptocurrencies (Bitcoin and Ripple), and S&P Green Bond, over four periods: before the COVID-19 crisis, during the COVID-19 crisis and before the Russia-Ukraine...

Machine learning (ML) plays a crucial role in big data (BD) by serving as the cornerstone of efficient data processing and analysis. In particular, ML provides BD with the ability to extract valuable insights from the large data sets. Therefore, this study conducted a scoping survey to define...

Purpose: The objective of this work is to fulfil a strategic requirement in Egypt’s agriculture industry by establishing a fresh produce supply chain network (SCN) that manages the collection, processing, packaging, and distribution of products. Design/methodology/approach: A two-phase...

Purpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms, which makes them an essential tool when working with large datasets. However, although they are unsupervised tools, they generally require the specification of the number of...

Modeling implied volatility (IV) is important for option pricing, hedging, and risk management. Previous studies of deterministic implied volatility functions (DIVFs) propose two parameters, moneyness and time to maturity, to estimate implied volatility. Recent DIVF models have included factors...