Abstract After signing the Paris Agreement and piloting carbon trading for many years, China
has taken a significant step toward carbon neutrality. Carbon price forecasting is helpful to …

Bitcoin has grown in popularity and has now attracted the attention of individual and
institutional investors. Accurate Bitcoin price direction forecasts are important for determining …

The article aims to explore the heterogeneous feature in the determination of Bitcoin
volatility using a Markov regime-switching model and test its forecasting ability. The …

The effect of digital transformation on enterprise technological innovation is reflected in
quantity and quality, which may show heterogeneity. In this regard, this paper uses the data …

Several machine learning techniques and hybrid architectures for predicting bitcoin price
movement have been presented in the past. Our paper proposes a hybrid model …

With the rise in popularity of Non-Fungible Tokens (NFTs), the demand for NFT coins has
also surged. NFT coins are cryptocurrencies that facilitate NFT ecosystems by supporting …

As a key input factor in industrial production, the price volatility of crude oil often brings about
economic volatility, so forecasting crude oil price has always been a pivotal issue in …

In this current era, Machine Learning (ML) Approach is widely used as a predictive
technology in transportation, finance, advertising, travel, healthcare, and various …

Purpose Perhaps the most popular pricing model among Bitcoin enthusiasts is the stock-to-
flow (S2F) model. The model gained significant traction after successfully predicting the …

Using NARDL methodology, this research investigates some asymmetric and non-linear
interconnections between leading cryptocurrency and commodity returns. Thus, this study …