Carbon price forecasting based on CEEMDAN and LSTM
F Zhou, Z Huang, C Zhang - Applied energy, 2022 - Elsevier
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 …
has taken a significant step toward carbon neutrality. Carbon price forecasting is helpful to …
[HTML][HTML] Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?
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 …
institutional investors. Accurate Bitcoin price direction forecasts are important for determining …
Re-examining bitcoin volatility: a CAViaR-based approach
Z Li, H Dong, C Floros, A Charemis… - … Markets Finance and …, 2022 - Taylor & Francis
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 …
volatility using a Markov regime-switching model and test its forecasting ability. The …
Is there any difference in the impact of digital transformation on the quantity and efficiency of enterprise technological innovation? Taking China's agricultural listed …
H Liu, P Wang, Z Li - Sustainability, 2021 - mdpi.com
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 …
quantity and quality, which may show heterogeneity. In this regard, this paper uses the data …
A new hybrid machine learning model for predicting the bitcoin (BTC-USD) price
Several machine learning techniques and hybrid architectures for predicting bitcoin price
movement have been presented in the past. Our paper proposes a hybrid model …
movement have been presented in the past. Our paper proposes a hybrid model …
[PDF][PDF] Utilizing machine learning to reassess the predictability of bank stocks
H Antonopoulou… - Emerging Science …, 2023 - pdfs.semanticscholar.org
Objectives: Accurate prediction of stock market returns is a very challenging task due to the
volatile and non-linear nature of the financial stock markets. In this work, we consider …
volatile and non-linear nature of the financial stock markets. In this work, we consider …
Forecasting NFT coin prices using machine learning: Insights into feature significance and portfolio strategies
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 …
also surged. NFT coins are cryptocurrencies that facilitate NFT ecosystems by supporting …
[PDF][PDF] Forecasting crude oil price using LSTM neural networks
K Zhang, M Hong, K Zhang, M Hong - Data Sci. Financ. Econ, 2022 - aimspress.com
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 …
economic volatility, so forecasting crude oil price has always been a pivotal issue in …
Machine learning as a predictive technology and its impact on digital pricing and cryptocurrency markets
NC Sattaru, D Umrao… - 2022 2nd …, 2022 - ieeexplore.ieee.org
In this current era, Machine Learning (ML) Approach is widely used as a predictive
technology in transportation, finance, advertising, travel, healthcare, and various …
technology in transportation, finance, advertising, travel, healthcare, and various …
Dissecting the stock to flow model for Bitcoin
TG Morillon, RG Chacon - Studies in Economics and Finance, 2022 - emerald.com
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 …
flow (S2F) model. The model gained significant traction after successfully predicting the …