Meta-LSTR: Meta-Learning with Long Short-Term Transformer for futures volatility prediction

Y Chen, N Ye, W Zhang, J Fan, S Mumtaz… - Expert Systems with …, 2024 - Elsevier
Futures are essential instruments in financial markets. Accurately predicting futures volatility
is crucial for calculating value-at-risk and comprehensively assessing financial uncertainty …

[HTML][HTML] Can Bitcoin trigger speculative pressures on the US Dollar? A novel ARIMA-EGARCH-Wavelet Neural Networks

D Alaminos, MB Salas-Compás… - Physica A: Statistical …, 2024 - Elsevier
In recent years, Bitcoin has garnered attention as a digital currency, prompting increasing
debate regarding its effects on traditional financial markets, particularly the US dollar. This …

Assessing the risk spillover effects between the Chinese carbon market and the US-China energy market

J Yan, C Işık - Heliyon, 2025 - cell.com
Pollution caused by environmental problems has aggravated the problem of resource
scarcity, and the destruction of the ecological environment by mankind has shown serious …

The ripple effects of energy price volatility on equity and debt markets: a Morlet wavelet analysis

U Razi, CWH Cheong, S Afshan, A Sharif - Eurasian Economic Review, 2025 - Springer
This study investigates the significant yet complex relationship between financial market
dynamics and oil price volatility, using Morlet wavelet analysis across two distinct periods …

Prediction Stock Price of Shanghai Pudong Development Bank with ARIMA and ARCH/GARCH Models

IW Sunarya - Jurnal Aplikasi Manajemen, Ekonomi …, 2024 - jameb.stimlasharanjaya.ac.id
This research was conducted to predict stock prices from July 2024 to December 2024. The
stock chosen for prediction was Shanghai Pudong Development Bank. The ARIMA and …

Innovation in Financial Enterprise Risk Prediction Model: A Hybrid Deep Learning Technique Based on CNN-Transformer-WT

J Jin, Y Zhang - Journal of Organizational and End User Computing …, 2024 - igi-global.com
In the context of predicting financial risks for enterprises, traditional methods are inadequate
in capturing complex multidimensional data features, resulting in suboptimal prediction …

Enhancing Volatility Prediction: Comparison Study Between Persistent and Anti-persistent Financial Series.

Y Bakkali, MEL Merzguioui, A Akharif - Statistics, Optimization & …, 2024 - iapress.org
Predicting financial volatility is crucial for managing risks and making investment decisions.
This research introduces a novel method for creating a prediction model that effectively …

[PDF][PDF] Wavelet Based Financial Forecast Ensemble Featuring Hybrid Quantum-Classical LSTM Model

P Bigica, X Wang - WSEAS Transactions on Business and Economics, 2024 - wseas.com
One of the most sought-after goals in the financial world is a reliable method by which
investors can predict a stock price movement consistently. Advancements in stock prediction …

[PDF][PDF] ANALYSING THE IMPACT OF VOLATILITY DECAY ON FORECASTED RETURNS USING ARMA, SYMMETRIC AND ASYMMETRIC GARCH AND TGARCH …

A Agarwal, N Dhankhar - researchgate.net
In accordance with the general perception that the risk appetite of an investor determines his
reward, the discussion neglects the important issue of the impact of volatility. An informed …

[引用][C] THE ROLE OF NEURAL NETWORKS, WAVELET DECOMPOSITION AND GARCH MODELS IN OPTIMIZING VOLATILITY PREDICTIONS

TS Sahana, G Kumarapandiyan - Emerging Innovations and …, 2024 - Beyond Line Publisher