Copertina

Stock Volatility Prediction using Time Series and Deep Learning Approach

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chatterjee, Ananda, Bhowmick, Hrisav, Sen, Jaydip
Natura:	Preprint
Pubblicazione:	2022
Soggetti:	Computational Finance Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learning
di: Sen, Jaydip, et al.
Pubblicazione: (2024)

Transformer Based Time-Series Forecasting for Stock
di: Li, Shuozhe, et al.
Pubblicazione: (2025)

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
di: Wang, Shengkun, et al.
Pubblicazione: (2024)

A Dynamic Approach to Stock Price Prediction: Comparing RNN and Mixture of Experts Models Across Different Volatility Profiles
di: Vallarino, Diego
Pubblicazione: (2024)

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints
di: Manzi, Pablo Rodriguez
Pubblicazione: (2026)

AMA-LSTM: Pioneering Robust and Fair Financial Audio Analysis for Stock Volatility Prediction
di: Wang, Shengkun, et al.
Pubblicazione: (2024)

Understanding the Impact of News Articles on the Movement of Market Index: A Case on Nifty 50
di: Dasgupta, Subhasis, et al.
Pubblicazione: (2024)

An Advanced Ensemble Deep Learning Framework for Stock Price Prediction Using VAE, Transformer, and LSTM Model
di: Sarkar, Anindya, et al.
Pubblicazione: (2025)

Stock Price Prediction and Traditional Models: An Approach to Achieve Short-, Medium- and Long-Term Goals
di: Alamu, Opeyemi Sheu, et al.
Pubblicazione: (2024)

DeepSVM: Learning Stochastic Volatility Models with Physics-Informed Deep Operator Networks
di: Malandain, Kieran A., et al.
Pubblicazione: (2025)

Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction
di: Mehrabian, Ali, et al.
Pubblicazione: (2024)

Multimodal Stock Price Prediction: A Case Study of the Russian Securities Market
di: Khubiev, Kasymkhan, et al.
Pubblicazione: (2025)

Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach
di: Ni, Haowei, et al.
Pubblicazione: (2024)

A Stock Price Prediction Approach Based on Time Series Decomposition and Multi-Scale CNN using OHLCT Images
di: Pei, Zhiyuan, et al.
Pubblicazione: (2024)

DiffSTOCK: Probabilistic relational Stock Market Predictions using Diffusion Models
di: Daiya, Divyanshu, et al.
Pubblicazione: (2024)

Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data
di: Omranpour, Soroush, et al.
Pubblicazione: (2024)

DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting
di: Zhao, Lifan, et al.
Pubblicazione: (2023)

Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
di: Koa, Kelvin J. L., et al.
Pubblicazione: (2024)

Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting
di: Thwal, Chu Myaet, et al.
Pubblicazione: (2024)

GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets
di: Xu, Zeda, et al.
Pubblicazione: (2024)

MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU
di: Zhu, Peng, et al.
Pubblicazione: (2024)

Realized Volatility Forecasting for New Issues and Spin-Offs using Multi-Source Transfer Learning
di: Teller, Andreas, et al.
Pubblicazione: (2025)

Exploiting Supply Chain Interdependencies for Stock Return Prediction: A Full-State Graph Convolutional LSTM
di: Liu, Chang
Pubblicazione: (2023)

Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management
di: Zhao, Lei, et al.
Pubblicazione: (2025)

Mitigating Distribution Shift in Stock Price Data via Return-Volatility Normalization for Accurate Prediction
di: Lee, Hyunwoo, et al.
Pubblicazione: (2025)

Stock Type Prediction Model Based on Hierarchical Graph Neural Network
di: Yao, Jianhua, et al.
Pubblicazione: (2024)

A Deep Reinforcement Learning Approach to Automated Stock Trading, using xLSTM Networks
di: Sarlakifar, Faezeh, et al.
Pubblicazione: (2025)

A Hybrid Deep Learning Framework for Stock Price Prediction Considering the Investor Sentiment of Online Forum Enhanced by Popularity
di: Li, Huiyu, et al.
Pubblicazione: (2024)

Solving The Dynamic Volatility Fitting Problem: A Deep Reinforcement Learning Approach
di: Gnabeyeu, Emmanuel, et al.
Pubblicazione: (2024)

Deep Generative Modeling for Financial Time Series with Application in VaR: A Comparative Review
di: Ericson, Lars, et al.
Pubblicazione: (2024)

CausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction
di: Li, Shuqi, et al.
Pubblicazione: (2024)

Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval
di: Kandimalla, Eshwar Sai, et al.
Pubblicazione: (2026)

LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU
di: Zhu, Peng, et al.
Pubblicazione: (2024)

Multi-task Meta Label Correction for Time Series Prediction
di: Yang, Luxuan, et al.
Pubblicazione: (2023)

Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis
di: Cheng, Qishuo, et al.
Pubblicazione: (2024)

Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information
di: François, Pascal, et al.
Pubblicazione: (2024)

Reasoning on Time-Series for Financial Technical Analysis
di: Koa, Kelvin J. L., et al.
Pubblicazione: (2025)

Predicting Grain Growth in Polycrystalline Materials Using Deep Learning Time Series Models
di: Younes, Eliane, et al.
Pubblicazione: (2025)

Realised Volatility Forecasting: Machine Learning via Financial Word Embedding
di: Rahimikia, Eghbal, et al.
Pubblicazione: (2021)

Financial Fine-tuning a Large Time Series Model
di: Fu, Xinghong, et al.
Pubblicazione: (2024)