Cover Image

Stochastic Volatility Modelling with LSTM Networks: A Hybrid Approach for S&P 500 Index Volatility Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Perekhodko, Anna, Ślepaczuk, Robert
Format:	Preprint
Published:	2025
Subjects:	Trading and Market Microstructure Artificial Intelligence Machine Learning Neural and Evolutionary Computing Portfolio Management
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models
by: Roszyk, Natalia, et al.
Published: (2024)

Deep Reinforcement Learning Framework for Diversified Portfolio Management Across Global Equity Markets
by: Kashif, Kamil, et al.
Published: (2026)

Informer in Algorithmic Investment Strategies on High Frequency Bitcoin Data
by: Stefaniuk, Filip, et al.
Published: (2025)

Construction and Hedging of Equity Index Options Portfolios
by: Wysocki, Maciej, et al.
Published: (2024)

Overreaction as an indicator for momentum in algorithmic trading: A Case of AAPL stocks
by: Lis, Szymon, et al.
Published: (2026)

Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market
by: Korniejczuk, Adam, et al.
Published: (2024)

A novel approach to trading strategy parameter optimization using double out-of-sample data and walk-forward techniques
by: Mroziewicz, Tomasz, et al.
Published: (2026)

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models
by: Kvasiuk, Yurii, et al.
Published: (2026)

Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model
by: Kurth, Jutta G., et al.
Published: (2025)

Do Mutual Funds Make Active and Skilled Liquidity Choices in Portfolio Management? Evidence from India
by: Agarwal, Pankaj K, et al.
Published: (2025)

Refining and Robust Backtesting of A Century of Profitable Industry Trends
by: Massaad, Alessandro, et al.
Published: (2024)

Pools as Portfolios: Observed arbitrage efficiency & LVR analysis of dynamic weight AMMs
by: Willetts, Matthew, et al.
Published: (2026)

Generating realistic metaorders from public data
by: Maitrier, Guillaume, et al.
Published: (2025)

Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets
by: Lu, Yutong, et al.
Published: (2023)

Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
by: Wood, Kieran, et al.
Published: (2023)

Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models
by: Herremans, Dorien, et al.
Published: (2022)

Trade execution games in a Markovian environment
by: Ohnishi, Masamitsu, et al.
Published: (2024)

A Practical Machine Learning Approach for Dynamic Stock Recommendation
by: Yang, Hongyang, et al.
Published: (2025)

Sizing the Risk: Kelly, VIX, and Hybrid Approaches in Put-Writing on Index Options
by: Wysocki, Maciej
Published: (2025)

Deep Learning for Options Trading: An End-To-End Approach
by: Tan, Wee Ling, et al.
Published: (2024)

LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies
by: Kashif, Kamil, et al.
Published: (2024)

Building Trust in Illiquid Markets: an AI-Powered Replication of Private Equity Funds
by: Benhamou, E., et al.
Published: (2025)

Autonomous Market Intelligence: Agentic AI Nowcasting Predicts Stock Returns
by: Chen, Zefeng, et al.
Published: (2026)

From Hypotheses to Factors: Constrained LLM Agents in Cryptocurrency Markets
by: Huang, Yikuan, et al.
Published: (2026)

Bimodal Dynamics of the Artificial Limit Order Book Stock Exchange with Autonomous Traders
by: Steinbacher, Matej, et al.
Published: (2025)

Kernel Learning for Mean-Variance Trading Strategies
by: Futter, Owen, et al.
Published: (2025)

Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy
by: Yang, Hongyang, et al.
Published: (2025)

The Random Forest Model for Analyzing and Forecasting the US Stock Market in the Context of Smart Finance
by: Zheng, Jiajian, et al.
Published: (2024)

Discovery of a 13-Sharpe OOS Factor: Drift Regimes Unlock Hidden Cross-Sectional Predictability
by: Singha, Mainak
Published: (2025)

Crisis Alpha: A High-Performance Trading Algorithm Tested in Market Downturns
by: Gharanchaei, Maysam Khodayari, et al.
Published: (2024)

Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models
by: Stempień, Dominik, et al.
Published: (2025)

Revisiting the Structure of Trend Premia: When Diversification Hides Redundancy
by: Etienne, Alban, et al.
Published: (2025)

Sentiment trading with large language models
by: Kirtac, Kemal, et al.
Published: (2024)

Forecasting S&P 500 Using LSTM Models
by: Pilla, Prashant, et al.
Published: (2025)

Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches
by: Chinazzo, Cristina, et al.
Published: (2024)

Forecast-to-Fill: Benchmark-Neutral Alpha and Billion-Dollar Capacity in Gold Futures (2015-2025)
by: Singha, Mainak, et al.
Published: (2025)

Mislearning of Factor Risk Premia under Structural Breaks: A Misspecified Bayesian Learning Framework
by: Qiu, Yimeng
Published: (2026)

Supervised Autoencoder MLP for Financial Time Series Forecasting
by: Bieganowski, Bartosz, et al.
Published: (2024)

Fast Times, Slow Times: Timescale Separation in Financial Timeseries Data
by: Rosenzweig, Jan
Published: (2026)

Optimal bidding in hourly and quarter-hourly electricity price auctions: trading large volumes of power with market impact and transaction costs
by: Narajewski, Michał, et al.
Published: (2021)