S&P 500

The S&P 500 is a stock market index that contains 500 of the largest publicly traded companies in the United States and is used to evaluate the overall performance of the U.S. stock market.

Papers using S&P 500 (36)

Forecasting S&P 500 Using LSTM Models2025 · 8 citesTimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting2024 · 4 citesIntroducing shrinkage in heavy-tailed state space models to predict equity excess returns2018 · 2 citesSBBTS: A Unified Schr\"odinger-Bass Framework for Synthetic Financial Time Series2026Financial time series augmentation using transformer based GAN architecture2026A Neuro-Fuzzy System for Interpretable Long-Term Stock Market Forecasting2025Improving S&P 500 Volatility Forecasting through Regime-Switching Methods2025Long-Range Dependence in Financial Markets: Empirical Evidence and Generative Modeling Challenges2025Dependency Network-Based Portfolio Design with Forecasting and VaR Constraints2025Conditional Time Series Forecasting with Convolutional Neural Networks2017 · 379 citesFinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks2021 · 76 citesImpact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory2020 · 72 citesFinancial Time Series Forecasting using CNN and Transformer2023 · 25 citesThe use of scaling properties to detect relevant changes in financial time series: a new visual warning tool2020 · 24 citesS&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data2021 · 18 citesForecasting Large Realized Covariance Matrices: The Benefits of Factor Models and Shrinkage2023 · 9 citesDeep Learning Based on Generative Adversarial and Convolutional Neural Networks for Financial Time Series Predictions2020 · 7 citesStock2Vec: A Hybrid Deep Learning Framework for Stock Market Prediction with Representation Learning and Temporal Convolutional Network2020 · 6 citesMultivariate Realized Volatility Forecasting with Graph Neural Network2021 · 4 citesForecasting in Non-stationary Environments with Fuzzy Time Series2020 · 3 citesShort-Term Stock Price-Trend Prediction Using Meta-Learning2021 · 3 citesEnhanced forecasting of stock prices based on variational mode decomposition, PatchTST, and adaptive scale-weighted layer2024 · 3 citesForecasting the Performance of US Stock Market Indices During COVID-19: RF vs LSTM2023 · 2 citesComparing Deep Learning Models for the Task of Volatility Prediction Using Multivariate Data2023 · 2 citesMegazordNet: combining statistical and machine learning standpoints for time series forecasting2021 · 1 citesDynamic and Context-Dependent Stock Price Prediction Using Attention Modules and News Sentiment2022 · 1 citesVolatility forecasting using Deep Learning and sentiment analysis2022 · 1 citesA Statistical Recurrent Stochastic Volatility Model for Stock Markets2019Forecasting volatility with a stacked model based on a hybridized Artificial Neural Network2020Unraveling S&P500 stock volatility and networks -- An encoding-and-decoding approach2021Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network2022Time Series Analysis in American Stock Market Recovering in Post COVID-19 Pandemic Period20221D-CapsNet-LSTM: A Deep Learning-Based Model for Multi-Step Stock Index Forecasting2023Forecasting and Analysis of CSI 300 Daily Index and S&P 500 Index Based on ARMA and GARCH Models2023Dynamical analysis of financial stocks network: improving forecasting using network properties2024From Votes to Volatility Predicting the Stock Market on Election Day2024