S&P 500

The S&P 500 is a stock market index that contains 500 of the largest publicly traded companies in the U.S. 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 · 3 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 · 378 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 citesThe use of scaling properties to detect relevant changes in financial time series: a new visual warning tool2020 · 24 citesFinancial Time Series Forecasting using CNN and Transformer2023 · 23 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