On the public citation graph
Unraveling Asset Pricing with AI: A Systematic Literature Review
0 signed · 380 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/asi.20739openalex-snapshot
Evaluating a news‐aware quantitative trader: The effect of momentum and contrarian stock selection strategies
inferredcites →https://doi.org/10.1002/fut.20465openalex-snapshot
A Markov regime-switching ARMA approach for hedging stock indices
inferredcites →https://doi.org/10.1002/int.22495openalex-snapshot
Hybrid evolutionary intelligent system and hybrid time series econometric model for stock price forecasting
inferredcites →https://doi.org/10.1002/int.22950openalex-snapshot
Asset pricing via deep graph learning to incorporate heterogeneous predictors
inferredcites →https://doi.org/10.1002/jae.800openalex-snapshot
A forecast comparison of volatility models: does anything beat a GARCH(1,1)?
inferredcites →https://doi.org/10.1007/978-3-319-42297-8_42openalex-snapshot
Exploiting Twitter Moods to Boost Financial Trend Prediction Based on Deep Network Models
inferredcites →https://doi.org/10.1007/978-3-642-23091-2_24openalex-snapshot
Improving Stock Market Prediction by Integrating Both Market News and Stock Prices
inferredcites →https://doi.org/10.1007/s00500-019-03918-3openalex-snapshot
Exploration of stock index change prediction model based on the combination of principal component analysis and artificial neural network
inferredcites →https://doi.org/10.1007/s00500-020-04957-xopenalex-snapshot
Time series data analysis of stock price movement using machine learning techniques
inferredcites →https://doi.org/10.1007/s00500-021-06602-7openalex-snapshot
Short-term stock trends prediction based on sentiment analysis and machine learning
inferredcites →https://doi.org/10.1007/s10614-015-9492-9openalex-snapshot
Exploiting Financial News and Social Media Opinions for Stock Market Analysis using MCMC Bayesian Inference
inferredcites →https://doi.org/10.1007/s10614-021-10115-8openalex-snapshot
A New Strategy for Short-Term Stock Investment Using Bayesian Approach
inferredcites →https://doi.org/10.1007/s11042-016-3643-4openalex-snapshot
The role of social sentiment in stock markets: a view from joint effects of multiple information sources
inferredcites →https://doi.org/10.1007/s11042-022-13231-1openalex-snapshot
A graph neural network-based stock forecasting method utilizing multi-source heterogeneous data fusion
inferredcites →https://doi.org/10.1007/s12559-023-10125-8openalex-snapshot
Learning-Based Stock Trending Prediction by Incorporating Technical Indicators and Social Media Sentiment
inferredcites →https://doi.org/10.1007/s12652-020-01839-wopenalex-snapshot
Stock market prediction using machine learning classifiers and social media, news
inferredcites →https://doi.org/10.1016/0022-0531(76)90046-6openalex-snapshot
The arbitrage theory of capital asset pricing
inferredcites →https://doi.org/10.1016/0165-4101(89)90017-7openalex-snapshot
Financial statement analysis and the prediction of stock returns
inferredcites →https://doi.org/10.1016/0304-3932(82)90021-6openalex-snapshot
Inflation, real returns and capital investment
inferredcites →https://doi.org/10.1016/0304-405x(79)90016-3openalex-snapshot
An intertemporal asset pricing model with stochastic consumption and investment opportunities
inferredcites →https://doi.org/10.1016/0304-405x(81)90018-0openalex-snapshot
The relationship between return and market value of common stocks
inferredcites →https://doi.org/10.1016/0304-405x(86)90070-xopenalex-snapshot
Predicting returns in the stock and bond markets
inferredcites →https://doi.org/10.1016/0304-405x(87)90026-2openalex-snapshot
Expected stock returns and volatility
inferredcites →https://doi.org/10.1016/0304-405x(87)90041-9openalex-snapshot
Stock returns and inflation
inferredcites →https://doi.org/10.1016/0304-405x(87)90045-6openalex-snapshot
Stock Returns and the Term Structure
inferredcites →https://doi.org/10.1016/0304-405x(89)90095-0openalex-snapshot
Business conditions and expected returns on stocks and bonds
inferredcites →https://doi.org/10.1016/0304-405x(93)90023-5openalex-snapshot
Common risk factors in the returns on stocks and bonds
inferredcites →https://doi.org/10.1016/0304-405x(94)00801-7openalex-snapshot
Stock returns and volatility a firm-level analysis
inferredcites →https://doi.org/10.1016/0304-4076(86)90063-1openalex-snapshot
Generalized autoregressive conditional heteroskedasticity
inferredcites →https://doi.org/10.1016/j.asoc.2014.12.028openalex-snapshot
A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price
inferredcites →https://doi.org/10.1016/j.asoc.2017.09.029openalex-snapshot
Wavelet Neural Network Prediction Method of Stock Price Trend Based on Rough Set Attribute Reduction
inferredcites →https://doi.org/10.1016/j.asoc.2020.106205openalex-snapshot
An integrated framework of deep learning and knowledge graph for prediction of stock price trend: An application in Chinese stock exchange market
inferredcites →https://doi.org/10.1016/j.asoc.2021.107488openalex-snapshot
A seasonal-trend decomposition-based dendritic neuron model for financial time series prediction
inferredcites →https://doi.org/10.1016/j.asoc.2021.108106openalex-snapshot
Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework
inferredcites →https://doi.org/10.1016/j.asoc.2022.109132openalex-snapshot
Dynamic forecasting of the Shanghai Stock Exchange index movement using multiple types of investor sentiment
inferredcites →https://doi.org/10.1016/j.asoc.2022.109921openalex-snapshot
Deep Learning-based Integrated Framework for stock price movement prediction
inferredcites →https://doi.org/10.1016/j.asoc.2024.111469openalex-snapshot
Association mining based deep learning approach for financial time-series forecasting
inferredcites →https://doi.org/10.1016/j.cor.2004.03.015openalex-snapshot
A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market
inferredcites →https://doi.org/10.1016/j.dss.2012.03.001openalex-snapshot
Evaluating sentiment in financial news articles
inferredcites →https://doi.org/10.1016/j.dss.2012.12.028openalex-snapshot
The impact of social and conventional media on firm equity value: A sentiment analysis approach
inferredcites →https://doi.org/10.1016/j.dss.2013.02.006openalex-snapshot
Automated news reading: Stock price prediction based on financial news using context-capturing features
inferredcites →https://doi.org/10.1016/j.dss.2014.01.013openalex-snapshot
Media-aware quantitative trading based on public Web information
inferredcites →https://doi.org/10.1016/j.dss.2016.03.001openalex-snapshot
Forecasting movements of health-care stock prices based on different categories of news articles using multiple kernel learning
inferredcites →https://doi.org/10.1016/j.dss.2018.11.004openalex-snapshot
Financial news-based stock movement prediction using causality analysis of influence in the Korean stock market
inferredcites →https://doi.org/10.1016/j.econlet.2014.10.013openalex-snapshot
Profitability and investment factors for UK asset pricing models
inferredcites →https://doi.org/10.1016/j.ememar.2008.02.002openalex-snapshot
Market integration in developed and emerging markets: Evidence from the CAPM
inferredcites →https://doi.org/10.1016/j.engappai.2022.105626openalex-snapshot
Forecasting stock market for an efficient portfolio by combining XGBoost and Hilbert–Huang transform
inferredcites →https://doi.org/10.1016/j.engappai.2023.105843openalex-snapshot
Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets
inferredcites →https://doi.org/10.1016/j.engappai.2023.106038openalex-snapshot
Machine learning techniques for stock price prediction and graphic signal recognition
inferredcites →https://doi.org/10.1016/j.eswa.2004.12.004openalex-snapshot
Dynamic adaptive ensemble case-based reasoning: application to stock market prediction
inferredcites →https://doi.org/10.1016/j.eswa.2006.08.020openalex-snapshot
A TSK type fuzzy rule based system for stock price prediction
inferredcites →https://doi.org/10.1016/j.eswa.2007.09.034openalex-snapshot
A type-2 fuzzy rule-based expert system model for stock price analysis
inferredcites →https://doi.org/10.1016/j.eswa.2008.08.077openalex-snapshot
A neural network with a case based dynamic window for stock trading prediction
inferredcites →https://doi.org/10.1016/j.eswa.2008.10.065openalex-snapshot
A two-stage architecture for stock price forecasting by integrating self-organizing map and support vector regression
inferredcites →https://doi.org/10.1016/j.eswa.2010.03.012openalex-snapshot
Integrating independent component analysis-based denoising scheme with neural network for stock price prediction
inferredcites →https://doi.org/10.1016/j.eswa.2010.10.027openalex-snapshot
Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange
inferredcites →https://doi.org/10.1016/j.eswa.2011.02.068openalex-snapshot
Using artificial neural network models in stock market index prediction
inferredcites →https://doi.org/10.1016/j.eswa.2011.04.210openalex-snapshot
A hybrid procedure for stock price prediction by integrating self-organizing map and genetic programming
inferredcites →https://doi.org/10.1016/j.eswa.2012.02.162openalex-snapshot
Predicting published news effect in the Brazilian stock market
inferredcites →https://doi.org/10.1016/j.eswa.2014.07.040openalex-snapshot
Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques
inferredcites →https://doi.org/10.1016/j.eswa.2014.08.004openalex-snapshot
Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment
inferredcites →https://doi.org/10.1016/j.eswa.2014.12.049openalex-snapshot
A social-media-based approach to predicting stock comovement
inferredcites →https://doi.org/10.1016/j.eswa.2015.05.013openalex-snapshot
Evaluating multiple classifiers for stock price direction prediction
inferredcites →https://doi.org/10.1016/j.eswa.2015.07.052openalex-snapshot
Sentiment analysis on social media for stock movement prediction
inferredcites →https://doi.org/10.1016/j.eswa.2015.07.063openalex-snapshot
An intelligent short term stock trading fuzzy system for assisting investors in portfolio management
inferredcites →https://doi.org/10.1016/j.eswa.2015.08.023openalex-snapshot
Emotion space model for classifying opinions in stock message board
inferredcites →https://doi.org/10.1016/j.eswa.2016.12.036openalex-snapshot
The impact of microblogging data for stock market prediction: Using Twitter to predict returns, volatility, trading volume and survey sentiment indices
inferredcites →https://doi.org/10.1016/j.eswa.2017.02.041openalex-snapshot
Stock market one-day ahead movement prediction using disparate data sources
inferredcites →https://doi.org/10.1016/j.eswa.2018.07.065openalex-snapshot
EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction
inferredcites →https://doi.org/10.1016/j.eswa.2019.03.029openalex-snapshot
CNNpred: CNN-based stock market prediction using a diverse set of variables
inferredcites →https://doi.org/10.1016/j.eswa.2020.114332openalex-snapshot
Stock price prediction using deep learning and frequency decomposition
inferredcites →https://doi.org/10.1016/j.eswa.2020.114444openalex-snapshot
Forecasting daily stock trend using multi-filter feature selection and deep learning
inferredcites →https://doi.org/10.1016/j.eswa.2021.115019openalex-snapshot
A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction
inferredcites →https://doi.org/10.1016/j.eswa.2021.115470openalex-snapshot
Investment strategies applied to the Brazilian stock market: A methodology based on Sentiment Analysis with deep learning
inferredcites →https://doi.org/10.1016/j.eswa.2021.115537openalex-snapshot
Applications of deep learning in stock market prediction: Recent progress
inferredcites →https://doi.org/10.1016/j.eswa.2022.116886openalex-snapshot
Stock Ranking with Multi-Task Learning
inferredcites →https://doi.org/10.1016/j.eswa.2022.118581openalex-snapshot
A machine learning trading system for the stock market based on N-period Min-Max labeling using XGBoost
inferredcites →https://doi.org/10.1016/j.eswa.2022.119186openalex-snapshot
Evaluating the performance of ensemble classifiers in stock returns prediction using effective features
inferredcites →https://doi.org/10.1016/j.finmar.2016.02.001openalex-snapshot
Earnings news, expected earnings, and aggregate stock returns
inferredcites →https://doi.org/10.1016/j.frl.2021.102280openalex-snapshot
Forecasting directional movements of stock prices for intraday trading using LSTM and random forests
inferredcites →https://doi.org/10.1016/j.inffus.2023.102165openalex-snapshot
Quantitative stock portfolio optimization by multi-task learning risk and return
inferredcites →https://doi.org/10.1016/j.ins.2003.03.023openalex-snapshot
A hybrid genetic-neural architecture for stock indexes forecasting
inferredcites →https://doi.org/10.1016/j.ins.2006.08.002openalex-snapshot
Self-organizing learning array and its application to economic and financial problems
inferredcites →https://doi.org/10.1016/j.ins.2014.03.096openalex-snapshot
The effect of news and public mood on stock movements
inferredcites →https://doi.org/10.1016/j.ins.2014.12.031openalex-snapshot
A weighted LS-SVM based learning system for time series forecasting
inferredcites →https://doi.org/10.1016/j.ins.2020.12.068openalex-snapshot
A novel graph convolutional feature based convolutional neural network for stock trend prediction
inferredcites →https://doi.org/10.1016/j.ins.2022.02.015openalex-snapshot
An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices
inferredcites →https://doi.org/10.1016/j.ins.2022.11.013openalex-snapshot
FinHGNN: A conditional heterogeneous graph learning to address relational attributes for stock predictions
inferredcites →https://doi.org/10.1016/j.ins.2022.11.077openalex-snapshot
Multi-granularity stock prediction with sequential three-way decisions
inferredcites →https://doi.org/10.1016/j.ipm.2009.05.001openalex-snapshot
A quantitative stock prediction system based on financial news
inferredcites →https://doi.org/10.1016/j.ipm.2013.12.002openalex-snapshot
Evaluating and understanding text-based stock price prediction models
inferredcites →https://doi.org/10.1016/j.ipm.2020.102212openalex-snapshot
Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong
inferredcites →https://doi.org/10.1016/j.jbankfin.2011.02.018openalex-snapshot
Intraday jumps and US macroeconomic news announcements
inferredcites →https://doi.org/10.1016/j.jbankfin.2011.03.006openalex-snapshot
The effect of macroeconomic news on stock returns: New evidence from newspaper coverage
inferredcites →https://doi.org/10.1016/j.jbankfin.2016.01.004openalex-snapshot
When does the stock market listen to economic news? New evidence from copulas and news wires
inferredcites →https://doi.org/10.1016/j.jbankfin.2017.07.002openalex-snapshot
Intraday online investor sentiment and return patterns in the U.S. stock market
inferredcites →https://doi.org/10.1016/j.jbankfin.2018.09.016openalex-snapshot
The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility
inferredcites →https://doi.org/10.1016/j.jbankfin.2019.01.012openalex-snapshot
Does residual state ownership increase stock return volatility? Evidence from China's secondary privatization
inferredcites →https://doi.org/10.1016/j.jbankfin.2019.105628openalex-snapshot
Aggregate investor sentiment and stock return synchronicity
inferredcites →https://doi.org/10.1016/j.jbankfin.2020.105758openalex-snapshot
Corporate relationship spending and stock price crash risk: Evidence from China's anti-corruption campaign
inferredcites →https://doi.org/10.1016/j.jbankfin.2021.106064openalex-snapshot
The ordering of historical returns and the cross-section of subsequent returns
inferredcites →https://doi.org/10.1016/j.jbankfin.2021.106123openalex-snapshot
Liquidity and the cross-section of international stock returns
inferredcites →https://doi.org/10.1016/j.jeconom.2005.07.020openalex-snapshot
A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series
inferredcites →https://doi.org/10.1016/j.jeconom.2020.07.009openalex-snapshot
Autoencoder Asset Pricing Models
inferredcites →https://doi.org/10.1016/j.jempfin.2002.12.001openalex-snapshot
Investor sentiment and the near-term stock market
inferredcites →https://doi.org/10.1016/j.jempfin.2010.04.008openalex-snapshot
A network perspective of the stock market
inferredcites →https://doi.org/10.1016/j.jfds.2018.04.003openalex-snapshot
Stock price prediction using support vector regression on daily and up to the minute prices
inferredcites →https://doi.org/10.1016/j.jfineco.2005.09.009openalex-snapshot
Profitability, investment and average returns
inferredcites →https://doi.org/10.1016/j.jfineco.2006.01.003openalex-snapshot
Disagreement, tastes, and asset prices
inferredcites →https://doi.org/10.1016/j.jfineco.2011.02.013openalex-snapshot
Information aggregation around macroeconomic announcements: Revisions matter
inferredcites →https://doi.org/10.1016/j.jfineco.2014.10.010openalex-snapshot
A five-factor asset pricing model
inferredcites →https://doi.org/10.1016/j.jfineco.2018.05.011openalex-snapshot
Micro(structure) before macro? The predictive power of aggregate illiquidity for stock returns and economic activity
inferredcites →https://doi.org/10.1016/j.jfineco.2018.10.001openalex-snapshot
Manager sentiment and stock returns
inferredcites →https://doi.org/10.1016/j.jfineco.2018.11.008openalex-snapshot
Technological Links and Predictable Returns
inferredcites →https://doi.org/10.1016/j.jfineco.2018.11.009openalex-snapshot
How news and its context drive risk and returns around the world
inferredcites →https://doi.org/10.1016/j.jfineco.2019.09.012openalex-snapshot
Time-varying inflation risk and stock returns
inferredcites →https://doi.org/10.1016/j.jfineco.2019.10.007openalex-snapshot
Shared analyst coverage: Unifying momentum spillover effects
inferredcites →https://doi.org/10.1016/j.jfineco.2020.02.003openalex-snapshot
Mood beta and seasonalities in stock returns
inferredcites →https://doi.org/10.1016/j.jfineco.2020.12.012openalex-snapshot
Salience theory and stock prices: Empirical evidence
inferredcites →https://doi.org/10.1016/j.jfineco.2021.03.003openalex-snapshot
Internet searching and stock price crash risk: Evidence from a quasi-natural experiment
inferredcites →https://doi.org/10.1016/j.jfineco.2021.04.007openalex-snapshot
Factors and risk premia in individual international stock returns
inferredcites →https://doi.org/10.1016/j.jfineco.2021.08.002openalex-snapshot
News as sources of jumps in stock returns: Evidence from 21 million news articles for 9000 companies
inferredcites →https://doi.org/10.1016/j.jfineco.2021.08.014openalex-snapshot
Music Sentiment and Stock Returns Around the World
inferredcites →https://doi.org/10.1016/j.jfineco.2021.08.017openalex-snapshot
Machine learning in the Chinese stock market
inferredcites →https://doi.org/10.1016/j.jfineco.2021.10.010openalex-snapshot
Salience Theory and the Cross-Section of Stock Returns: International and Further Evidence
inferredcites →https://doi.org/10.1016/j.jfineco.2022.10.004openalex-snapshot
Presidential economic approval rating and the cross-section of stock returns
inferredcites →https://doi.org/10.1016/j.jmoneco.2020.03.016openalex-snapshot
Aggregate expected investment growth and stock market returns
inferredcites →https://doi.org/10.1016/j.jmoneco.2020.04.010openalex-snapshot
Do survey expectations of stock returns reflect risk adjustments?
inferredcites →https://doi.org/10.1016/j.jocs.2010.12.007openalex-snapshot
Twitter mood predicts the stock market
inferredcites →https://doi.org/10.1016/j.knosys.2010.05.004openalex-snapshot
Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting
inferredcites →https://doi.org/10.1016/j.knosys.2010.11.001openalex-snapshot
Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm
inferredcites →https://doi.org/10.1016/j.knosys.2013.10.012openalex-snapshot
Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting
inferredcites →https://doi.org/10.1016/j.knosys.2014.04.022openalex-snapshot
News impact on stock price return via sentiment analysis
inferredcites →https://doi.org/10.1016/j.knosys.2017.01.033openalex-snapshot
A multiple support vector machine approach to stock index forecasting with mixed frequency sampling
inferredcites →https://doi.org/10.1016/j.knosys.2018.01.016openalex-snapshot
Using Twitter trust network for stock market analysis
inferredcites →https://doi.org/10.1016/j.knosys.2018.10.035openalex-snapshot
Aggregating multiple types of complex data in stock market prediction: A model-independent framework
inferredcites →https://doi.org/10.1016/j.knosys.2021.107119openalex-snapshot
Technical analysis strategy optimization using a machine learning approach in stock market indices
inferredcites →https://doi.org/10.1016/j.knosys.2021.107478openalex-snapshot
Natural visibility encoding for time series and its application in stock trend prediction
inferredcites →https://doi.org/10.1016/j.knosys.2022.109358openalex-snapshot
Construction of stock portfolios based on k-means clustering of continuous trend features
inferredcites →https://doi.org/10.1016/j.knosys.2022.110211openalex-snapshot
Deep reinforcement learning based on transformer and U-Net framework for stock trading
inferredcites →https://doi.org/10.1016/j.knosys.2023.110262openalex-snapshot
Essential tensor learning for multimodal information-driven stock movement prediction
inferredcites →https://doi.org/10.1016/j.najef.2018.06.013openalex-snapshot
Predicting the direction of stock market prices using tree-based classifiers
inferredcites →https://doi.org/10.1016/j.neucom.2011.12.013openalex-snapshot
A novel text mining approach to financial time series forecasting
inferredcites →https://doi.org/10.1016/j.omega.2004.07.024openalex-snapshot
A hybrid ARIMA and support vector machines model in stock price forecasting
inferredcites →https://doi.org/10.1016/j.pacfin.2013.02.003openalex-snapshot
An analysis of the impact of media coverage on stock price crashes and jumps: Evidence from Japan
inferredcites →https://doi.org/10.1016/j.pacfin.2017.09.002openalex-snapshot
Stock return anomalies and individual investors in the Korean stock market
inferredcites →https://doi.org/10.1016/j.pacfin.2020.101267openalex-snapshot
Stock return predictability from a mixed model perspective
inferredcites →https://doi.org/10.1016/j.pacfin.2021.101535openalex-snapshot
Do factor models explain stock returns when prices behave explosively? Evidence from China
inferredcites →https://doi.org/10.1016/j.patcog.2021.108209openalex-snapshot
Graph-based stock correlation and prediction for high-frequency trading systems
inferredcites →https://doi.org/10.1016/j.sbspro.2011.10.562openalex-snapshot
Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”
inferredcites →https://doi.org/10.1016/s0304-405x(03)00146-6openalex-snapshot
Stock price reaction to news and no-news: drift and reversal after headlines
inferredcites →https://doi.org/10.1016/s0304-405x(97)00002-0openalex-snapshot
Book-to-market, dividend yield, and expected market returns: A time-series analysis
inferredcites →https://doi.org/10.1016/s0304-405x(98)00020-8openalex-snapshot
Book-to-market ratios as predictors of market returns
inferredcites →https://doi.org/10.1016/s0305-0548(02)00037-0openalex-snapshot
Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index
inferredcites →https://doi.org/10.1016/s0927-538x(01)00020-8openalex-snapshot
Selecting macroeconomic variables as explanatory factors of emerging stock market returns
inferredcites →https://doi.org/10.1016/s0957-4174(00)00027-0openalex-snapshot
Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index
inferredcites →https://doi.org/10.1016/s0957-4174(01)00047-1openalex-snapshot
Predicting stock price using fuzzy grey prediction system
inferredcites →https://doi.org/10.1016/s0957-4174(01)00058-6openalex-snapshot
Analyzing stock market tick data using piecewise nonlinear model
inferredcites →https://doi.org/10.1016/s1049-0078(01)00111-7openalex-snapshot
Stock market and macroeconomic fundamental dynamic interactions: ASEAN-5 countries
inferredcites →https://doi.org/10.1016/s1566-0141(02)00042-0openalex-snapshot
Systematic risk in emerging markets: the D-CAPM
inferredcites →https://doi.org/10.1023/a:1008768404046openalex-snapshot
Genetic Programming Prediction of Stock Prices
inferredcites →https://doi.org/10.1038/srep01684openalex-snapshot
Quantifying Trading Behavior in Financial Markets Using Google Trends
inferredcites →https://doi.org/10.1038/srep01801openalex-snapshot
Quantifying Wikipedia Usage Patterns Before Stock Market Moves
inferredcites →https://doi.org/10.1038/srep03578openalex-snapshot
Quantifying the Relationship Between Financial News and the Stock Market
inferredcites →https://doi.org/10.1038/srep03711openalex-snapshot
Trading Network Predicts Stock Price
inferredcites →https://doi.org/10.1038/srep04213openalex-snapshot
When Can Social Media Lead Financial Markets?
inferredcites →https://doi.org/10.1080/0015198x.2021.1963186openalex-snapshot
ESG Rating Disagreement and Stock Returns
inferredcites →https://doi.org/10.1080/07408170600897486openalex-snapshot
Kernel principal component analysis and support vector machines for stock price prediction
inferredcites →https://doi.org/10.1080/09603100701748956openalex-snapshot
Can macroeconomic variables explain long-term stock market movements? A comparison of the US and Japan
inferredcites →https://doi.org/10.1080/14697688.2012.672762openalex-snapshot
Predicting abnormal returns from news using text classification
inferredcites →https://doi.org/10.1080/14697688.2014.931593openalex-snapshot
How news affects the trading behaviour of different categories of investors in a financial market
inferredcites →https://doi.org/10.1080/14697688.2015.1071078openalex-snapshot
Twitter financial community sentiment and its predictive relationship to stock market movement
inferredcites →https://doi.org/10.1080/14697688.2020.1720276openalex-snapshot
Slow-moving capital and stock returns
inferredcites →https://doi.org/10.1080/1540496x.2019.1695597openalex-snapshot
Media-based Corporate Network and Its Effects on Stock Market
inferredcites →https://doi.org/10.1086/209638openalex-snapshot
Forecasting Profitability and Earnings
inferredcites →https://doi.org/10.1086/260061openalex-snapshot
Risk, Return, and Equilibrium: Empirical Tests
inferredcites →https://doi.org/10.1086/261703openalex-snapshot
Noise Trader Risk in Financial Markets
inferredcites →https://doi.org/10.1086/323282openalex-snapshot
Resurrecting the (C)CAPM: A Cross‐Sectional Test When Risk Premia Are Time‐Varying
inferredcites →https://doi.org/10.1086/592415openalex-snapshot
The Small World of Investing: Board Connections and Mutual Fund Returns
inferredcites →https://doi.org/10.1093/qje/qjaa009openalex-snapshot
Financial Market Risk Perceptions and the Macroeconomy*
inferredcites →https://doi.org/10.1093/rapstu/raac013openalex-snapshot
Why Do Predicted Stock Issuers Earn Low Returns?
inferredcites →https://doi.org/10.1093/rfs/2.2.225openalex-snapshot
Mean Reversion in Short-Horizon Expected Returns
inferredcites →https://doi.org/10.1093/rfs/5.3.351openalex-snapshot
Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement
inferredcites →https://doi.org/10.1093/rfs/hhaa009openalex-snapshot
Empirical Asset Pricing via Machine Learning
inferredcites →https://doi.org/10.1093/rfs/hhaa020openalex-snapshot
Factors That Fit the Time Series and Cross-Section of Stock Returns
inferredcites →https://doi.org/10.1093/rfs/hhaa065openalex-snapshot
Uncertainty, Investor Sentiment, and Innovation
inferredcites →https://doi.org/10.1093/rfs/hhaa080openalex-snapshot
Illiquidity and Stock Returns II: Cross-Section and Time-Series Effects
inferredcites →https://doi.org/10.1093/rfs/hhaa105openalex-snapshot
Information Dispersion Across Employees and Stock Returns
inferredcites →https://doi.org/10.1093/rfs/hhab045openalex-snapshot
Asset Price Dynamics with Limited Attention
inferredcites →https://doi.org/10.1093/rfs/hhab137openalex-snapshot
What Moves Stock Prices? The Roles of News, Noise, and Information
inferredcites →https://doi.org/10.1093/rfs/hhad042openalex-snapshot
Narrative Asset Pricing: Interpretable Systematic Risk Factors from News Text
inferredcites →https://doi.org/10.1093/rfs/hhl021openalex-snapshot
Stock Return Predictability: Is it There?
inferredcites →https://doi.org/10.1093/rfs/hhm014openalex-snapshot
A Comprehensive Look at The Empirical Performance of Equity Premium Prediction
inferredcites →https://doi.org/10.1093/rfs/hhm055openalex-snapshot
Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?
inferredcites →https://doi.org/10.1093/rfs/hhq052openalex-snapshot
Does Public Financial News Resolve Asymmetric Information?
showing the first 200 of 380 · page through all 380
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.