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Forecasting earnings and returns: A review of recent advancements
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Density forecasting in economics and finance
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Removing predictable analyst forecast errors to improve implied cost of equity estimates
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The Supraview of Return Predictive Signals
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Evaluating cross-sectional forecasting models for implied cost of capital
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Linear valuation without OLS: the Theil-Sen estimation approach
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Do Excessively Volatile Forecasts Impact Investors?
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Earnings forecasts: the case for combining analysts’ estimates with a cross-sectional model
inferredcites →https://doi.org/10.1007/s11156-022-01099-zopenalex-snapshot
Enhancing stock market anomalies with machine learning
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Machine learning in empirical asset pricing
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Financial statement analysis and the prediction of stock returns
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Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics
inferredcites →https://doi.org/10.1016/j.finmar.2020.100588openalex-snapshot
Does it pay to follow anomalies research? Machine learning approach with international evidence
inferredcites →https://doi.org/10.1016/j.ijforecast.2019.05.007openalex-snapshot
Forecasting of density functions with an application to cross-sectional and intraday returns
inferredcites →https://doi.org/10.1016/j.ijforecast.2021.11.001openalex-snapshot
Forecasting: theory and practice
inferredcites →https://doi.org/10.1016/j.jacceco.2008.09.005openalex-snapshot
Earnings volatility and earnings predictability
inferredcites →https://doi.org/10.1016/j.jacceco.2010.09.008openalex-snapshot
Accounting anomalies and fundamental analysis: A review of recent research advances
inferredcites →https://doi.org/10.1016/j.jacceco.2019.101238openalex-snapshot
Earnings Acceleration and Stock Returns
inferredcites →https://doi.org/10.1016/j.jbankfin.2015.03.006openalex-snapshot
What explains the dynamics of 100 anomalies?
inferredcites →https://doi.org/10.1016/j.jbankfin.2016.04.025openalex-snapshot
Stock returns and future tense language in 10-K reports
inferredcites →https://doi.org/10.1016/j.jbankfin.2020.105966openalex-snapshot
Where have the profits gone? Market efficiency and the disappearing equity anomalies in country and industry returns
inferredcites →https://doi.org/10.1016/j.jeconom.2013.04.017openalex-snapshot
Complete subset regressions
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Autoencoder Asset Pricing Models
inferredcites →https://doi.org/10.1016/j.jfds.2017.02.001openalex-snapshot
Textual analysis and machine leaning: Crack unstructured data in finance and accounting
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Stock price prediction using support vector regression on daily and up to the minute prices
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FinLex: An effective use of word embeddings for financial lexicon generation
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Persistence in factor-based supervised learning models
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The short of it: Investor sentiment and anomalies
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The long of it: Odds that investor sentiment spuriously predicts anomaly returns
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Forecasting stock returns under economic constraints
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Deflating profitability
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Does realized skewness predict the cross-section of equity returns?
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Accruals, cash flows, and operating profitability in the cross section of stock returns
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Day of the Week and the Cross-Section of Returns
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Characteristics are covariances: A unified model of risk and return
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Anomalies across the globe: Once public, no longer existent?
inferredcites →https://doi.org/10.1016/j.jfineco.2019.06.008openalex-snapshot
Shrinking the cross-section
inferredcites →https://doi.org/10.1016/j.jfineco.2020.03.006openalex-snapshot
Does the Ross recovery theorem work empirically?
inferredcites →https://doi.org/10.1016/j.jfineco.2020.12.003openalex-snapshot
Estimating the anomaly base rate
inferredcites →https://doi.org/10.1016/j.jfineco.2021.05.014openalex-snapshot
Expected return, volume, and mispricing
inferredcites →https://doi.org/10.1016/j.jfineco.2021.06.002openalex-snapshot
A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news
inferredcites →https://doi.org/10.1016/j.jfineco.2021.08.008openalex-snapshot
The level, slope, and curve factor model for stocks
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Have risk premia vanished?
inferredcites →https://doi.org/10.1016/s0165-4101(98)00002-0openalex-snapshot
Market assessment of industry and firm earnings information
inferredcites →https://doi.org/10.1017/s0022109022001028openalex-snapshot
Uncovering Sparsity and Heterogeneity in Firm-Level Return Predictability Using Machine Learning
inferredcites →https://doi.org/10.1023/a:1011338221623openalex-snapshot
Ratio Analysis and Equity Valuation: From Research to Practice
inferredcites →https://doi.org/10.1080/1351847042000255652openalex-snapshot
Evaluating density forecasts from models of stock market returns
inferredcites →https://doi.org/10.1080/13518470802042369openalex-snapshot
Return forecasts and optimal portfolio construction: a quantile regression approach
inferredcites →https://doi.org/10.1080/14697688.2012.672762openalex-snapshot
Predicting abnormal returns from news using text classification
inferredcites →https://doi.org/10.1086/260061openalex-snapshot
Risk, Return, and Equilibrium: Empirical Tests
inferredcites →https://doi.org/10.1093/jjfinec/nbn001openalex-snapshot
Estimating Value at Risk and Expected Shortfall Using Expectiles
inferredcites →https://doi.org/10.1093/jjfinec/nbz002openalex-snapshot
An Empirical Implementation of the Ross Recovery Theorem as a Prediction Device
inferredcites →https://doi.org/10.1093/rfs/hhaa009openalex-snapshot
Empirical Asset Pricing via Machine Learning
inferredcites →https://doi.org/10.1093/rfs/hhaa019openalex-snapshot
New Methods for the Cross-Section of Returns
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/hhm055openalex-snapshot
Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?
inferredcites →https://doi.org/10.1093/rfs/hhp003openalex-snapshot
Parametric Portfolio Policies: Exploiting Characteristics in the Cross-Section of Equity Returns
inferredcites →https://doi.org/10.1093/rfs/hhv059openalex-snapshot
Editor's Choice … and the Cross-Section of Expected Returns
inferredcites →https://doi.org/10.1093/rfs/hhw102openalex-snapshot
Aggregation of Information About the Cross Section of Stock Returns: A Latent Variable Approach
inferredcites →https://doi.org/10.1093/rfs/hhx019openalex-snapshot
The Characteristics that Provide Independent Information about Average U.S. Monthly Stock Returns
inferredcites →https://doi.org/10.1093/rfs/hhz085openalex-snapshot
A Transaction-Cost Perspective on the Multitude of Firm Characteristics
inferredcites →https://doi.org/10.1093/rfs/hhz123openalex-snapshot
Dissecting Characteristics Nonparametrically
inferredcites →https://doi.org/10.1111/1475-679x.12070openalex-snapshot
Unsophisticated Arbitrageurs and Market Efficiency: Overreacting to a History of Underreaction?
inferredcites →https://doi.org/10.1111/1475-679x.12121openalex-snapshot
The Value of Crowdsourced Earnings Forecasts
inferredcites →https://doi.org/10.1111/1475-679x.12123openalex-snapshot
Textual Analysis in Accounting and Finance: A Survey
inferredcites →https://doi.org/10.1111/1475-679x.12160openalex-snapshot
Do Weather-Induced Moods Affect the Processing of Earnings News?
inferredcites →https://doi.org/10.1111/1911-3846.12307openalex-snapshot
An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts
inferredcites →https://doi.org/10.1111/1911-3846.12314openalex-snapshot
Aggregate Margin Debt and the Divergence of Price from Accounting Fundamentals
inferredcites →https://doi.org/10.1111/1911-3846.12491openalex-snapshot
Investor Overreaction to Earnings Surprises and Post-Earnings-Announcement Reversals
inferredcites →https://doi.org/10.1111/abac.12064openalex-snapshot
Review of Recent Research on Improving Earnings Forecasts and Evaluating Accounting-Based Estimates of the Expected Rate of Return on Equity Capital
inferredcites →https://doi.org/10.1111/eufm.12290openalex-snapshot
Time‐series and cross‐sectional momentum in anomaly returns
inferredcites →https://doi.org/10.1111/j.1475-679x.2008.00313.xopenalex-snapshot
Do Industry‐Level Analyses Improve Forecasts of Financial Performance?
inferredcites →https://doi.org/10.1111/j.1540-6261.1985.tb05004.xopenalex-snapshot
Does the Stock Market Overreact?
inferredcites →https://doi.org/10.1111/j.1540-6261.1987.tb04569.xopenalex-snapshot
Further Evidence On Investor Overreaction and Stock Market Seasonality
inferredcites →https://doi.org/10.1111/j.1540-6261.1988.tb04598.xopenalex-snapshot
Stock Prices, Earnings and Expected Dividends
inferredcites →https://doi.org/10.1111/j.1540-6261.2008.01370.xopenalex-snapshot
Asset Growth and the Cross‐Section of Stock Returns
inferredcites →https://doi.org/10.1111/j.1540-6261.2011.01671.xopenalex-snapshot
Presidential Address: Discount Rates
inferredcites →https://doi.org/10.1111/jofi.12365openalex-snapshot
Does Academic Research Destroy Stock Return Predictability?
inferredcites →https://doi.org/10.1111/jofi.13477openalex-snapshot
Forest through the Trees: Building Cross‐Sections of Stock Returns
inferredcites →https://doi.org/10.1126/science.235.4784.33openalex-snapshot
The Volatility of Stock Market Prices
inferredcites →https://doi.org/10.1126/science.243.4896.1313openalex-snapshot
Is the Stock Market Efficient?
inferredcites →https://doi.org/10.1146/annurev-economics-063016-103651openalex-snapshot
Quantile Regression: 40 Years On
inferredcites →https://doi.org/10.1146/annurev-financial-110217-022713openalex-snapshot
Forecasting Methods in Finance
inferredcites →https://doi.org/10.1177/0148558x17722919openalex-snapshot
Using MD&A to Improve Earnings Forecasts
inferredcites →https://doi.org/10.1198/jbes.2010.07318openalex-snapshot
Evaluating Value-at-Risk Models via Quantile Regression
inferredcites →https://doi.org/10.12785/ijcds/100193openalex-snapshot
Boosting Algorithms to Analyse Firm’s Performance Based on Return on Equity: An Explanatory Study
inferredcites →https://doi.org/10.1287/mnsc.1080.0986openalex-snapshot
A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms
inferredcites →https://doi.org/10.1287/mnsc.2020.3694openalex-snapshot
Tail-Heaviness, Asymmetry, and Profitability Forecasting by Quantile Regression
inferredcites →https://doi.org/10.1287/mnsc.2023.4966openalex-snapshot
Optimal Cross-Sectional Regression
inferredcites →https://doi.org/10.1561/104.00000024openalex-snapshot
The Cross-section of Expected Stock Returns
inferredcites →https://doi.org/10.1561/1400000036openalex-snapshot
Financial Statement Analysis and Earnings Forecasting
inferredcites →https://doi.org/10.17016/feds.2020.039openalex-snapshot
Zeroing in on the Expected Returns of Anomalies
inferredcites →https://doi.org/10.2139/ssrn.2112137openalex-snapshot
Regression-Based Earnings Forecasts
inferredcites →https://doi.org/10.2139/ssrn.3205697openalex-snapshot
Shrinking Factor Dimension: A Reduced-Rank Approach
inferredcites →https://doi.org/10.2139/ssrn.3388293openalex-snapshot
Predicting Returns With Text Data
inferredcites →https://doi.org/10.2139/ssrn.3438754openalex-snapshot
What Matters When? Time-Varying Sparsity in Expected Returns
inferredcites →https://doi.org/10.2139/ssrn.3450322openalex-snapshot
Machine Learning Versus Economic Restrictions: Evidence from Stock Return Predictability
inferredcites →https://doi.org/10.2139/ssrn.3466478openalex-snapshot
Predicting Profitability Using Machine Learning
inferredcites →https://doi.org/10.2139/ssrn.3489679openalex-snapshot
Alpha Go Everywhere: Machine Learning and International Stock Returns
inferredcites →https://doi.org/10.2139/ssrn.3545886openalex-snapshot
Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective
inferredcites →https://doi.org/10.2139/ssrn.3557957openalex-snapshot
Subsampled Factor Models for Asset Pricing: The Rise of Vasa
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Man vs. Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases
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Machine Learning and Return Predictability Across Firms, Time and Portfolios
inferredcites →https://doi.org/10.2139/ssrn.3706532openalex-snapshot
Fundamental Analysis Via Machine Learning
inferredcites →https://doi.org/10.2139/ssrn.3741015openalex-snapshot
Fundamental Analysis of XBRL Data: A Machine Learning Approach
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Forecasting Earnings Using k-Nearest Neighbor Matching
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PEAD.txt: Post-Earnings-Announcement Drift Using Text
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Forecasting Earnings with Predicted, Conditional Probability Density Functions
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Predicting Firm Profits: From Fama-MacBeth to Gradient Boosting
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Causal Effect of Information Costs on Asset Pricing Anomalies
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Beyond Growth Rates: Macro Trends and Price Cycles
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Missing Data in Asset Pricing Panels
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How Learning in Financial Markets Generates Excess Volatility and Predictability in Stock Prices
inferredcites →https://doi.org/10.2308/accr-50833openalex-snapshot
Evidence on the Information Content of Text in Analyst Reports
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Life Cycle Models and Forecasting Growth and Profitability
inferredcites →https://doi.org/10.2308/jfir-51332openalex-snapshot
Do Analyst Forecasts Vary Too Much?
inferredcites →https://doi.org/10.2308/tar-2015-0413openalex-snapshot
The Higher Moments of Future Earnings
inferredcites →https://doi.org/10.2308/tar-2019-0622openalex-snapshot
Fundamental Analysis and Mean-Variance Optimal Portfolios
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Abnormal returns to a fundamental analysis strategy.
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Investing in a Multidimensional Market
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News vs. Sentiment: Predicting Stock Returns from News Stories
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Empirical Asset Pricing and Ensemble Machine Learning
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Taming the Factor Zoo: A Test of New Factors
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Comovements in Stock Prices and Comovements in Dividends
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Noise in Expectations: Evidence from Analyst Forecasts
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Return Forecasting by Quantile Regression
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Beyond the Central Tendency: Quantile Regression as a Tool in Quantitative Investing
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The Threshold Effects of RMB Exchange Rate Fluctuations on Imports and Exports
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