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Forecasting returns with fundamentals-removed investor sentiment
Stivers, Adam - In: International Journal of Financial Studies : open … 3 (2015) 3, pp. 319-341
The Baker and Wurgler (2006) sentiment index purports to measure irrational investor sentiment, while the University of Michigan Consumer Sentiment Index is designed to largely reflect fundamentals. Removing this fundamental component from the Baker and Wurgler index creates an index of investor...
Persistent link: https://www.econbiz.de/10011312208
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News Content, Investor Misreaction, and Stock Return Predictability
Hadzic, Muris - 2015
Using a large dataset of news releases, we study instances of investors' mistaken reaction, or misreaction, to news. We define misreaction as stock prices moving in the direction opposite to the news when it is released. We find that news tone predicts returns in the cross-section only upon the...
Persistent link: https://www.econbiz.de/10013016562
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Predicting Momentum
Ma, Siyuan - 2022
This paper examines to what extent the momentum spread ratio (MSR) can predict momentum profits. The momentum spread ratio as a potential proxy of investor underreaction can significantly predict the momentum, industry momentum, and residual momentum, especially after 1994, suggesting that...
Persistent link: https://www.econbiz.de/10013404733
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Investor Sentiment and Paradigm Shifts in Equity Return Forecasting
Chu, Liya; He, Xuezhong; Li, Kai; Tu, Jun - 2022
This study investigates the impact of investor sentiment on excess equity return forecasting. A high (low) investor sentiment may weaken the connection between fundamental economic (behavioral-based non-fundamental) predictors and market returns. We find that although fundamental variables can...
Persistent link: https://www.econbiz.de/10013405087
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Forecasting Excess Returns of the Gold Market : Can We Learn from Stock Market Predictions?
Dichtl, Hubert - 2017
As some recent studies have shown empirically, future gold price fluctuations are especially difficult to forecast … prediction techniques leads to better forecasts of gold excess returns. The forecast power of fundamental predictor variables is … not only highly regime-dependent, but also dependent on the selected economic evaluation criterion. Future gold forecast …
Persistent link: https://www.econbiz.de/10012951544
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Average skewness matters!
Jondeau, Eric; Zhang, Qunzi - 2015
Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...
Persistent link: https://www.econbiz.de/10011412455
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Why Do Options Prices Predict Stock Returns? Evidence from Analyst Tipping
Lin, Tse-Chun - 2014
We study the role of analysts and options traders in the information transmission between options and stock markets. We first show that the predictive power of option implied volatilities (IVs) on stock returns more than doubles around analyst-related events, indicating that a significant...
Persistent link: https://www.econbiz.de/10013065163
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Credit Conditions and Stock Return Predictability
Chava, Sudheer - 2015
We analyze U.S. stock return predictability using a measure of credit standards (Standards) derived from the Federal Reserve Board's Senior Loan Officer Opinion Survey on Bank Lending Practices. Standards is a strong predictor of stock returns at a business cycle frequency, especially in the...
Persistent link: https://www.econbiz.de/10013039035
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Forecasting Yield Changes Using Bond Market Order Flow
Valseth, Siri - 2012
Bond market order flow contains information about future yield changes that is not incorporated into the current yield curve. Daily and monthly forecasts based on models including interdealer order flow outperform forecasts based on traditional term structure models and the random walk. A new...
Persistent link: https://www.econbiz.de/10013113018
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The Promises and Pitfalls of Machine Learning for Predicting Stock Returns
Leung, Edward - 2020
Recent research suggests that machine learning models dominate traditional linear models in predicting cross-sectional stock returns. We confirm this finding when predicting one-month forward-looking returns based on a set of common stock characteristics, including predictors such as short-term...
Persistent link: https://www.econbiz.de/10012840386