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Investor Attention and Stock Returns
Chen, Jian - 2020
We find that investor attention proxies proposed in the literature collectively have a common component that has significant power in predicting stock market risk premium, both in-sample and out-of-sample. This common component is well extracted by using partial least squares, scaled principal...
Persistent link: https://www.econbiz.de/10012852097
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Intraday Momentum : The First Half-Hour Return Predicts the Last Half-Hour Return
Gao, Lei - 2017
Our research on data for the S&P 500 ETF from 1993-2013 documents an intraday momentum pattern: the first half-hour return on the market (from the previous day's close) predicts the last half-hour return. The predictability, both statistically and economically significant, is stronger on more...
Persistent link: https://www.econbiz.de/10012972249
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Taming Momentum Crashes : A Simple Stop-Loss Strategy
Han, Yufeng - 2016
In this paper, we propose a stop-loss strategy to limit the downside risk of the well-known momentum strategy. At a stop-level of 10%, we find, with data from January 1926 to December 2013, that the maximum monthly losses of the equal- and value-weighted momentum strategies go down from -49.79%...
Persistent link: https://www.econbiz.de/10013006637
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Macroeconomic Volatilities and Long-Run Risks of Asset Prices
Zhou, Guofu - 2014
-run risks model of Bansal and Yaron (2004) by allowing both a long- and a short-run volatility components in the evolution of … economic fundamentals. With this extension, the new model not only is consistent with the volatility literature that the stock … market is driven by two, rather than one, volatility factors, but also provides significant improvements in fitting various …
Persistent link: https://www.econbiz.de/10013071174
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A New Anomaly : The Cross-Sectional Profitability of Technical Analysis
Han, Yufeng - 2012
by volatility generates investment timing portfolios that often outperform the buy-and-hold strategy substantially. For … high volatility portfolios, the abnormal returns, relative to the CAPM and the Fama-French three-factor models, are high …
Persistent link: https://www.econbiz.de/10013115819
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Investor Sentiment and the Cross-Section of Corporate Bond Returns
Guo, Xu - 2019
This paper constructs an investor sentiment measure at both individual bond and aggregate levels, uncovering the first evidence that investor sentiment has strong cross- sectional predictive power for corporate bond returns. High bond investor sentiment leads to low future returns. A portfolio...
Persistent link: https://www.econbiz.de/10012898628
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Industry Return Predictability : A Machine Learning Approach
Rapach, David - 2019
We use machine learning tools to analyze industry return predictability based on theinformation in lagged industry returns from across the entire economy. Controlling forpost-selection inference and multiple testing, we nd significant in-sample evidence ofindustry return predictability. Lagged...
Persistent link: https://www.econbiz.de/10012900047
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Cost Behavior and Stock Returns
Huang, Dashan - 2017
attention, higher idiosyncratic volatility, and higher transaction costs, suggesting that investor underreaction and limits to …
Persistent link: https://www.econbiz.de/10012973043
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Upper Bounds on Return Predictability
Huang, Dashan - 2017
Can the degree of predictability found in the data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R-squares of predictive regressions. Using data on the market and component portfolios, we find that the empirical R-squares are significantly greater...
Persistent link: https://www.econbiz.de/10012973313
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Forecasting Stock Returns in Good and Bad Times : The Role of Market States
Huang, Dashan - 2017
This paper proposes a two-state predictive regression model and shows that stock market 12-month return (TMR), the time-series momentum predictor of Moskowitz, Ooi, and Pedersen (2012), forecasts the aggregate stock market negatively in good times and positively in bad times. The out-of-sample...
Persistent link: https://www.econbiz.de/10012974764