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Calomiris, Charles W.; Melek, Nida Çakır; Mamaysky, Harry - National Bureau of Economic Research - 2021

-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories …

Persistent link: https://www.econbiz.de/10012660057

Why Has U.S. Inflation Become Harder to Forecast?

Stock, James H. - 2006

inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an …

Persistent link: https://www.econbiz.de/10012466341

Dynamics of Subjective Risk Premia

Nagel, Stefan; Xu, Zhengyang - National Bureau of Economic Research - 2022

We examine subjective risk premia implied by return expectations of individual investors and professionals for aggregate portfolios of stocks, bonds, currencies, and commodity futures. While in-sample predictive regressions with realized excess returns suggest that objective risk premia vary...

Persistent link: https://www.econbiz.de/10012938772

A Dynamic Model of Characteristic-Based Return Predictability

Alti, Aydoğan - 2019

We present a dynamic model that links characteristic-based return predictability to systematic factors that determine the evolution of firm fundamentals. In the model, an economy-wide disruption process reallocates profits from existing businesses to new projects and thus generates a source of...

Persistent link: https://www.econbiz.de/10012479727

Predicting Returns With Text Data

Ke, Zheng Tracy - 2019

We introduce a new text-mining methodology that extracts sentiment information from news articles to predict asset returns. Unlike more common sentiment scores used for stock return prediction (e.g., those sold by commercial vendors or built with dictionary-based methods), our supervised...

Persistent link: https://www.econbiz.de/10012480131

Robust Bond Risk Premia

Bauer, Michael D. - 2017

A consensus has recently emerged that variables beyond the level, slope, and curvature of the yield curve can help predict bond returns. This paper shows that the statistical tests underlying this evidence are subject to serious small-sample distortions. We propose more robust tests, including a...

Persistent link: https://www.econbiz.de/10012455201

Innovative Originality, Profitability, and Stock Returns

Hirshleifer, David - 2017

We propose that innovative originality (InnOrig) is a valuable organizational resource, and that owing to limited investor attention and skepticism of complexity, firms with greater InnOrig are undervalued. We find that firms' InnOrig strongly predicts higher, more persistent, and less volatile...

Persistent link: https://www.econbiz.de/10012455249

Four Centuries of Return Predictability

Golez, Benjamin - 2014

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands/U.K. (1629-1812), U.K. (1813-1870) and U.S. (1871-2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for...

Persistent link: https://www.econbiz.de/10012457852

Growth Expectations, Dividend Yields, and Future Stock Returns

Da, Zhi - 2014

According to the dynamic version of the Gordon growth model, the long-run expected return on stocks, stock yield, is the sum of the dividend yield on stocks plus some weighted average of expected future growth rates in dividends. We construct a measure of stock yield based on sell-side analysts'...

Persistent link: https://www.econbiz.de/10012458014

Identifying Long-Run Risks : A Bayesian Mixed-Frequency Approach

Schorfheide, Frank - 2014

multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly … predictable component and use high-frequency data, whenever available, to efficiently identify the volatility processes. Our … are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our …

Persistent link: https://www.econbiz.de/10012458363

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