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Real-Time Macro Information and Bond Return Predictability : Does Deep Learning Help?

Feng, Guanhao; Fulop, Andras; Li, Junye - 2021

This paper examines whether deep/machine learning can help find any statistical and/or economic evidence of out-of-sample bond return predictability when real-time, instead of fully-revised, macro variables are taken as predictors. First, when using pure real-time macro information alone, we...

Persistent link: https://www.econbiz.de/10013250220

Does Realized Skewness Predict the Cross-Section of Equity Returns?

Amaya, Diego; Christoffersen, Peter; Jacobs, Kris; … - 2015

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We...

Persistent link: https://www.econbiz.de/10014179412

Real-Time Bayesian Learning and Bond Return Predictability

Fulop, Andras; Li, Junye; WAN, Runqing - 2019

The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However,...

Persistent link: https://www.econbiz.de/10014120968

Modifications on book-valued ratios

Georgiou, Catherine - In: International journal of business and economic sciences … 15 (2022) 3, pp. 24-37

book, dividends and earnings, Our analysis includes evidence of predictability on dividend and earnings growth rates on the … series and fix the book-earnings (be) and the dividend-book (db) ratios, We similarly modify be and db, and examine their … forecasting performance on returns, dividend and earnings growth. Findings: In-sample evidence suggests that an investor who …

Persistent link: https://www.econbiz.de/10014281276

Generalized Bounds on the Conditional Expected Excess Return on Individual Stocks

Chabi-Yo, Fousseni - 2020

We derive generalized bounds on conditional expected excess returns. The bounds deliver consistent expected returns for individual and index-type assets, are conditionally tight, account for all risk-neutral moments of returns, and outperform runner-up models for out-of-sample predictions....

Persistent link: https://www.econbiz.de/10012838211

The Market Value of Equity-to-Gross Domestic Product Ratio as a Predictor of Long-term Equity Returns : Evidence from the U.S. Market, 1951-2019

Umlauft, Thomas S. - 2020

In a 2001 interview in Forbes, Warren Buffett suggested that the ratio of the market value of publicly traded stocks to economic output could identify potential equity market mispricings. This paper investigates the return-predictive characteristics of the market value of equity-to-gross...

Persistent link: https://www.econbiz.de/10012839874

Good News, Bad News, No News : The Media and the Cross Section of Stock Returns

Naumer, Hans-Jörg - 2020

We examine the relationship between the tonality of news flow and the cross section of expected stock returns. We use a comprehensive definition of media coverage that includes both financial newspapers and mass media, represented by TV broadcasts. Using the total news flow with positive and...

Persistent link: https://www.econbiz.de/10012841196

An Empirical Investigation of Asymmetric Volatility, Trading Volume and Risk-Return Relationship in the Indian Stock Market

Naik, Pramod Kumar - 2013

The objective of this article is to investigate the volatility asymmetry, volatility-volume relationship by considering trading volume as a mixing variable, and the risk-return relationship in the Indian stock market. Daily data from January 2, 1997 to May 30, 2013 for S&P CNX Nifty are used for...

Persistent link: https://www.econbiz.de/10013078205

Tail Risk and Asset Prices

Kelly, Bryan T. - 2014

We propose a new measure of time-varying tail risk that is directly estimable from the cross section of returns. We exploit firm-level price crashes every month to identify common fluctuations in tail risk across stocks. Our tail measure is significantly correlated with tail risk measures...

Persistent link: https://www.econbiz.de/10013063059

Cross-section without factors : correlation risk, strings and asset prices

Distaso, Walter; Mele, Antonio; Vilkov, Grigory - 2021 - This version: January 13, 2021

Many asset pricing theories treat the cross-section of returns volatility and correlations as two intimately related quantities driven by common factors, which hinders achieving a neat definition of a correlation premium. We formulate a model without factors, but with a continuum of securities...

Persistent link: https://www.econbiz.de/10012421289