stock: The Data Set of Monthly Stock Return and Sotck Variance
In quantilogram: Cross-Quantilogram
stock R Documentation
The Data Set of Monthly Stock Return and Sotck Variance
Description
The dataset contains monthly excess stock returns and stock varaince,
which are included in the data set analyzed in Goyal and Welch (2008).
Stock returns are measured by the S&P 500 index and include dividens.
A treasury-bill rate is subtracted from stock returns to give excess stock returns
The stock variance is a volatility estimate based on daily squared returns
and is treated as an estimate of equity risk in the literature.
The sample period is from Feburary 1885 to December 2005 with sample size 1,451.
Date: Year-Month-Day
Return: excess stock returns
Variance: stock variance
Usage
data(stock)
Format
A data object with two variables
References
Han, H., Linton, O., Oka, T., and Whang, Y. J. (2016).
"The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series."
Journal of Econometrics, 193(1), 251-270.
Welch, Ivo, and Amit Goyal.
"A comprehensive look at the empirical performance of equity premium prediction."
Review of Financial Studies 21.4 (2008): 1455-1508.
quantilogram documentation built on March 18, 2022, 5:29 p.m.
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| stock | R Documentation |
The Data Set of Monthly Stock Return and Sotck Variance
Description
The dataset contains monthly excess stock returns and stock varaince, which are included in the data set analyzed in Goyal and Welch (2008). Stock returns are measured by the S&P 500 index and include dividens. A treasury-bill rate is subtracted from stock returns to give excess stock returns The stock variance is a volatility estimate based on daily squared returns and is treated as an estimate of equity risk in the literature. The sample period is from Feburary 1885 to December 2005 with sample size 1,451.
Date: Year-Month-Day
Return: excess stock returns
Variance: stock variance
Usage
data(stock)
Format
A data object with two variables
References
Han, H., Linton, O., Oka, T., and Whang, Y. J. (2016). "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series." Journal of Econometrics, 193(1), 251-270.
Welch, Ivo, and Amit Goyal. "A comprehensive look at the empirical performance of equity premium prediction." Review of Financial Studies 21.4 (2008): 1455-1508.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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