Showing 1 - 10 of 11
Over the last four decades, several methods for selecting the smoothing parameter, generally called the bandwidth, have been introduced in kernel regression. They differ quite a bit, and although there already exist more selection methods than for any other regression smoother we can still see...
Persistent link: https://www.econbiz.de/10010329908
Over the last four decades, several methods for selecting the smoothing parameter, generally called the bandwidth, have been introduced in kernel regression. They differ quite a bit, and although there already exist more selection methods than for any other regression smoother we can still see...
Persistent link: https://www.econbiz.de/10010349165
We discuss the following two particular aspects of the paper of González-Manteiga and Crujeiras (<ExternalRef> <RefSource>10.1007/s11749-013-0327-5</RefSource> <RefTarget Address="10.1007/s11749-013-0327-5" TargetType="DOI"/> </ExternalRef>): First, what changes if the null hypothesis is non- or semiparametric? For example, Rodriguez-Poo et al. (A practical test for misspecification in regression:...</refsource></externalref>
Persistent link: https://www.econbiz.de/10010994273
On the one hand, kernel density estimation has become a common tool for empirical studies in any research area. This goes hand in hand with the fact that this kind of estimator is now provided by many software packages. On the other hand, since about three decades the discussion on bandwidth...
Persistent link: https://www.econbiz.de/10010848172
Over the last four decades, several methods for selecting the smoothing parameter, generally called the bandwidth, have been introduced in kernel regression. They differ quite a bit, and although there already exist more selection methods than for any other regression smoother we can still see...
Persistent link: https://www.econbiz.de/10009293342
In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate. In particular, we apply in a two-step...
Persistent link: https://www.econbiz.de/10013200531
Persistent link: https://www.econbiz.de/10011422898
Persistent link: https://www.econbiz.de/10009666508
In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate. In particular, we apply in a two-step...
Persistent link: https://www.econbiz.de/10012127861
Persistent link: https://www.econbiz.de/10012138047