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We propose a hybrid penalized averaging for combining parametric and non-parametric quantile forecasts when faced with a large number of predictors. This approach goes beyond the usual practice of combining conditional mean forecasts from parametric time series models with only a few predictors....
Persistent link: https://www.econbiz.de/10012859663
This paper considers the estimation of a semi-parametric single-index regression model that allows for nonlinear predictive relationships. This model is useful for predicting financial asset returns, whose observed behavior is described by a stationary process, when the multiple non-stationary...
Persistent link: https://www.econbiz.de/10012822931
The procedure for estimating probabilities of future investment returns using time-shifted indexes is based on the simple principle that a multi-dimensional conditional probability distribution can be envisioned involving investment total returns (for a single investment or a fixed portfolio of...
Persistent link: https://www.econbiz.de/10014198891
The procedure for estimating probabilities of future investment returns using time-shifted indexes is based on the simple principle that a multi-dimensional conditional probability distribution can be envisioned involving investment total returns (for a single investment or a fixed portfolio of...
Persistent link: https://www.econbiz.de/10014072195
The Nelson-Siegel model is widely used in practice for fitting the term structure of interest rates. Due to the ease in linearizing the model, a grid search or an OLS approach using a fixed shape parameter are popular estimation procedures. The estimated parameters, however, have been reported...
Persistent link: https://www.econbiz.de/10013036922
The topic of this chapter is forecasting with nonlinear models. First, a number of well-known nonlinear models are introduced and their properties discussed. These include the smooth transition regression model, the switching regression model whose univariate counterpart is called threshold...
Persistent link: https://www.econbiz.de/10014023698
Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels,...
Persistent link: https://www.econbiz.de/10013119940
We propose Midastar models by combining the Mixed Data Sampling (MIDAS) and the threshold autoregression (TAR). The Midastar model of the first kind is designed for a low frequency target variable and a high frequency threshold variable. The proposed model can detect threshold effects...
Persistent link: https://www.econbiz.de/10014240508
Non-homogeneous regression models are widely used to statistically post-process numerical ensemble weather prediction models. Such regression models are capable of forecasting full probability distributions and correct for ensemble errors in the mean and variance. To estimate the corresponding...
Persistent link: https://www.econbiz.de/10011762435
We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...
Persistent link: https://www.econbiz.de/10012487589