Showing 1 - 10 of 957
We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which we apply to the housing markets of China's major cities. Building on the Log-Periodic Power Law Singular (LPPLS) model of self-reinforcing feedback loops, we use the quantile...
Persistent link: https://www.econbiz.de/10011761282
The availability of many variables with predictive power makes their selection in a regression context difficult. This study considers robust and understandable low-dimensional estimators as building blocks to improve overall predictive power by optimally combining these building blocks. Our new...
Persistent link: https://www.econbiz.de/10015361553
Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many...
Persistent link: https://www.econbiz.de/10014178700
The paper develops estimation and inference methods for econometric models with partial identification, focusing on models defined by moment inequalities and equalities. Main applications of this framework include analysis of game-theoretic models, regression with missing and mismeasured data,...
Persistent link: https://www.econbiz.de/10014026967
Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many...
Persistent link: https://www.econbiz.de/10009419329
of macroeconomic predictors and technical indicators with the goal of forecasting the S&P 500 equity risk premium. To … illustrate the merit of the proposed approach, we extend the mean-based equity premium forecasting into the conditional quantile … systematic forecasting power. Third, different predictors are identified as important when considering lower, central and upper …
Persistent link: https://www.econbiz.de/10012859663
. These seven scripts contain the Dynamic Conditional Correlation (DCC) framework, Instantaneous Frequency Forecasting (IFF …
Persistent link: https://www.econbiz.de/10014253907
This paper develops a theory of high and low (extremal) quantile regression: the linear models, estimation, and inference. In particular, the models coherently combine the convenient, flexible linearity with the extreme-value-theoretic restrictions on tails and the general heteroscedasticity...
Persistent link: https://www.econbiz.de/10014129636
forecasting performances across most of the forecasting horizons. Moreover, we found that models using the VRP as an additional … forecasting performances were not statistically different for most models, and only the Principal Component Regression (PCR) and … the Partial least squares (PLS) regression were consistently excluded from the set of best forecasting models. These …
Persistent link: https://www.econbiz.de/10014349277
We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in …
Persistent link: https://www.econbiz.de/10010344303