|
Activity Number:
|
65
- Forecasting and Time Series Estimation
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, August 3, 2020 : 10:00 AM to 2:00 PM
|
|
Sponsor:
|
Business and Economic Statistics Section
|
|
Abstract #312854
|
|
|
Title:
|
Improved boosted two parameter Breitung estimator: An application to the crude oil prices
|
|
Author(s):
|
Talha Omer* and Pär Henrik Sjölander and Kristofer Månsson and B M Golam Kibria
|
|
Companies:
|
Jönköping International Business School and Jönköping International Business School, Jönköping University, Sweden and Jönköping International Business School, Jönköping University, Sweden and Florida International University FIU, Miami, USA
|
|
Keywords:
|
MIDAS;
nonparametric;
crude oil;
Two-parameter;
Forecast
|
|
Abstract:
|
Breitung and Roling (2015) presented a superiority of the nonparametric approach for estimation of mixed-frequency forecast. This approach remained outer performed than the usual parametric approach. In this paper, a boosted two parameter Breitung estimator by using the Lipovetsky and Conklin (2005) is proposed. Monte Carlo Simulation experiment suggests that boosted two parameters with an additional predicting parameter provides more reliable, and efficient approximation to the actual lag distribution than the one parameter Breitung nonparametric estimator. One parameter and two parameter Breitung estimators are applied to judge the predictive power of monthly Brent crude oil prices (low frequency variable) of the world on the bases of various daily stock market index (high frequency variable) indicators. In our real-time forecasting application, we find that the two parameter Breitung estimator performed well.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2020 program
|
