Search Results - subject:"Gaussian process"

Predicting wholesale edible oil prices through Gaussian process regressions tuned with Bayesian optimization and cross-validation

Jin, Bingzi; Xu, Xiaojie - In: Asian journal of economics and banking : AJEB 9 (2025) 1, pp. 64-82

optimisations and cross-validation, we study Gaussian process (GP) regressions for our forecasting needs. Findings - The produced …

Persistent link: https://www.econbiz.de/10015339298

Modeling the interest rates term structure using Machine Learning : a Gaussian process regression approach

Delucchi, Alessio; Giribone, Pier Giuseppe - In: Risk management magazine 18 (2023) 3, pp. 16-35

-Siegel, Svensson and de Rezende-Ferreira) up to the Gaussian Process (GP) Regression, is able to define the best representation for a …

Persistent link: https://www.econbiz.de/10014491969

A Gaussian process regression machine learning model for forecasting retail property prices with Bayesian optimizations and cross-validation

Xu, Xiaojie; Zhang, Yun - In: Decision analytics journal 8 (2023), pp. 1-12

to 2021 through monthly data and Gaussian process regression models. We examine ten kernels, four basis functions, and …

Persistent link: https://www.econbiz.de/10014516551

Gaussian process regression with a hybrid risk measure for dynamic risk management in the electricity market

Das, Abhinav; Schlüter, Stephan - In: Risks : open access journal 13 (2025) 1, pp. 1-18

budget using the aforementioned measures to minimize the financial risk. To generate price predictions, a Gaussian process …

Persistent link: https://www.econbiz.de/10015333597

Forecasts of residential real estate price indices for ten major Chinese cities through Gaussian process regressions

Jin, Bingzi; Xu, Xiaojie - In: International journal of empirical economics 4 (2025) 1, pp. 1-24

investigate Gaussian process regressions across various kernels and basis functions for monthly residential real estate price …

Persistent link: https://www.econbiz.de/10015374007

Empirical Asset Pricing via Ensemble Gaussian Process Regression

Filipović, Damir; Pasricha, Puneet - 2022

We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected …

Persistent link: https://www.econbiz.de/10014236083

Machine learning-based scrap steel price forecasting for the Northeast Chinese market

Jin, Bingzi; Xu, Xiaojie - In: International journal of empirical economics 3 (2024) 4, pp. 1-21

account estimates for this significant commodity price measurement. In this instance, Gaussian process regression methods are …

Persistent link: https://www.econbiz.de/10015194297

GMM estimation with Brownian kernels applied to income inequality measurement

Cho, Jin Seo; Phillips, Peter C. B. - 2024

Persistent link: https://www.econbiz.de/10015077115

Stochastic modeling of wind derivatives with application to the Alberta energy market

Warunasinghe, Sudeesha; Sviščuk, Anatolij - In: Risks : open access journal 12 (2024) 2, pp. 1-26

Wind-power generators around the world face two risks, one due to changes in wind intensity impacting energy production, and the second due to changes in electricity retail prices. To hedge these risks simultaneously, the quanto option is an ideal financial tool. The natural logarithm of...

Persistent link: https://www.econbiz.de/10014497409

Consumption dynamics and welfare under non-Gaussian earnings risk

Guvenen, Fatih; Ozkan, Serdar; Madera, Rocio - 2024

Recent empirical studies document that the distribution of earnings changes displays substantial deviations from lognormality: in particular, earnings changes are negatively skewed with extremely high kurtosis (long and thick tails), and these non-Gaussian features vary substantially both over...

Persistent link: https://www.econbiz.de/10014543845