Search Results - subject:"Gaussian process regression"

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 … regression model is used. The aim of this hybrid approach is to design a model that is easily understandable but allows for a …

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

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

Purpose - Developing price forecasts for various agricultural commodities has long been a significant undertaking for a variety of agricultural market players. The weekly wholesale price of edible oil in the Chinese market over a ten-year period, from January 1, 2010 to January 3, 2020, is the...

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

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

Due to the rapid growth of the Chinese housing market over the past ten years, forecasting home prices has become a crucial issue for investors and authorities alike. In this research, utilising Bayesian optimisations and cross validation, we investigate Gaussian process regressions across...

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

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

Persistent link: https://www.econbiz.de/10015557539

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

Learn to decompose multiobjective optimization models for large-scale networks

Aslani, Babak; Mohebbi, Shima - In: International transactions in operational research : a … 31 (2024) 2, pp. 949-978

Persistent link: https://www.econbiz.de/10014441148

A comprehensive machine learning framework for dynamic portfolio choice with transaction costs

Gaegauf, Luca; Scheidegger, Simon; Trojani, Fabio - 2023

Persistent link: https://www.econbiz.de/10014483248

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

Xu, Xiaojie; Zhang, Yun - 2023

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

A comparative assessment of machine learning methods for predicting housing prices using Bayesian optimization

Lahmiri, Salim; Bekiros, Stelios; Avdoulas, Christos - 2023

regression, and Gaussian process regression. Bayesian optimization is implemented in a ten-fold cross-validation framework to …, followed by Gaussian process regression and support vector regression. In addition, all three aforementioned predictive systems …

Persistent link: https://www.econbiz.de/10014505865

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

The correct modeling of the interest rates term structure should definitely be considered an aspect of primary importance since the forward rates and the discount factors used in any financial and risk analysis are calculated from such structure. The turbulence of the markets in recent years,...

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