Search Results - subject:"neural network model"

Stock return prediction with multiple measures using neural network models

Wang, Cong - In: Financial innovation : FIN 10 (2024), pp. 1-34

In the feld of empirical asset pricing, the challenges of high dimensionality, non-linear relationships, and interaction efects have led to the increasing popularity of machine learning (ML) methods. This study investigates the performance of ML methods when predicting diferent measures of stock...

Persistent link: https://www.econbiz.de/10014548175

Prediction of China's industrial carbon peak : based on GDIM-MC model and LSTM-NN model

Li, Wen-kai; Wen, Hong-xing; Nie, Pu-yan - In: Energy strategy reviews 50 (2023), pp. 1-13

comprehensively used Monte Carlo simulation and LSTM Neural Network model to predict the evolution trends of China's industrial carbon … Technological Breakthrough scenario (green technology progress) will peak in 2027 and 2025, and under the LSTM Neural Network model …

Persistent link: https://www.econbiz.de/10014574953

Supporting of manufacturing system based on demand forecasting tool

Kmiecik, Mariusz; Zangana, Hawre - In: LogForum : elektroniczne czasopismo naukowe z dziedziny … 18 (2022) 1, pp. 33-48

Persistent link: https://www.econbiz.de/10013164691

A Dynamic Weighted Distancedbased Fuzzy Time Series Neural Network with Bootstrap Model for Option Price Forecasting

Yang, Chih-Chung; Leu, Yungho; Lee, Chien-Pang - In: Journal for Economic Forecasting (2014) 2, pp. 115-129

function neural network model and a bootstrap method. In the proposed model, the dynamic n-order 2-factor fuzzy time series … dataset for the radial basis function neural network model to forecast the option price. However, the sample size of option …

Persistent link: https://www.econbiz.de/10010797473

Detecting the Manipulation of Financial Information by Using Artificial Neural Network Models

Kuçukkocaoglu, Guray; Benli, Yasemin Keskin; … - In: Istanbul Stock Exchange Review 9 (2009) 36, pp. 1-26

companies. An Artificial Neural Network Model, which is based on the concept of using artificial neurons, to estimate the … the proposed Artificial Neural Network Model outperforms the traditional statistical techniques used in earnings …

Persistent link: https://www.econbiz.de/10010756116

Detecting the Manipulation of Financial Information by Using Artificial Neural Network Models

Kuçukkocaoglu, Guray; Benli, Yasemin Keskin; … - In: Istanbul Stock Exchange Review 9 (2007) 36, pp. 1-26

Persistent link: https://www.econbiz.de/10010764158

Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination

Teräsvirta, Timo; van Dijk, Dick; Medeiros, Marcelo C. - 2004

In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and neural network (NN) time series models for 47 monthly macroeconomic variables of the G7 economies. Unlike previous studies that typically consider multiple but fixed model...

Persistent link: https://www.econbiz.de/10011807313

Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination

Teräsvirta, Timo; Dijk, Dick van; Medeiros, Marcelo Cunha - Departamento de Economia, Pontifícia Universidade … - 2004

Persistent link: https://www.econbiz.de/10005744713

Analyzing the supplier/customer relationship: an industrial case study

Larson, Nick; Kusiak, Andrew; Clymer, David; Thompson, Gary - 1996

capabilities. A neural network model was developed to supplement an existing supplier evaluation system by providing commodity …

Persistent link: https://www.econbiz.de/10009466033