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Demand estimation with machine learning and model combination

Bajari, Patrick L.; Nekipelov, Denis N.; Ryan, Stephen; … - 2015

Persistent link: https://www.econbiz.de/10010496176

Forecasting exchange rates with neural networks : time variation, nonstationarity, and causal models

Reikard, Gordon - In: International economic journal 37 (2023) 2, pp. 202-219

Persistent link: https://www.econbiz.de/10014295003

Non-Linear interactions and exchange rate prediction : empirical evidence using support vector regression

Peng, Yaohao; Albuquerque, Pedro H. - In: Applied mathematical finance 26 (2019) 1, pp. 69-100

Persistent link: https://www.econbiz.de/10012210260

Dynamic Factor Trees and Forests : a theory-led machine learning framework for non-linear and state-dependent short-term U.S. GDP growth predictions

Wochner, Daniel - 2020 - This version: January 31, 2020

theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic … reduce to the standard Dynamic Factor Model (DFM) as a special case and allow us to embed theory-led factor models in …

Persistent link: https://www.econbiz.de/10012172506

Extracting statistical factors when betas are time-varying

Gagliardini, Patrick; Ma, Hao - 2019 - This version: July 2019

This paper deals with identification and inference on the unobservable conditional factor space and its dimension in large unbalanced panels of asset returns. The model specification is nonparametric regarding the way the loadings vary in time as functions of common shocks and individual...

Persistent link: https://www.econbiz.de/10012176811

Improving the predictive accuracy of production frontier models for efficiency measurement using machine learning : the LSB-MAFS method

Guillen, María D.; Aparicio, Juan; Zofío, José L.; … - In: Computers & operations research : an international journal 171 (2024), pp. 1-19

Persistent link: https://www.econbiz.de/10015066453

Short-term hourly ozone concentration forecasting using functional data approach

Shah, Ismail; Gul, Naveed; Ali, Sajid; Houmani, Hassan - In: Econometrics : open access journal 12 (2024) 2, pp. 1-21

Air pollution, especially ground-level ozone, poses severe threats to human health and ecosystems. Accurate forecasting of ozone concentrations is essential for reducing its adverse effects. This study aims to use the functional time series approach to model ozone concentrations, a method less...

Persistent link: https://www.econbiz.de/10014636419