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The impact of jumps and leverage in forecasting the co-volatility of oil and gold futures
Asai, Manabu; Gupta, Rangan; McAleer, Michael - 2019
Persistent link: https://www.econbiz.de/10011986953
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Using large data sets to forecast housing prices : a case study of twenty US states
Gupta, Rangan; Kabundi, Alain; Miller, Stephen M. - 2009
Persistent link: https://www.econbiz.de/10003867043
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Forecasting US real house price returns over 1831 - 2013 : evidence from copula models
Gupta, Rangan; Majumdar, Anandamayee - 2014
Persistent link: https://www.econbiz.de/10010432202
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Forecasting US real private residential fixed investment using a large number of predictors
Aye, Goodness C.; Gupta, Rangan; Miller, Stephen M.; … - 2014
Persistent link: https://www.econbiz.de/10010415549
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The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate : A Nonlinear Approach
Gogas, Periklis - 2017
The difficulty in modelling inflation and the significance in discovering the underlying data generating process of inflation is expressed in an ample literature regarding inflation forecasting. In this paper we evaluate nonlinear machine learning and econometric methodologies in forecasting the...
Persistent link: https://www.econbiz.de/10012953784
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Do shortages forecast aggregate and sectoral U.S. stock market realized variance? : evidence from a century of data
Bonato, Matteo; Gupta, Rangan; Pierdzioch, Christian - 2024
Persistent link: https://www.econbiz.de/10015126965
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Forecasting growth-at-risk of the United States : housing price versus housing sentiment or attention
Cepni, Oguzhan; Gupta, Rangan; Pierdzioch, Christian - 2024
Persistent link: https://www.econbiz.de/10014483637
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Climate risks and forecastability of the weekly state-level economic conditions of the United States
Ҫepni, Oğuzhan; Gupta, Rangan; Liao, Wenting; Ma, Jun - 2022
Persistent link: https://www.econbiz.de/10013435217
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Using Large Data Sets to Forecast Housing Prices : A Case Study of Twenty US States
Gupta, Rangan - 2012
We implement several Bayesian and classical models to forecast housing prices in 20 US states. In addition to standard …, we compare the forecast performance of the alternative models. Based on the average root mean squared error (RMSE) for …
Persistent link: https://www.econbiz.de/10013117046
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Safe havens, machine learning, and the sources of geopolitical risk : a forecasting analysis using over a century of data
Gupta, Rangan; Karmakar, Sayar; Pierdzioch, Christian - 2022
Persistent link: https://www.econbiz.de/10012794059