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Machine learning methods for inflation forecasting in Brazil : new contenders versus classical models
Araújo, Gustavo Silva; Gaglianone, Wagner Piazza - In: Latin American journal of central banking : LAJCB 4 (2023) 2, pp. 1-29
In this paper, we explore machine learning (ML) methods to improve inflation forecasting in Brazil. An extensive out …-of-sample forecasting exercise is designed with multiple horizons, a large database of 501 series, and 50 forecasting methods, including new … are relevant to forecasting inflation. The set of top forecasts often includes forecast combinations, tree-based methods …
Persistent link: https://www.econbiz.de/10014382916
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Credit growth, the yield curve and financial crisis prediction : evidence from a machine learning approach
Bluwstein, Kristina; Buckmann, Marcus; Joseph, Andreas; … - In: Journal of international economics 145 (2023), pp. 1-37
Persistent link: https://www.econbiz.de/10014480111
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Economists in the 2008 financial crisis: Slow to see, fast to act
Levy, Daniel C.; Mayer, Tamir; Raviv, Alon - 2022
We study the economics and finance scholars' reaction to the 2008 financial crisis using machine learning language analyses methods of Latent Dirichlet Allocation and dynamic topic modelling algorithms, to analyze the texts of 14,270 NBER working papers covering the 1999-2016 period. We find...
Persistent link: https://www.econbiz.de/10014304174
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Economists in the 2008 financial crisis : slow to see, fast to act
Levy, Daniel C.; Mayer, Tamir; Raviv, Alon - 2022 - Last revision: February 13, 2022
We study the economics and finance scholars' reaction to the 2008 financial crisis using machine learning language analyses methods of Latent Dirichlet Allocation and dynamic topic modelling algorithms, to analyze the texts of 14,270 NBER working papers covering the 1999-2016 period. We find...
Persistent link: https://www.econbiz.de/10013161550
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Can financial sector distress be detected early?
Pietrzak, Marcin - In: Borsa Istanbul Review 22 (2022) 6, pp. 1132-1144
Financial sector distress is a situation in which financial intermediation is either costly or impossible (or both) as proxied by tight financial conditions - high spreads, decline in equity value and high volatility. Tight financial conditions have been identified as a risk factor to the...
Persistent link: https://www.econbiz.de/10014305879
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Is ESG investing an ‘equity vaccine’ in times of crisis? : evidence from the 2020 Wuhan Lockdown and the 2022 Shanghai Lockdown
Dai, Yuwen - In: Borsa Istanbul Review 22 (2022) 5, pp. 992-1004
In the literature on sustainable investing, most studies assume normal market conditions. However, research is limited regarding the specific role of sustainable investing during stressed market conditions. In this paper, we contribute to the literature by investigating the role of ESG investing...
Persistent link: https://www.econbiz.de/10013426739
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Can central bank speeches predict financial market turbulence? Evidence from an adaptive NLP sentiment index analysis using XGBoost machine learning technique
Petropoulos, Anastasios; Siakoulis, Vasilis - In: Central Bank Review (CBR) 21 (2021) 4, pp. 141-153
speeches and translate into a sentiment index for forecasting the future financial markets behaviour. In our analysis, it is …
Persistent link: https://www.econbiz.de/10014547839
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Can central bank speeches predict financial market turbulence? : evidence from an adaptive NLP sentiment index analysis using XGBoost machine learning technique
Petropoulos, Anastasios; Siakoulis, Vasilis - In: Central Bank review / Central Bank of the Republic of Turkey 21 (2021) 4, pp. 141-153
speeches and translate into a sentiment index for forecasting the future financial markets behaviour. In our analysis, it is …
Persistent link: https://www.econbiz.de/10012802256
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Yield Curve and Recession Forecasting in a Machine Learning Framework
Gogas, Periklis; Papadimitriou, Theophilos; Matthaiou, Maria - In: Computational Economics 45 (2015) 4, pp. 635-645
In this paper, we investigate the forecasting ability of the yield curve in terms of the U.S. real GDP cycle. More … attention in correctly forecasting the instances of output gaps referred for the purposes of our analysis here as recessions. In … overall forecasting accuracy of 66.7 and 100 % accuracy in forecasting recessions. These results are compared to the …
Persistent link: https://www.econbiz.de/10011242009
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Multivariate Bayesian Regression Approach to Forecast Releases from a System of Multiple Reservoirs
Ticlavilca, Andres; McKee, Mac - In: Water Resources Management 25 (2011) 2, pp. 523-543
This research presents a model that simultaneously forecasts required water releases 1 and 2 days ahead from two reservoirs that are in series. In practice, multiple reservoir system operation is a difficult process that involves many decisions for real-time water resources management. The...
Persistent link: https://www.econbiz.de/10010997421