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The anatomy of out-of-sample forecasting accuracy
Borup, Daniel; Goulet Coulombe, Philippe; Rapach, David E. - 2022
application forecasting US inflation, we find important discrepancies between individual predictor relevance according to the in …
Persistent link: https://www.econbiz.de/10013429204
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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 U.S. inflation based on autoregressive and structural models of the …
Persistent link: https://www.econbiz.de/10012953784
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The Anatomy of Out-of-Sample Forecasting Accuracy
Borup, Daniel; Goulet Coulombe, Philippe; Rapach, David E. - 2022
application forecasting US inflation, we find important discrepancies between individual predictor relevance according to the in …
Persistent link: https://www.econbiz.de/10014238433
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Prospects of artificial intelligence and machine learning application in banking risk management
Milojević, Nenad; Redzepagic, Srdjan - In: Journal of Central Banking Theory and Practice 10 (2021) 3, pp. 41-57
Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The...
Persistent link: https://www.econbiz.de/10014558436
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Weak-form market efficiency and corruption : a cross-country comparative analysis
İcan, Özgür; Çelik, Taha Buğra - In: Journal of capital markets studies 7 (2023) 1, pp. 72-90
Purpose - The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance...
Persistent link: https://www.econbiz.de/10014318195
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Prospects of artificial intelligence and machine learning application in banking risk management
Milojević, Nenad; Redzepagic, Srdjan - In: Journal of central banking theory and practice 10 (2021) 3, pp. 41-57
Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The...
Persistent link: https://www.econbiz.de/10012650890
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Forecasting accuracy of machine learning and linear regression: evidence from the secondary CAT bond market
Götze, Tobias; Gürtler, Marc; Witowski, Eileen - In: Journal of Business Economics 93 (2023) 9, pp. 1629-1660
The main challenge in empirical asset pricing is forecasting the future value of assets traded in financial markets with a high level of accuracy. Because machine learning methods can model relationships between explanatory and dependent variables based on complex, non-linear, and/or...
Persistent link: https://www.econbiz.de/10015272797
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Weak-form market efficiency and corruption: A cross-country comparative analysis
İcan, Özgür; Çelik, Taha Buğra - In: Journal of Capital Markets Studies (JCMS) 7 (2023) 1, pp. 72-90
Purpose - The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance...
Persistent link: https://www.econbiz.de/10015327960
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Adaptive trees : a new approach to economic forecasting
Woloszko, Nicolas - 2020
The present paper develops Adaptive Trees, a new machine learning approach specifically designed for economic forecasting. Economic forecasting is made difficult by economic complexity, which implies non-linearities (multiple interactions and discontinuities) and unknown structural changes (the...
Persistent link: https://www.econbiz.de/10012203223
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Tracking activity in real time with Google Trends
Woloszko, Nicolas - 2020
This paper introduces the OECD Weekly Tracker of economic activity for 46 OECD and G20 countries using Google Trends search data. The Tracker performs well in pseudo-real time simulations including around the COVID-19 crisis. The underlying model adds to the previous Google Trends literature in...
Persistent link: https://www.econbiz.de/10012420946