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Tackling large outliers in macroeconomic data with vector artificial neural network autoregression
Polito, Vito; Zhang, Yunyi - 2021
We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure...
Persistent link: https://www.econbiz.de/10012668293
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Persistence in ESG and conventional stock market indices
Caporale, Guglielmo Maria; Gil-Alaña, Luis A.; … - 2021
This paper uses R/S analysis and fractional integration techniques to examine the persistence of two sets of 12 ESG and conventional stock price indices from the MSCI database over the period 2007-2020 for a large number of both developed and emerging markets. Both sets of results imply that...
Persistent link: https://www.econbiz.de/10012520863
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A long-memory model for multiple cycles with an application to the S&P500
Caporale, Guglielmo Maria; Gil-Alaña, Luis A. - 2024
This paper proposes a long-memory model including multiple cycles in addition to the long-run component. Specifically, instead of a single pole or singularity in the spectrum, it allows for multiple poles and thus different cycles with different degrees of persistence. It also incorporates...
Persistent link: https://www.econbiz.de/10014470433
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Volatility forecasts for the RTS stock index : optionimplied volatility versus alternative methods
Caporale, Guglielmo Maria; Teterkina, Daria - 2019
This paper compares volatility forecasts for the RTS Index (the main index for the Russian stock market) generated by … alternative models, specifically option-implied volatility forecasts based on the Black-Scholes model, ARCH/GARCH-type model … information content). Various forecasting performance tests are carried out which suggest that both implied volatility and …
Persistent link: https://www.econbiz.de/10011997328
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Model Averaging in Risk Management with an Application to Futures Markets
Pesaran, M. Hashem (contributor);  … - 2008
Persistent link: https://www.econbiz.de/10003641741
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Forecasting random walks under drift instability
Pesaran, M. Hashem (contributor); Pick, Andreas (contributor) - 2008
Persistent link: https://www.econbiz.de/10003711763
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Predicting student dropout : a replication study based on neural networks
Buchhorn, Jascha; Wigger, Berthold U. - 2021
Using neural networks, the present study replicates previous results on the prediction of student dropout obtained with decision trees and logistic regressions. For this purpose, multilayer perceptrons are trained on the same data as in the initial study. It is shown that neural networks lead to...
Persistent link: https://www.econbiz.de/10012622475
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The weekly structure of US stock prices
Caporale, Guglielmo Maria; Gil-Alaña, Luis A. - 2010
In this paper we use fractional integration techniques to examine the degree of integration of four US stock market indices, namely the Standard and Poor, Dow Jones, Nasdaq and NYSE, at a daily frequency from January 2005 till December 2009. We analyse the weekly structure of the series and...
Persistent link: https://www.econbiz.de/10008732289
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Testing for persistence in German green and brown stock market indices
Caporale, Guglielmo Maria; Gil-Alaña, Luis A.; Solarin … - 2024
estimation of a GARCH (1,1) model for stock returns shows that their conditional volatility is characterised by lower persistence …
Persistent link: https://www.econbiz.de/10014578571
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The Warsaw Stock Exchange index WIG : modelling and forecasting
Wdowinski, Piotr (contributor);  … - 2005
In this paper we have assessed an influence of the NYSE Stock Exchange indexes (DJIA and NASDAQ) and European Stock indexes (DAX and FTSE) on the Warsaw Stock Exchange index WIG within a framework of a GARCH model. By applying a procedure of checking predictive quality of econometric models as...
Persistent link: https://www.econbiz.de/10003202866