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An adaptive and enhanced framework for daily stock market prediction using feature selection and ensemble learning algorithms
Sivri, Mahmut Sami; Ustundag, Alp - In: Journal of business analytics 7 (2024) 1, pp. 42-62
Persistent link: https://www.econbiz.de/10014446579
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Forecasting stock market volatility in India : using linear and non-linear models
Srinivasan, Kaliyaperumal; Deo, Malabika - In: International journal of economic perspectives : IJEP 4 (2010) 4, pp. 617-622
Persistent link: https://www.econbiz.de/10011587796
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Different strokes for different folks : the case of oil shocks and emerging equity markets
Raheem, Ibrahim D. - In: Energy economics 108 (2022), pp. 1-8
Persistent link: https://www.econbiz.de/10013202997
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Correlated beliefs, returns, and stock market volatility
David, Joel M.; Simonovska, Ina - In: Journal of international economics 99 (2016), pp. 58-77
Persistent link: https://www.econbiz.de/10011655068
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The Warsaw Stock Exchange index WIG : modelling and forecasting
Wdowiński, Piotr; Zglinska-Pietrzak, Aneta - 2005
In this paper we have assessed an influence of the NYSE Stock Exchange indexes (DJIA and NASDAQ) and European Stock …
Persistent link: https://www.econbiz.de/10010277059
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One-factor-Garch models for German stocks: Estimation and forecasting
Kaiser, Thomas - 1996
This paper presents theoretical models and their empirical results for the return and variance dynamics of German …
Persistent link: https://www.econbiz.de/10010435583
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The Stochastic Volatility in Mean Model
Koopman, Siem Jan; Uspensky, Eugenie Hol - 2000
In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean … this paper together with a Monte Carlo study toinvestigate the small-sample properties of the SVM estimators. Takingthese …
Persistent link: https://www.econbiz.de/10010324578
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Hierarchical Markov normal mixture models with applications to financial asset returns
Geweke, John; Amisano, Gianni - 2007
With the aim of constructing predictive distributions for daily returns, we introduce a new Markov normal mixture model in which the components are themselves normal mixtures. We derive the restrictions on the autocovariances and linear representation of integer powers of the time series in...
Persistent link: https://www.econbiz.de/10011604877
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Asymmetric effects and long memory in the volatility of Dow Jones stocks
Scharth, Marcel; Medeiros, Marcelo C. - 2006
dynamics? In this paper, we provide empirical evidence that cumulated price variations convey meaningful information about …
Persistent link: https://www.econbiz.de/10011807356
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Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching
Lux, Thomas; Kaizoji, Taisei - 2006
emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short …-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …
Persistent link: https://www.econbiz.de/10010294979