Nonlinearity, data-snooping, and stock index ETF return predictability

DOI10.1016/J.EJOR.2009.01.009zbMath1177.91111OpenAlexW2092155530MaRDI QIDQ1042502

J. Blot

Publication date: 14 December 2009

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2009.01.009

zbMATH Keywords

nonlinear modelsrandom walkforecasting evaluationisharesreality check

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84) Statistical methods; economic indices and measures (91B82)

Related Items (3)

Neural networks in financial trading ⋮ Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and particle swarm optimization ⋮ Rough support vector regression

Cites Work

• Unnamed Item
• Is the predictability of emerging and developed stock markets really exploitable?
• Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules
• Testing for neglected nonlinearity in time series models. A comparison of neural network methods and alternative tests
• A Reality Check for Data Snooping
• Functional-Coefficient Regression Models for Nonlinear Time Series
• Linear and nonlinear dependence in Turkish equity returns and its consequences for financial risk management

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