 Neural networks and technical analysis for price prediction: the case of Borsa Italiana SP MIBAngelo Corelli International Journal of Business Continuity and Risk Management, 2020, vol. 10, issue 1, 1-22 Abstract: The paper analyses the relationship between common technical analysis indicators and the returns of an index for the period considered. It is expected to find correlation between indicators and index prices, as well as showing clear patterns and potential strategies for investment analysis and portfolio management. As an innovative methodology a mixed analysis is carried out, trying to combine classic signals offered by the indicators with the power of neural networks. The neural network plays an important role in that allows for an accurate regression with efficient error minimisation, while giving indications about the concentration of results obtained around some reference values. Through a simple hidden-layer, back-propagation algorithm, regressions give interesting result, in term of the forecasting potential of the analysed indicators. The final step of the project is to conclude about results and summarise the indication coming from the multivariate stage analysis, commenting on the power of the indicators to reveal potential investment opportunities. Keywords: technical indicator; neural network; backpropagation; steepest descent; normalisation. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbcrm:v:10:y:2020:i:1:p:1-22 Access Statistics for this article More articles in International Journal of Business Continuity and Risk Management from Inderscience Enterprises Ltd |
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