Predicting Prices Of Financial Assets: From Classical Economics To Intelligent Finance
AbstractDetermining the circumstances under which it is possible to make any sort of prediction is a fundamental question in financial research. The presence of complex and robust statistical characteristics, exhibited by most financial time series, raise doubts on the simple relationship between information and price changes, as implied by the efficient market hypothesis. In this paper, we consider the main competing economic hypotheses and examine different approaches for learning the price behaviour in financial markets. Our analysis reveals the need to approach the problem from a new perspective. In financial markets, traders are not only adapting, but also determine and form the economic mechanism essentially by their actions. In these settings, financial markets are evolutionary structures of competing trading strategies; prices in such markets are driven endogenously by the induced expectations. A combination of economics, computer and cognitive science in cross-disciplinary study of intelligent finance, which aims to explore information about financial markets from multiple perspectives, is expected to expand the boundary of pure economic analysis.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by World Scientific Publishing Co. Pte. Ltd. in its journal New Mathematics and Natural Computation.
Volume (Year): 07 (2011)
Issue (Month): 02 ()
Contact details of provider:
Web page: http://www.worldscinet.com/nmnc/nmnc.shtml
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tai Tone Lim).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.