The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS
Transactions ID Number: 29-655
Full Name: Pirtea Marilen Gabriel
Position: Professor
Age: ON
Sex: Male
Address: J. H. Pestalozzi nr. 16, 300115, Timişoara
Country: ROMANIA
Tel: 0040720724197
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Fax:
E-mail address: marilen.pirtea@gmail.com
Other E-mails: stefana_cristea@yahoo.it
Title of the Paper: Error-Based Learning Processes on Financial Markets
Authors as they appear in the Paper: Dima Bogdan, Pirtea Marilen Gabriel, Cristea Ştefana
Email addresses of all the authors: bogdandima2001@gmail.com , stefana_cristea@yahoo.it, marilen.pirtea@feaa.uvt.ro
Number of paper pages: 12
Abstract: A critical issue in financial markets' research is the debate between the academic orthodox approach of the Efficient Markets' Hypothesis and the critics rising from the behavioral finance paradigm and practice. Several alternative explanations have been proposed in order to provide a more realistic description of the financial markets' inner mechanisms. This debate's importance consists in the implications of the adopted point of view on the assessment of the financial markets' predictability degree. [4], [5] proposed a unified approach labeled as Adaptive Markets Hypothesis. Thus, from a practical point of view, the main issue consists in providing a pertinent answer to the next question: Is an active portfolio management able to provide better results that a passive "follow the market on long-run" strategy? If in adaptive models the markets are considered to display, at least in a certain sense, a degree of predictability, then, one of the major difficulties in !
supplying empirical evidences is the requirement of knowing ex ante the "exact" forecast model used by the economic subjects. The aim of this study is providing a solution to this problem inspired by the transduction's (supervised learning) algorithms. Our main output consists in the thesis that the forecasting errors matter for price formation in financial markets. So, despite the fact that nor the theoretical foundations nor the empirical evidences are conclusive, we argue that the nature of the "exact" learning mechanisms can be seen as one of the key variables in investors' decisions and markets evolution. There is a significant positive payoff of a more detailed study of such mechanisms inside an extended framework of financial markets as complex systems.
Keywords: Financial markets, FTSE 100, Adaptive Markets Hypothesis, forecasting algorithms, forecasting errors, adaptive mechanisms
EXTENSION of the file: .rtf
Special (Invited) Session: Remarks over the Error-Based Learning Process in Financial Markets with Application on FTSE 100 Market
Organizer of the Session: 620-363
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