LVFM

"Learning and volatility in financial markets: theory, experiments and empirics"

Coordinatore	UNIVERSITY COLLEGE LONDON    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	765˙000 €
EC contributo	765˙000 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2007-StG
Funding Scheme	ERC-SG
Anno di inizio	2008
Periodo (anno-mese-giorno)	2008-10-01   -   2014-09-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITY COLLEGE LONDON  Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT contact info Titolo: Dr. Nome: Antonio Cognome: Guarino Email: send email Telefono: -6796025 Fax: +44-0-207-916 2774	UK (LONDON)	hostInstitution	0.00
2	UNIVERSITY COLLEGE LONDON  Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT contact info Titolo: Mr. Nome: Michael Cognome: Browne Email: send email Telefono: 442031000000 Fax: 442078000000	UK (LONDON)	hostInstitution	0.00

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 Obiettivo del progetto (Objective)

'The project aims to study learning and volatility in financial markets. We will develop a theoretical market microstructure model to analyze how informational inefficiencies can arise in financial markets even though traders (who have non speculative reasons to trade) are allowed to buy or sell any quantity of an asset (in a continuous action space). In this theoretical framework, we will also analyze the case in which the asset value can change over time (e.g., because of shocks to the economy). We will study how learning occurs in this economy with changing fundamentals and how learning affects price volatility. This will create a bridge between the theoretical literature on learning and the empirical literature on time varying volatility (e.g., ARCH and GARCH). After developing the theoretical analyses, we will test the predictions in experiments, and proceed to a structural estimation of our models. We will run both field and laboratory experiments. The structural estimation will use transaction data in order to shed light on the process of information aggregation and volatility in different markets (e.g., more or less speculative) and different conditions (tranquil times versus financial crises).'