RICERCA ITALIANA     

Programmi di ricerca simili:

• 1 - Progettazione di mercati e modelli ad agenti di comportamento di trading
• 2 - Analisi econometrica dell'interdipendenza, stabilizzazione e contagio nei mercati reali e finanziari
• 3 - I “mercati della CO2” e il loro impatto sui prezzi dell’elettricità: analisi teorica ed empirica
• 4 - Struttura, funzionamento e integrazione dei mercati elettrici europei e ruolo dei mercati finanziari ad essi collegati: modelli teorici e analisi empiriche
• 5 - Modelli di breve e lungo termine per il settore elettrico liberalizzato: decisioni di investimento, equilibri di mercato e comportamenti di offerta
• 6 - Analisi e simulazione di modelli dinamici con aspettative eterogenee
• 7 - L’importanza delle imperfezioni nei mercati finanziari per la stabilità, la crescita e le politiche economiche.
• 8 - Mercati finanziari, del credito e del lavoro in modelli ciclici per l'analisi delle politiche economiche. Teoria ed evidenza empirica.
• 9 - Rischio ed ambiguità: nuove teorie ed applicazioni all'analisi dei mercati ed al disegno delle istituzioni
• 10 - Modelli econometrici per l'analisi dell'integrazione finanziaria ed economica nell'Unione Europea Allargata

Classificazione scientifico-disciplinare

• Area scientifico disciplinare: Scienze economiche e statistiche
  • METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE
• Area scientifico disciplinare: Ingegneria industriale e dell'informazione
  • ELETTROTECNICA
  • INGEGNERIA ECONOMICO-GESTIONALE
  • SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI

Classificazione geografica

• Regione: Sicilia

Bibliografia

[1] W.B. Arthur, J. Holland, B. Le Baron, R. Palmer, and P. Taylor. Asset Pricing Under Endogenous Expectations in Artificial Stock Market. In W.B. Arthur, S. Durlauf, and D. Lane, editors, The Economy as an Evolving Complex System II. Addison-Wesley, Reading, MA, 1997.

[2] P. Bak, M. Paczuski, and M. Shubik. Price Variation in a Stock Market with Many Agents. Physica A, 246:430–453, 1997.

[3] W. Brock, C. Hommes, and F. Wagener. Evolutionary Dynamics in Financial Markets with Many Trader Types. Working Paper 7, Wisconsin
Madison - Social Systems, University Of Wisconsin Madison, 2001.

[4] J.Y. Campbell, A.W. Lo, and A.C. MacKinlay. The Econometrics of
Financial Markets. Princeton University Press, Princeton NJ, 1997.

[5] N. Chan, B. Le Baron, A. Lo, and T. Poggio. Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders. Technical Memorandum 1646, MIT Artificial Intelligence Laboratory, 1998.

[6] S.H. Chen, T. Lux, and M. Marchesi. Testing for Non-Linearity Structure in an Artificial Market. Journal of Economic Behavior and Organization, 46:327–342, 2001.

[7] C. Chiarella and T. He. Asset Price and Wealth Dynamics under Heterogeneous Expetations. Quantitative Finance, 1:509–526, 2001.

[8] C. Chiarella and G. Iori. A Simulation Analysis of the Microstructure of Double Auction Markets. Quantitative Finance, 2:346–353, 2002.

[9] A. Consiglio, F. Cocco, and S.A. Zenios. The Value of Integrative
Risk Management for Insurance Products with Minimum Guarantees. Journal of Risk Finance, 2(3):1–11, Spring 2001.

[10] A. Consiglio, F. Cocco, and S.A. Zenios. www.Personal Asset Allocation. Interface, 2003. to appear.

[11] A. Consiglio and S.A. Zenios. Designing Portfolios of Financial Products via Integrated Simulation and Optimization Models. Operations
Research, 47(2):195–208, March–April 1999.

[12] A. Consiglio and S.A. Zenios. Integrated Simulation and Optimization Models for Tracking International Fixed Income Indices. Mathematical Programming, 89(2):311–339, January 2001.

[13] M.G. Daniels, J.D. Farmer, L. Gillemot, G. Iori, and E. Smith. Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process. Physical Review Letters, 90, 2003.

[14] R. Dembo, A. Aziz, D. Rosen, and M. Zerbs. Mark To Future - A
Framework for Measuring Risk and Reward. Algorithmics Publications,
May 2000.

[15] R.F. Engle and A.J. Patton. What Good is a Volatility Model? Quantitative Finance, 1(2):237–245, 2001.

[16] D. Farmer and S. Joshi. The Price Dynamics of Common Trading
Strategies. Journal of Economic Behavior and Organization, 49:149–
171, 2002.

[17] S. Focardi, S. Cincotti, and M. Marchesi. Self–Organized Criticality and Market Crashes. Journal of Economic Behaviour and Organization, 49(2):241–267, 2002.

[18] D. Friedman. Evolutionary Games in Economics. Econometrica,
47:637–666, 1991.

[19] R.A. Gallant, P.E. Rossi, and G. Tauchen. Stock Prices and Volume. The Review of Financial Studies, 5:199–242, 1992.

[20] A.E. Goodhart and M. O’Hara. High Frequency Data in Financial
Markets: Issues and Applications. Journal of Empirical Finance, 4:73–
114, 1997.

[21] D.M. Guillame, M.M. Dacorogna, R.R. Dav´e, U.A. M¨uller, R.B. Olsen, and O.V. Pictet. From the Bird’s Eye to the Microscope: A Survey of New Stylized Facts of Intra–Daily Foreign Exchange Markets. Finance and Stochastics, 1:95–129, 1997.

[22] G. Iori, M.G. Daniel, J.D. Farmer, L. Gillemot, S. Krishnamurthy, and E. Smith. An Analysis of Price Impact Function in Order Driven Markets. Physica A, 324:146–151, 2003.

[23] K. Kahneman and A. Tversky. Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47:263–291, 1979.

[24] J.M. Karpoff. The relation between Price Changes and Trading Volume: A Survey. Journal of Financial and Quantitative Analysis, 22:109–126, 1987.

[25] B. Le Baron. Building Financial Markets with Artificial Agents: Desired Goals and Present Techniques. In G. Karakoulas, editor, Computational Markets. MIT Press, 1999.

[26] B. Le Baron. Empirical Regularities from Interacting Long and Short Memory Investors in an Agent-Based Stock Market. IEEE Transaction on Evolutionary Computation, 5:442–455, 2001.

[27] M. Li Calzi and P. Pellizzari. Fundamentalists Clashing over the Book: A Study of Order-Driven Stock Markets. Quantitative Finance, 3:470–480, 2003.

[28] F. Lillo, J.D Farmer, and R.N. Mantegna. Master Curve for Price-
Impact Function. Nature, 421:129–130, 2003.

[29] F. Lillo and R.N. Mantegna. Power Law Relaxation in a Complex
System: Omori Law After a Financial Market Crash. Physical Review
E, 68, 2003. 016119.

[30] T. Lux and M. Marchesi. Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market. Nature, 397:498–500, 1999.

[31] T. Lux and M. Marchesi. Volatility clustering in Financial Markets: A Micro-Simulation of Interacting Agents. International Journal of Theoretical and Applied Finance, 3:675–702, 2000.

[32] S. Maslov. A Simple Model of a Limit Order-driven Market. Physica
A, 278:571–578, 2000.

[33] S. Miccichè, G. Bonanno, F. Lillo, and R.N. Mantegna. Volatility in Financial Markets: Stochastic Models and Empirical Results. Physica
A, 314:756–761, 2002.

[34] U.A. Muller, M.M. Dacorogna, R.B. Olsen, O.V. Pictet, M. Schwarz,
and C. Morgenegg. Statistical Study of Foreign Exchange Rates, Empirical Evidence of a Price Scaling Law, and Intraday Analysis. Journal of Banking and Finance, 14:1189–1208, 1990.

[35] A. Pagan. The Econometrics of Financial Markets. Journal of Empirical Finance, 3:15–102, 1996.

[36] O.V. Pictet, M.M. Dacorogna, U.A. M¨uller, R.B. Olsen, and J.R.Ward. Real–Time Trading Models for Foreign Exchange Rates. Neural Network World, 2(6):713–744, 1992.

[37] M. Raberto, S. Cincotti, S. Focardi, and M. Marchesi. Agent-Based
Simulation of a Financial Market. Physica A, 299:319–327, 2001.

[38] B.R. Routledge. Adaptive Learning in Financial Markets. The Review of Financial Studies, 12:1165–1202, 1999.

[39] L. Russo. Flussi e Riflussi. Indagine sull’Origine di una Teoria Scientifica. Feltrinelli, Milano, 2003.

[40] R. Thaler. Advances in Behavioral Finance. Russel Sage Foundation, New York, 1993.

Parole Chiave

MERCATI ARTIFICIALI; MICROSTRUTTURA DEL MERCATO; SIMULAZIONE DI MERCATI FINANZIARI; EFFICIENZA INFORMATIVA; DINAMICA DEI PREZZI; OTTIMIZZAZIONE DI PORTAFOGLIO; AGENTI ETEROGENEI; SOFTWARE OPEN-SOURCE