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  1. Fulvio Corsi
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portrait of Dr Fulvio Corsi

Dr Fulvio Corsi

Reader in Financial Economics

School of Arts and Social Sciences, Department of Economics

Contact Information

Contact

Visit Fulvio Corsi

D621, Rhind Building

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Postal Address

City, University of London
Northampton Square
London
EC1V 0HB
United Kingdom

About

Background

After joining the Olsen and Associates Company, who pioneered the study on high-frequency data in finance, he earned his PhD in finance at University of Lugano under the supervision of Prof. Barone-Adesi and Prof. Tim Bollerslev. He is an expert of in modelling and forecasting volatility dynamics: he devised the HAR-RV model (winning the Engle Prize 2010 for best paper published in 2007, 2008 and 2009 volumes of Journal of Financial Econometrics) which is nowadays a standard benchmark in analyzing financial volatility dynamics. He also contributed in the field of volatility measuring in the presence of microstructure noise, jump detection, correlation measuring and modelling, derivative pricing and nonlinear dynamic modelling of asset price bubble and crashes. He published on international journals as Journal of Financial Economics, Journal of Econometrics, Journal of Applied Econometrics, Journal of Business and Economic Statistics, PNAS.

Qualifications

Ph.D. in Finance (Hons), University of Lugano, Lugano (CH), 2005

MSc in Economics and Finance (Hons), Venice International University, Venice (IT), 1999

Diploma in Economics and Business (Hons), University of Pisa, Pisa (IT), 1998

Employment

Reader, City University of London 2013 - present

Assistant Professor, Ca' Foscari University of Venice (IT), 2013 - present

Postdoctoral Research Fellow, Scuola Normale Superiore di Pisa, Pisa (IT), 2012 - 2013

Postdoctoral Research Fellow, University of St. Gallen and Swiss Finance Institute, St. Gallen (CH), 2009 - 2011

Postdoctoral Research Fellow, University of Siena, Siena (IT), 2007 - 2009

Postdoctoral Research Fellow, University of Lugano, Lugano (CH), 2005 - 2007

Visiting Scholar, Duke University, NC (USA), 2004

Research

Financial Econometrics and Empirical Finance: volatility, jumps, and correlation measures with high frequency data, (pseudo) long memory models induced by heterogeneous agents, multivariate models of realized volatility, derivative pricing, models for financial bubbles and systemic risk.

Publications

Chapter

  1. Corsi, F., Audrino, F. and Renò, R. (2012). HAR Modeling for Realized Volatility Forecasting. Handbook of Volatility Models and Their Applications (pp. 363–382).

Journal Articles (18)

  1. Corsi, F., Marmi, S. and Lillo, F. (2016). When Micro Prudence Increases Macro Risk: The Destabilizing Effects of Financial Innovation, Leverage, and Diversification. OPERATIONS RESEARCH, 64(5), pp. 1073–1088. doi:10.1287/opre.2015.1464.
  2. Audrino, F., Corsi, F. and Filipova, K. (2016). Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators. Econometric Reviews, 35(2), pp. 232–256. doi:10.1080/07474938.2013.833809.
  3. Majewski, A.A., Bormetti, G. and Corsi, F. (2015). Smile from the past: A general option pricing framework with multiple volatility and leverage components. Journal of Econometrics, 187(2), pp. 521–531. doi:10.1016/j.jeconom.2015.02.036.
  4. Bormetti, G., Calcagnile, L.M., Treccani, M., Corsi, F., Marmi, S. and Lillo, F. (2015). Modelling systemic price cojumps with Hawkes factor models. Quantitative Finance, 15(7), pp. 1137–1156. doi:10.1080/14697688.2014.996586.
  5. Corsi, F., Peluso, S. and Audrino, F. (2015). Missing in Asynchronicity: A Kalman-em Approach for Multivariate Realized Covariance Estimation. Journal of Applied Econometrics, 30(3), pp. 377–397. doi:10.1002/jae.2378.
  6. Peluso, S., Corsi, F. and Mira, A. (2015). A Bayesian high-frequency estimator of the multivariate covariance of noisy and asynchronous returns. Journal of Financial Econometrics, 13(3), pp. 665–697. doi:10.1093/jjfinec/nbu017.
  7. Corsi, F. and Sornette, D. (2014). Follow the money: The monetary roots of bubbles and crashes. INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 32, pp. 47–59. doi:10.1016/j.irfa.2014.01.007.
  8. Saichev, A., Sornette, D., Filimonov, V. and Corsi, F. (2013). Bridge homogeneous volatility estimators. Quantitative Finance, 14(1), pp. 87–99. doi:10.1080/14697688.2013.819985.
  9. Corsi, F., Fusari, N. and La Vecchia, D. (2013). Realizing smiles: Options pricing with realized volatility. Journal of Financial Economics, 107(2), pp. 284–304. doi:10.1016/j.jfineco.2012.08.015.
  10. Curci, G. and Corsi, F. (2012). Discrete sine transform for multi-scale realized volatility measures. Quantitative Finance, 12(2), pp. 263–279.
  11. Corsi, F. and Renò, R. (2012). Discrete-time volatility forecasting with persistent leverage effect and the link with continuous-time volatility modeling. Journal of Business and Economic Statistics, 30(3), pp. 368–380.
  12. Corsi, F. and Audrino, F. (2012). Realized covariance tick-by-tick in presence of rounded time stamps and general microstructure effects. Journal of Financial Econometrics, 10(4), pp. 591–616.
  13. Corsi, F., Pirino, D. and Renò, R. (2010). Threshold bipower variation and the impact of jumps on volatility forecasting. Journal of Econometrics, 159(2), pp. 276–288. doi:10.1016/j.jeconom.2010.07.008.
  14. Audrino, F. and Corsi, F. (2010). Modeling tick-by-tick realized correlations. Computational Statistics and Data Analysis, 54(11), pp. 2372–2382. doi:10.1016/j.csda.2009.09.033.
  15. Corsi, F. (2009). A simple approximate long-memory model of realized volatility. Journal of Financial Econometrics, 7(2), pp. 174–196.
  16. Bianco, S., Corsi, F. and Renò, R. (2009). Intraday LeBaron effects. Proc.Natl.Acad.Sci.U.S.A., 106(28), pp. 11439–11443.
  17. Corsi, F., Mittnik, S., Pigorsch, C. and Pigorsch, U. (2008). The volatility of realized volatility. Econometric Reviews, 27(1-3), pp. 46–78.
  18. Corsi, F., Zumbach, G., Muller, U.A. and Dacorogna, M.M. (2001). Consistent high-precision volatility from high-frequency data. Economic Notes, 30(2), pp. 183–204.

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London EC1V 0HB

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