Lars Stentoft
Associate Professor / Joint with the Department of Statistical and Actuarial Sciences
Ph.D. University of Aarhus, Denmark, 2004
Office: SSC 4029
Telephone: 519-661-2111 Ext. 85311
Fax: 519-661-3666
E-mail: Lars.Stentoft@uwo.ca
Research Interests
Finance; Financial Econometrics; Computational Finance; Econometrics
Teaching Fields
Time Series Econometrics
Representative Publications
Letourneau, P. and L. Stentoft. (2022), ‘Simulated Greeks for American Options’, forthcoming in Quantitative Finance.
Huddleston, D. Liu, F. and L. Stentoft. (2021), ‘Intraday Market Predictability: A Machine Learning Approach’, Journal of Financial Econometrics, nbab007, (https://doi.org/10.1093/jjfinec/nbab007).
Francois, P. and L. Stentoft. (2021), ‘Smile-Implied Hedging with Volatility Risk’, Journal of Futures Markets, 41(8), 1220-1240, (https://doi.org/10.1002/fut.22191).
Liu, F. and L. Stentoft. (2021), ‘Regulatory Capital and Incentives for Risk Model Choice under Basel 3’, Journal of Financial Econometrics, 19(1), 53-96, (https://doi.org/10.1093/jjfinec/nbaa029).
Escobar, M., Rastegeri, J. and L. Stentoft. (2021), ‘Option Pricing with Conditional GARCH Models’, European Journal of Operational Research, 289(1), 350-363, (https://doi.org/10.1016/j.ejor.2020.07.002).
Rombouts, J., L. Stentoft and F. Violante. (2020), ‘Dynamics of Variance Risk Premia: A New Model for Disentangling the Price of Risk’, Journal of Econometrics, 217(2), 312-334, (https://doi.org/10.1016/j.jeconom.2019.12.006).
Rombouts, J., L. Stentoft and F. Violante. (2020), ‘Pricing Individual Stock Options using both Stock and Market Index Information’, Journal of Banking and Finance, 111, #105727, 1-16, (https://doi.org/10.1016/j.jbankfin.2019.105727).
Rombouts, J. and L. Stentoft (2015), ‘Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models’, International Journal of Forecasting, 31(3), 635-650 (https://doi.org/10.1016/j.ijforecast.2014.09.002).
Rombouts, J. and L. Stentoft (2014), ‘Bayesian Option Pricing using Mixed Normal Heteroskedasticity Models’, Computational Statistics & Data Analysis, 76, 588-605 (https://doi.org/10.1016/j.csda.2013.06.023).
Létourneau, P. and L. Stentoft (2014), ‘Refining the Least Squares Monte Carlo Method by Imposing Structure’, Quantitative Finance, 14(3), 495-507 (https://doi.org/10.1080/14697688.2013.787543).
Denault, M., J.-G. Simonato & L. Stentoft (2013), ‘A Simulation-and-Regression Approach for Stochastic Dynamic Programs with Endogenous State Variable’, Computers & Operations Research 40 (11), 2760-2769 (https://doi.org/10.1016/j.cor.2013.04.008).
Rombouts, J. and L. Stentoft. (2011), ‘Multivariate Option Pricing with Time Varying Volatility and Correlations’, Journal of Banking and Finance 35, 2267–2281 (https://doi.org/10.1016/j.jbankfin.2011.01.025).
Stentoft, L. (2008), ‘American Option Pricing Using GARCH models and the Normal Inverse Gaussian Distribution’, Journal of Financial Econometrics 6 (4), 540-582 (https://doi.org/10.1093/jjfinec/nbn013).
Stentoft, L. (2004), ‘Convergence of the Least Squares Monte Carlo Approach to American Option Valuation’, Management Science 50 (9), 1193-1203 (https://doi.org/10.1287/mnsc.1030.0155).
