Lars Stentoft
Lars Stentoft is Associate Professor at Department of Economics, University of Western Ontario. He earned his PhD degree in economics from Aarhus University in 2004. Stentoft’s field of research is concerned with financial econometrics where he has published in journals such as Management Science, Journal of Empirical Finance, and Review of Derivatives Research.
Stentoft, L. (2014). Value Function Approximation or Stopping Time Approximation: A Comparison of Two Recent Numerical Methods for American Option Pricing using Simulation and Regression. Journal of Computational Finance, 65-120. http://search.proquest.com.ez.statsbiblioteket.dk:2048/docview/1629026628/63E809A7971247ACPQ/1?accountid=14468
Stentoft, L. & Wang, S. (2020). Consistent and Efficient Dynamic Portfolio Replication with Many Factors. The Journal of Portfolio Management, 46(2), 79-91. https://doi.org/10.3905/jpm.2019.1.118
Stentoft, L. (2019). Efficient Numerical Pricing of American Call Options using Symmetry Arguments. Journal of Risk and Financial Management, 12(2), 59. https://doi.org/10.3390/jrfm12020059
Rombouts, J. & Stentoft, L. (2014). Bayesian Option Pricing using Mixed Normal Heteroskedasticity Models. Computational Statistics & Data Analysis, 588-605. https://doi.org/10.1016/j.csda.2013.06.023
Rombouts, J., Stentoft, L. & Violante, F. (2014). The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options. International Journal of Forecasting, 30(1), 78-98. https://doi.org/10.1016/j.ijforecast.2013.07.006
Rombouts, J. V. K., Stentoft, L. & Violante, F. (2020). Variance swap payoffs, risk premia and extreme market conditions. Econometrics and Statistics, 13, 106-124. adv. onlinepublikation. https://doi.org/10.1016/j.ecosta.2019.05.003
Rombouts, J. V. K., Stentoft, L. & Violante, F. (2020). Pricing individual stock options using both stock and market index information. Journal of Banking and Finance, 111, artikel 105727. https://doi.org/10.1016/j.jbankfin.2019.105727
Rombouts, J. V. K., Stentoft, L. & Violante, F. (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
Létourneau, P. & Stentoft, L. (2014). Refining the least squares Monte Carlo method by imposing structure. Quantitative Finance, Volume 14(3), 495-507. https://doi.org/10.1080/14697688.2013.787543
Grynkiv, G. & Stentoft, L. (2018). Stationary Threshold Vector Autoregressive Models. Journal of Risk and Financial Management, 11(3), artikel 45. https://doi.org/10.3390/jrfm11030045
Denault, M., Simonato, J-G. & Stentoft, L. (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
Boyer, M. M., Mejza, J. & Stentoft, L. (2014). Measuring Longevity Risk: An Application to the Royal Canadian Mounted Police Pension Plan. Risk Management and Insurance Review, 17(1), 37-59. https://doi.org/10.1111/rmir.12018
Boyer, M. M. & Stentoft, L. (2013). If we can simulate it, we can insure it: An application to longevity risk management. Insurance: Mathematics and Economics, 52(1), 35-45. https://doi.org/10.1016/j.insmatheco.2012.10.003
Boyer, M. M. & Stentoft, L. (2017). Yes We Can (Price Derivatives on Survivor Indices). Risk Management and Insurance Review, 20(1), 37-62. https://doi.org/10.1111/rmir.12073
