Numerical integration-based Gaussian mixture filters for maximum likelihood estimation of asymmetric stochastic volatility models
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- Tore Selland KLEPPE & Jun YU & Hans J. SKAUG, 2009. "Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models," Working Papers 20-2009, Singapore Management University, School of Economics.
- Almut Veraart, 2011.
"How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?,"
AStA Advances in Statistical Analysis,
Springer;German Statistical Society, vol. 95(3), pages 253-291, September.
- Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
- Tore Selland Kleppe & Jun Yu & Hans J. skaug, 2011.
"Simulated Maximum Likelihood Estimation for Latent Diffusion Models,"
10-2011, Singapore Management University, School of Economics.
- Tore Selland Kleppe & Jun Yu & Hans J. Skaug, 2012. "Simulated Maximum Likelihood Estimation for Latent Diffusion Models," Working Papers 12-2012, Singapore Management University, School of Economics.
- Cai, Lili & Swanson, Norman R., 2011.
"In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008,"
Journal of Empirical Finance,
Elsevier, vol. 18(4), pages 743-764, September.
- Norman R. Swanson & Lili Cai, 2011. "In- and Out-of-Sample Specification Analysis of Spot Rate Models: Further Evidence for the Period 1982-2008," Departmental Working Papers 201102, Rutgers University, Department of Economics.
- Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.
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