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Efficient drift parameter estimation for ergodic solutions of backward SDEs

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  • Teppei Ogihara
  • Mitja Stadje

Abstract

We derive consistency and asymptotic normality results for quasi‐maximum likelihood methods for drift parameters of ergodic stochastic processes observed in discrete time in an underlying continuous‐time setting. The special feature of our analysis is that the stochastic integral part is unobserved and nonparametric. Additionally, the drift may depend on the (unknown and unobserved) stochastic integrand. Our results hold for ergodic semi‐parametric diffusions and backward SDEs. Simulation studies confirm that the methods proposed yield good convergence results.

Suggested Citation

  • Teppei Ogihara & Mitja Stadje, 2024. "Efficient drift parameter estimation for ergodic solutions of backward SDEs," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(3), pages 1181-1205, September.
    • Handle: RePEc:bla:scjsta:v:51:y:2024:i:3:p:1181-1205
    DOI: 10.1111/sjos.12709
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    References listed on IDEAS

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    4. Wing Fung Chong & Ying Hu & Gechun Liang & Thaleia Zariphopoulou, 2019. "An ergodic BSDE approach to forward entropic risk measures: representation and large-maturity behavior," Finance and Stochastics, Springer, vol. 23(1), pages 239-273, January.
    5. N. El Karoui & S. Peng & M. C. Quenez, 1997. "Backward Stochastic Differential Equations in Finance," Mathematical Finance, Wiley Blackwell, vol. 7(1), pages 1-71, January.
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