1. Audrino, F., Chassot, J., Huang, C., Knaus, M., Lechner, M., and Ortega, J.-P. [2020]  How does post-earnings announcement sentiment affect firms’ dynamics? New evidence from causal machine learning. Preprint

  1. Grigoryeva, L., Hart, A., and Ortega, J.-P. [2020] Chaos on compact manifolds: Differentiable synchronizations beyond Takens. Preprint

  1. Cuchiero, C., Gonon, L., Grigoryeva, L., Ortega, J.-P., and Teichmann, J. [2020] Discrete-time signatures and randomness in reservoir computing. Preprint

  1. Grigoryeva, L., and Ortega, J.-P. [2020] Dimension reduction in recurrent networks by canonicalization. Preprint

  1. Gonon, L., Grigoryeva, L., and Ortega, J.-P. [2020] Approximation bounds for random neural networks and reservoir systems. Preprint

  1. Badescu, A., Elliott, R., Grigoryeva, L., and Ortega, J.-P. [2016] Option pricing and hedging under non-affine autoregressive stochastic volatility models. Preprint

  1. Grigoryeva, L. and Ortega, J.-P. [2016] Singular ridge regression with homoscedastic residuals: generalization error with estimated parameters. Preprint

  1. Bauwens, L., Grigoryeva, L., and Ortega, J.-P. [2015] Non-scalar GARCH models: Composite likelihood estimation and empirical model comparisons. Preprint

  1. Grigoryeva, L., Henriques, J., and Ortega, J.-P. [2015] Quantitative evaluation of the performance of discrete-time reservoir computers in the forecasting, filtering, and reconstruction of  stochastic stationary  signals. Preprint

  1. Ortega, J.-P., Pullirsch, R., Teichmann, J., and Wergieluk, J. [2009] A new approach for scenario generation in risk management. Preprint