We consider a monetary DSGE model featuring a borrowing constraint such that the amount of debt cannot be larger than a fraction - the debt-to-income (DTI) limit - of borrowers' labor income and the DTI limit is endogenous. The coexistence of financial amplification mechanisms warranted by this model provides a role for a specific macroprudential tool: a countercyclical DTI limit. Conditional on the pre-crisis sample and in a more recent out-of-sample period, our ex-post normative analysis shows that when this policy is implemented the cooperation between central bank and macroprudential authority in pursuing the “two instruments for two goals” strategy delivers an efficient performance in terms of macroeconomic stabilization, significantly outperforming the central bank's policy of “leaning against the wind”. This implies that a central bank should only be focused on its standard objectives (inflation and output stabilization) while financial stability be monitored by a macroprudential authority.

An adaptive and precise peak wavelength detection algorithm for fibre Bragg grating using generative adversarial network is proposed. The algorithm consists of generative model and discriminative model. The generative model generates a synthetic signal and is sampled for training using a deep neural network. The discriminative model predicts the real fibre Bragg grating signal by the calculation of the loss functions. The maxima of loss function of the discriminative signal and the minima of loss function of the generative signal are matched and the desired peak wavelength of fibre Bragg grating is determined. The proposed algorithm is verified theoretically and experimentally for a single fibre Bragg grating peak. The accuracy has been obtained as ±0.2 pm. The proposed algorithm is adaptive in the sense that any random fibre Bragg grating peak can be identified within a short wavelength range.