The global financial crisis and its follow-up have caused a major revamp of theoretical macroeconomic models to better reflect imperfections in financial markets. Macro-models with financial frictions, in the tradition of Bernanke – Gertler – Gilchrist (1999) or Kiyotaki – Moore (1997), have gained popularity in the last years, as they address both a theoretical shortcoming of previous models and give more realistic policy conclusions. Their focus is still in the amplification of shocks through market imperfections and thus in the aftermath of a bust. In our project, we want to focus on the framework introduced by Bhattacharya – Goodhart – Tsomocos – Vardoulakis (2015) as an explanation behind the excessive credit growth and the increase in leverage during the upswing. The authors introduce agents as Bayesian learners, which update their beliefs on future outcomes based on the past and present and therefore can become over-optimistic during the boom phase, in line with the financial instability hypothesis of Minsky (1992). Our goal is then to augment two popular DSGE New Keynesian models with financial frictions with this expectations framework. We take the now popular Gertler – Karadi (2011) model of unconventional monetary policy and the MAPMOD model of the IMF (Benes – Kumhof – Laxton 2014) of macroprudential policy and introduce in them the expectations framework of Bhattacharya et al. (2015). We estimate the models and aim at validating them by replicating some of the stylised facts on financial crises, asset price booms and credit expansions as reported by the work of Schularick – Taylor (2012, 2017).