In a broader context the aim of this project is to analyse the interaction among uncertainty, asset prices, and financial shocks in the real economy and delve into their relationship. In particular, the project contributes to the extensive body of work exploring the connection between financial markets, private consumption patterns, and the real economy. Especially, we want to understand uncertainty in greater detail. One of the key objectives is to analyse the effects of negative financial shocks on both output and prices. While the recessionary impact on output is well-documented in the past literature, the influence on prices remains elusive. Additionally, the project aims to model uncertainty shocks, recognizing their complexity and their role in influencing investor behaviour, predictability, volatility, and risk premiums. Understanding uncertainty as a component of business cycles is crucial for analysing its impact on the economy. In addition to allowing non-Gaussianity of structural shocks, the project proposes the development of new statistical methods based on SVAR models. These methods aim to better identify and analyze shocks related to financial markets, incorporating nonlinear elements. Furthermore, the project plans to label shocks using narrative sign restrictions using historical records. This approach ensures clearer interpretation and comparison of results, enhancing the robustness of the findings. Our approach is rather novel in the literature since we exploit from the nature of financial markets. In fact, our model identification gains from the randomness of financial markets which makes it highly desirable. Overall, the research aims to provide deeper insights into the complex relationship between financial markets, uncertainty, and asset pricing. By improving methods for shock identification and analysis, the project seeks to offer valuable tools and perspectives for future research in this field.

2024

2027