Measuring firms’ default probabilities with imperfect information

This dissertation aims to estimate default probabilities in an imperfect information setting. This is achieved through the implementation of a model that considers creditors cannot observe the firm asset values directly. Instead, they receive periodic information coming from accounting reports that can be imperfect. The dataset considered covers 18 non-financial companies that belong to the Euro STOXX 50, between 2010 and 2020. Evidence was found that probabilities of default overall behave monotonically when it comes to the degree of data inaccuracy. In periods marked by extreme events, such as the European sovereign debt crisis and the covid 19 pandemic, it is possible to observe a wider impact in the probabilities of default, as the assumption of the degree of accounting noise increases. Lastly, comparing the results to the default probabilities implied by Standard & Poor’s credit ratings, it is possible to conclude that the model’ results are underestimating the probabilities of default. On absolute terms, the difference between the model default probabilities and the ones implied by credit ratings, ranges between 0.46% and 0.75%.Esta tese tem como objetivo estimar as probabilidades de falência num cenário de informação imperfeita. Isto é conseguido através da implementação de um modelo que considera que os credores não conseguem observar diretamente os valores dos ativos da empresa. Em vez disso, os investidores recebem informações periódicas provenientes de relatórios contabilísticos que podem ser imperfeitos. O conjunto de dados considerado abrange 18 empresas não financeiras que pertencem ao Euro STOXX 50, entre 2010 e 2020. Os resultados obtidos por este estudo sugerem que as probabilidades de falência em geral comportam-se de forma monótona relativamente ao grau de imprecisão dos dados. Em períodos marcados por eventos extremos, tal como a crise europeia da dívida soberana e a pandemia causada pelo covid-19, é possível observar um impacto mais significativo nas probabilidades de falência à medida que se aumenta a hipótese relativa ao grau de ruído contabilístico. Finalmente, comparando os resultados com as probabilidades de falência implicadas pelas classificações de crédito elaboradas pela agência Standard & Poor’s, é possível concluir que os resultados do modelo estão a subestimar as probabilidades de incumprimento, variando em termos absolutos, entre 0,46% a 0,75% das implicadas pelas classificações de crédito

Magnetic field into multifunctional materials: magnetorheological, magnetostrictive and magnetocaloric

Society is facing serious challenges towards achieving highly efficient utilization of materials and devices. Magnetoactive lightweight materials, such as magnetorheological, magnetostrictive and magnetocaloric materials are attracting increasing interest once they allow a high number of applications such as energy generation, conversion, storage, sensing and actuation, as well as in the biomedical field. In this chapter, the latest research and development in multifunctional lightweight magnetorheological, magnetostrictive and magnetocaloric materials is summarized and discussed in the scope of different application areas. Furthermore, it will be also illustrated the unique functions of inorganic nanomaterials to improve performance of organic materials, as well as combination of the functions of nanomaterials into a device. Final remarks and future perspectives allow to look into a “magnetoactive crystal ball” aiming to foresee what will/should happen in this fascinating research field.The authors thank the FCT- Fundação para a Ciência e Tecnologia- for financial support in the framework of the Strategic Funding UID/FIS/04650/2019 and under project PTDC/BTM-MAT/28237/2017 and PTDC/EMD-EMD/28159/2017. P. Martins thanks FCT for the contract under the Stimulus of Scientific Employment, Individual Support – 2017 Call (CEECIND/03975/2017). The authors acknowledge funding by the Spanish Ministry of Economy and Competitiveness (MINECO) through the project MAT2016-76039-C4-3-R (AEI/FEDER, UE) and from the Basque Government Industry and Education Department under the ELKARTEK, HAZITEK and PIBA (PIBA-2018- 06) programs, respectively. Funding from the European Union’s Horizon 2020 Programme for Research, ICT-02-2018 - Grant agreement no. 824339 – WEARPLEX is also acknowledged