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Vânia, S., Laureano, L. & Curto, J. (2013). Interbank payment flows in Portugal: an empirical analysis. 5th International IFABS Conference.
V. G. Silva et al., "Interbank payment flows in Portugal: an empirical analysis", in 5th Int. IFABS Conf., Nottingham, 2013
@misc{silva2013_1734881709298, author = "Vânia, S. and Laureano, L. and Curto, J.", title = "Interbank payment flows in Portugal: an empirical analysis", year = "2013", howpublished = "Outro", url = "http://www.ifabsconference.com//ifabsconference2013/" }
TY - CPAPER TI - Interbank payment flows in Portugal: an empirical analysis T2 - 5th International IFABS Conference AU - Vânia, S. AU - Laureano, L. AU - Curto, J. PY - 2013 CY - Nottingham UR - http://www.ifabsconference.com//ifabsconference2013/ AB - Using daily data from the payments processed through the Portuguese payment system operated by Banco de Portugal, we assess the impact of calendar effects, as well as institutional and financial variables, on the value, number and average value of interbank payments. The analysis aims to provide insights on the pattern of interbank payments processed in the Portuguese real-time gross settlement system, before and after the beginning of the recent financial crisis. In fact, understanding interbank payment flows is a very important step towards the smooth functioning of payment systems and, therefore, the maintenance of financial stability. Through the examination of static and dynamic econometric models, we conclude that calendar effects, namely the day of the week and month of the year, have a notable positive impact, while the holidays in Portugal and bank holidays in the United States of America have a negative effect before and after the beginning of the recent financial crisis. We also conclude that the pattern of interbank payments is considerably affected by institutional and financial factors (such as the settlement of the main refinancing operations and of the futures traded in the Portuguese stock exchange and the evolution of the interest rates under analysis) after the beginning of the recent financial crisis. We also verify that the models have a better forecasting accuracy on the period before the beginning of the recent financial crisis. ER -