4 resultados para Nonrandom two-liquid model

em RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal


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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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This paper studies the effects of monetary policy on mutual fund risk taking using a sample of Portuguese fixed-income mutual funds in the 2000-2012 period. Firstly I estimate time-varying measures of risk exposure (betas) for the individual funds, for the benchmark portfolio, as well as for a representative equally-weighted portfolio, through 24-month rolling regressions of a two-factor model with two systematic risk factors: interest rate risk (TERM) and default risk (DEF). Next, in the second phase, using the estimated betas, I try to understand what portion of the risk exposure is in excess of the benchmark (active risk) and how it relates to monetary policy proxies (one-month rate, Taylor residual, real rate and first principal component of a cross-section of government yields and rates). Using this methodology, I provide empirical evidence that Portuguese fixed-income mutual funds respond to accommodative monetary policy by significantly increasing exposure, in excess of their benchmarks, to default risk rate and slightly to interest risk rate as well. I also find that the increase in funds’ risk exposure to gain a boost in return (search-for-yield) is more pronounced following the 2007-2009 global financial crisis, indicating that the current historic low interest rates may incentivize excessive risk taking. My results suggest that monetary policy affects the risk appetite of non-bank financial intermediaries.

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This study investigates three questions related to medical practice variation. First, it tests whether average length of stay across Portuguese National Health Service hospitals varies when controlling for differences in patients’ characteristics. Second, it looks at hospital-level characteristics in order to find out whether these are able to explain differences in average length of stay across hospitals. Finally, it proposes a best practice average length of stay for each of the six episodes of care analyzed. To perform the analysis, administrative data from the Diagnosis-Related groups’ data set for the year of 2012 was used. A replication of a hierarchical two-stage model with hospital fixed effects was carried out. The results show that after taking patients’ characteristics into account, variation in average length of stay across hospitals exists. This variation cannot be explained by hospital-level characteristics.

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A Work Project, presented as part of the requirements for the Award of a Master’s Double Degree in Finance from Maastricht University and NOVA – School of Business and Economics