Search-for-yield in Portuguese fixed-income mutual funds and monetary policy

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.

A business model for an entertainment solution to the in-vehicle infotainment industry

The evolution of mobile technologies that make its presence something ubiquitous and the idea of internet connectivity in every device, often called as the Internet of Things, are pushing a disruption in other industry: the in-vehicle infotainment (IVI). Many companies are trying to enter this new industry that comprises information (weather, news, location services) and entertainment solutions in just one. For that purpose, company X developed a new entertainment solution and intends to bring it to market. This Work Project focuses on creating a business model and an entry mode for the company.

Structural transformation in the product space: Patterns and implications

Product fundamentals are essential in explaining heterogeneity in the product space. The scope for adapting and transferring capabilities into the production of different goods determines the speed and intensity of the structural transformation process and entails dissimilar development opportunities for nations. Future specialization patterns become then partly determined by the current network of products’ relatedness. Building on previous literature, this paper explicitly compares methodological concepts of product connectivity to conclude in favor of the density measure we propose combined with the Revealed Relatedness Index (RRI) approach presented by Freitas and Salvado (2011). Overall, RRI specifications displayed more consistent behavior when different time horizons are equated.

Fractional state space analysis of economic systems

This paper examines modern economic growth according to the multidimensional scaling (MDS) method and state space portrait (SSP) analysis. Electing GDP per capita as the main indicator for economic growth and prosperity, the long-run perspective from 1870 to 2010 identifies the main similarities among 34 world partners’ modern economic growth and exemplifies the historical waving mechanics of the largest world economy, the USA. MDS reveals two main clusters among the European countries and their old offshore territories, and SSP identifies the Great Depression as a mild challenge to the American global performance, when compared to the Second World War and the 2008 crisis.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

Solution processed quantum dot photodetectors

To find sustainable solutions for the production of energy, it is necessary to create photovoltaic technologies that make every photon count. To pursue this necessity, in the present work photodetectors of zinc oxide embedded with nano-structured materials, that significantly raise the conversion of solar energy to electric energy, were developed. The novelty of this work is on the development of processing methodologies in which all steps are in solution: quantum dots synthesis, passivation of their surface and sol-gel deposition. The quantum dot solutions with different capping agents were characterized by UVvisible absorption spectroscopy, spectrofluorimetry, dynamic light scattering and transmission electron microscopy. The obtained quantum dots have dimensions between 2 and 3nm. These particles were suspended in zinc acetate solutions and used to produce doped zinc oxide films with embedded quantum dots, whose electric response was tested. The produced nano-structured zinc oxide materials have a superior performance than the bulk, in terms of the produced photo-current. This indicates that an intermediate band material should have been produced that acts as a photovoltaic medium for solar cells. The results are currently being compiled in a scientific article, that is being prepared for possible submission to Energy and Environmental Science or Nanoscale journals.