Residential property loans and performance during property price booms: evidence from European banks

Understanding the performance of banks is of the utmost relevance, because of the impact of this sector on economic growth and financial stability. Of all the different assets that make up a bank portfolio, the residential mortgage loans constitute one of its main. Using the dynamic panel data method, we analyse the influence of residential mortgage loans on bank profitability and risk, using a sample of 555 banks in the European Union (EU-15), over the period from 1995 to 2008. We find that banks with larger weights of residential mortgage loans show lower credit risk in good times. This result explains why banks rush to lend on property during booms due to the positive effects it has on credit risk. The results show further that credit risk and profitability are lower during the upturn in the residential property price cycle. The results also reveal the existence of a non-linear relationship (U-shaped marginal effect), as a function of bank’s risk, between profitability and the residential mortgage loans exposure. For those banks that have high credit risk, a large exposure of residential mortgage loans is associated with higher risk-adjusted profitability, through lower risk. For banks with a moderate/low credit risk, the effects of higher residential mortgage loan exposure on its risk-adjusted profitability are also positive or marginally positive.

Residential property loans and performance during property price booms: evidence from European

Understanding the performance of banks is of the u tmost importance due to the impact the sector may have on economic growth and financial stability. Residential mortgage loans constitute a large proportion of the portfolio of many banks and are one of the key assets in the determination of performance. Using a dynamic panel model , we analyse the impact of res idential mortgage loans on bank profitability and risk , based on a sample of 555 banks in the European Union ( EU - 15 ) , over the period from 1995 to 2008. We find that banks with larger weight s in residential mortgage loans display lower credit risk in good market conditions . This result may explain why banks rush to lend on property during b ooms due to the positive effect it has on credit risk . The results also show that credit risk and profitability are lower during the upturn in the residential property cy cle. Furthermore, t he results reveal the existence of a non - linear relationship ( U - shaped marginal effect), as a function of bank’s risk, between profitability and residential mortgage exposure . For those banks that have high er credit risk, a large exposur e to residential loans is associated with increased risk - adjusted profitability, through a reduction in risk. For banks with a moderate to low credit risk, the impact of higher exposure are also positive on risk - adjusted profitability.

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

Radio link quality estimation in wireless sensor networks: a survey

Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

Characterization and performance analysis of a VDFLL GNSS receiver architecture

A non-coherent vector delay/frequency-locked loop architecture for GNSS receivers is proposed. Two dynamics models are considered: PV (position and velocity) and PVA (position, velocity, and acceleration). In contrast with other vector architectures, the proposed approach does not require the estimation of signals amplitudes. Only coarse estimates of the carrier-to-noise ratios are necessary.

Detect and pointing algorithm's performance for a planar smart antenna array: a review

An adaptive antenna array combines the signal of each element, using some constraints to produce the radiation pattern of the antenna, while maximizing the performance of the system. Direction of arrival (DOA) algorithms are applied to determine the directions of impinging signals, whereas beamforming techniques are employed to determine the appropriate weights for the array elements, to create the desired pattern. In this paper, a detailed analysis of both categories of algorithms is made, when a planar antenna array is used. Several simulation results show that it is possible to point an antenna array in a desired direction based on the DOA estimation and on the beamforming algorithms. A comparison of the performance in terms of runtime and accuracy of the used algorithms is made. These characteristics are dependent on the SNR of the incoming signal.

Design and performance evaluation of turbo FDE receivers

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Estimation of 3D shapes using active surface models

This paper addresses the estimation of surfaces from a set of 3D points using the unified framework described in [1]. This framework proposes the use of competitive learning for curve estimation, i.e., a set of points is defined on a deformable curve and they all compete to represent the available data. This paper extends the use of the unified framework to surface estimation. It o shown that competitive learning performes better than snakes, improving the model performance in the presence of concavities and allowing to desciminate close surfaces. The proposed model is evaluated in this paper using syntheticdata and medical images (MRI and ultrasound images).

Estimation of rotational frequency response functions

As it is widely known, in structural dynamic applications, ranging from structural coupling to model updating, the incompatibility between measured and simulated data is inevitable, due to the problem of coordinate incompleteness. Usually, the experimental data from conventional vibration testing is collected at a few translational degrees of freedom (DOF) due to applied forces, using hammer or shaker exciters, over a limited frequency range. Hence, one can only measure a portion of the receptance matrix, few columns, related to the forced DOFs, and rows, related to the measured DOFs. In contrast, by finite element modeling, one can obtain a full data set, both in terms of DOFs and identified modes. Over the years, several model reduction techniques have been proposed, as well as data expansion ones. However, the latter are significantly fewer and the demand for efficient techniques is still an issue. In this work, one proposes a technique for expanding measured frequency response functions (FRF) over the entire set of DOFs. This technique is based upon a modified Kidder's method and the principle of reciprocity, and it avoids the need for modal identification, as it uses the measured FRFs directly. In order to illustrate the performance of the proposed technique, a set of simulated experimental translational FRFs is taken as reference to estimate rotational FRFs, including those that are due to applied moments.

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

Radio link quality estimation is essential for protocols and mechanisms such as routing, mobility management and localization, particularly for low-power wireless networks such as wireless sensor networks. Commodity Link Quality Estimators (LQEs), e.g. PRR, RNP, ETX, four-bit and RSSI, can only provide a partial characterization of links as they ignore several link properties such as channel quality and stability. In this paper, we propose F-LQE (Fuzzy Link Quality Estimator, a holistic metric that estimates link quality on the basis of four link quality properties—packet delivery, asymmetry, stability, and channel quality—that are expressed and combined using Fuzzy Logic. We demonstrate through an extensive experimental analysis that F-LQE is more reliable than existing estimators (e.g., PRR, WMEWMA, ETX, RNP, and four-bit) as it provides a finer grain link classification. It is also more stable as it has lower coefficient of variation of link estimates. Importantly, we evaluate the impact of F-LQE on the performance of tree routing, specifically the CTP (Collection Tree Protocol). For this purpose, we adapted F-LQE to build a new routing metric for CTP, which we dubbed as F-LQE/RM. Extensive experimental results obtained with state-of-the-art widely used test-beds show that F-LQE/RM improves significantly CTP routing performance over four-bit (the default LQE of CTP) and ETX (another popular LQE). F-LQE/RM improves the end-to-end packet delivery by up to 16%, reduces the number of packet retransmissions by up to 32%, reduces the Hop count by up to 4%, and improves the topology stability by up to 47%.

Longshore Transport Estimation on Ofir Beach in Northwest Portugal: Sand-Tracer Experiment

This work aims to shed some light on longshore sediment transport (LST) in the highly energetic northwest coast of Portugal. Data achieved through a sand-tracer experiment are compared with data obtained from the original and the new re-evaluated longshore sediment transport formulas (USACE Waterways Experiment Station’s Coastal Engineering and Research Center, Kamphuis, and Bayram bulk formulas) to assess their performance. The field experiment with dyed sand was held at Ofir Beach during one tidal cycle under medium wave-energy conditions. Local hydrodynamic conditions and beach topography were recorded. The tracer was driven southward in response to the local swell and wind- and wave-induced currents (Hsb=0.75mHsb=0.75m, Tp=11.5sTp=11.5s, θb=8−12°θb=8−12°). The LST was estimated by using a linear sediment transport flux approach. The obtained value (2.3×10−3m3⋅s−12.3×10−3m3⋅s−1) approached the estimation provided by the original Bayram formula (2.5×10−3m3⋅s−12.5×10−3m3⋅s−1). The other formulas overestimated the transport, but the estimations resulting from the new re-evaluated formulas also yield approximate results. Therefore, the results of this work indicated that the Bayram formula may give satisfactory results for predicting the longshore sediment transport on Ofir Beach.

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Mat`ern models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Numerical Evaluation of Ventilation Performance in Children Day Care Centres

Modelling of ventilation is strongly dependent on the physical characteristics of the building of which precise evaluation is a complex and time consuming task. In the frame of a research project, two children day care centres (CDCC) have been selected in order to measure the envelope air permeability, the flow rate of mechanical ventilation systems and indoor and outdoor temperature. The data obtained was used as input to the computer code CONTAM for ventilation simulations. The results obtained were compared with direct measurements of ventilation flow from short term measurements with CO2 tracer gas and medium term measurements with perfluorocarbon tracer (PFT) gas decay method. After validation, in order to analyse the main parameters that affect ventilation, the model was used to predict the ventilation rates for a wide range of conditions. The purpose of this assessment was to find the best practices to improve natural ventilation. A simple analytical method to predict the ventilation flow rate of rooms is also presented. The method is based on the estimation of wind effect on the room through the evaluation of an average factor and on the assessment of relevant cross section of gaps and openings combined in series or in parallel. It is shown that it may be applied with acceptable accuracy for this type of buildings when ventilation is due essentially to wind action.

Customer Lifetime Value: a framework for application in the insurance industry - Building a Business Process to Generate and Maintain an Automatic Estimation Agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management