Estimating and forecasting generalized fractional Long memory stochastic volatility models

In recent years fractionally differenced processes have received a great deal of attention due to its flexibility in financial applications with long memory. This paper considers a class of models generated by Gegenbauer polynomials, incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the statistical properties of the new model, suggest using the spectral likelihood estimation for long memory processes, and investigate the finite sample properties via Monte Carlo experiments. We apply the model to three exchange rate return series. Overall, the results of the out-of-sample forecasts show the adequacy of the new GLMSV model.

Short-term Load Forecasting Using Neural Network For Future Smart Grid Application

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

A Matrix PRNG with S-Box Output Filtering

We describe a modification to a previously published pseudorandom number generator improving security while maintaining high performance. The proposed generator is based on the powers of a word-packed block upper triangular matrix and it is designed to be fast and easy to implement in software since it mainly involves bitwise operations between machine registers and, in our tests, it presents excellent security and statistical characteristics. The modifications include a new, key-derived s-box based nonlinear output filter and improved seeding and extraction mechanisms. This output filter can also be applied to other generators.

Use of an Inverse Method for Time Series to Estimate the Dynamics of and Management Strategies for the Box Jellyfish Carybdea marsupialis

Frequently, population ecology of marine organisms uses a descriptive approach in which their sizes and densities are plotted over time. This approach has limited usefulness for design strategies in management or modelling different scenarios. Population projection matrix models are among the most widely used tools in ecology. Unfortunately, for the majority of pelagic marine organisms, it is difficult to mark individuals and follow them over time to determine their vital rates and built a population projection matrix model. Nevertheless, it is possible to get time-series data to calculate size structure and densities of each size, in order to determine the matrix parameters. This approach is known as a “demographic inverse problem” and it is based on quadratic programming methods, but it has rarely been used on aquatic organisms. We used unpublished field data of a population of cubomedusae Carybdea marsupialis to construct a population projection matrix model and compare two different management strategies to lower population to values before year 2008 when there was no significant interaction with bathers. Those strategies were by direct removal of medusae and by reducing prey. Our results showed that removal of jellyfish from all size classes was more effective than removing only juveniles or adults. When reducing prey, the highest efficiency to lower the C. marsupialis population occurred when prey depletion affected prey of all medusae sizes. Our model fit well with the field data and may serve to design an efficient management strategy or build hypothetical scenarios such as removal of individuals or reducing prey. TThis This sdfsdshis method is applicable to other marine or terrestrial species, for which density and population structure over time are available.

Transport across two interacting quantum dots: Bulk Kondo, Kondo box, and molecular regimes

We analyze the transport properties of a double quantum dot device with both dots coupled to perfect conducting leads and to a finite chain of N noninteracting sites connecting both of them. The interdot chain strongly influences the transport across the system and the local density of states of the dots. We study the case of a small number of sites, so that Kondo box effects are present, varying the coupling between the dots and the chain. For odd N and small coupling between the interdot chain and the dots, a state with two coexisting Kondo regimes develops: the bulk Kondo due to the quantum dots connected to leads and the one produced by the screening of the quantum dot spins by the spin in the finite chain at the Fermi level. As the coupling to the interdot chain increases, there is a crossover to a molecular Kondo effect, due to the screening of the molecule (formed by the finite chain and the quantum dots) spin by the leads. For even N the two Kondo temperatures regime does not develop and the physics is dominated by the usual competition between Kondo and antiferromagnetism between the quantum dots. We finally study how the transport properties are affected as N is increased. For the study we used exact multiconfigurational Lanczos calculations and finite-U slave-boson mean-field theory at T=0. The results obtained with both methods describe qualitatively and also quantitatively the same physics.

Forecasting Elections with High Volatility

This article uses data from the social survey Allbus 1998 to introduce a method of forecasting elections in a context of electoral volatility. The approach models the processes of change in electoral behaviour, exploring patterns in order to model the volatility expressed by voters. The forecast is based on the matrix of transition probabilities, following the logic of Markov chains. The power of the matrix, and the use of the mover-stayer model, is debated for alternative forecasts. As an example of high volatility, the model uses data from the German general election of 1998. The unification of two German states in 1990 caused the incorporation of around 15 million new voters from East Germany who had limited familiarity and no direct experience of the political culture in West Germany. Under these circumstances, voters were expected to show high volatility.

Y-box binding protein 1 (YB-1) relevance in estrogen receptor-positive (ER+) breast cancer

Tese de mestrado, Biologia Molecular e Genética, Universidade de Lisboa, Faculdade de Ciências, 2016

The end of chocolate box-style integration? EU-Swiss relations after the referendum. CEPS Commentaries, 28 February 2014

Surveying the landscape following the Swiss referendum on February 9th, Adam Łazowski observes that once Swiss voters are deprived of the benefits of the EU internal market, they may come to appreciate that their days of cherry-picking from among EU policies are over. This might present the EU with a golden opportunity to press for a comprehensive framework agreement with Switzerland that would simplify the existing regime and provide for a uniform institutional set-up. He concludes, however, that what both sides cannot avoid is a frank discussion about free movement of persons, noting that that dossier will be crucial for any future steps that will be taken by the EU and the Swiss authorities.