Orbit simulations of fast-ion transport induced by externally applied 3D magnetic perturbations in the ASDEX Upgrade tokamak.

Externally applied 3D magnetic perturbations break the symmetry of the magnetic field in a tokamak and have an impact on the transport of fast-ions, i.e. suprathermal ions. It was shown that the variation of the toroidal canonical momentum gives a measured for the radial transport of fast-ions. In this thesis, experiments of the ASDEX Upgrade tokamak were analyzed in terms of the radial transport of fast-ions. Simulations using the Monte Carlos orbit-following code ASCOT were carried out in order to study the impact of externally applied 3D magnetic perturbations on the topology of the orbits and to quantify the radial fast-ion transport. The results show that when the magnetic perturbations are applied a drift appears (changing the trajectory of the particle) and the transport created depends on the initial pitch angle, radius and energy of the particles and the equilibrium. Also, it is confirmed that the strong correlation between fast-ion losses and impurity toroidal rotation is related to the trapped-passing boundary .Universidad de Sevilla. Máster Universitario en Física Nuclea

On understanding and interpretation in mathematics: An integrative overview

For decades, understanding has been considered as a basic theme of interest and a research object in Mathematics Education. In this theoretical overview paper we present a integrative framework for organizing the diversity of results that emerge from the different studies on mathematical understanding and its interpretation. The proposal is applied onto a representation of relevant literature that has arise in the area over the last two decades. With this overview we seek to provide an useful reference for: (a) advancing towards a better insight of understanding in mathematics, (b) establishing the specific limitations and open questions that demarcate the boundaries of understanding and interpretation in mathematics, and (c) orienting its future study using a shared base of consolidated knowledge

Non-exact present value relations

One of the most cornmonly used and, at the same time. rejected models in finance and macroeconomics is the exact present value model (PVM), where a variable Yt is expressed as the expected value at time t of the sum of discounted future values of another variable Xt. This paper generalizes the PVM by making it non-exact (NEPVM) in a simple way, allowing us to study situations with time varying discount factors, transitory deviations from the exact PVM, as well as situations with correlated market returns. The proposed NEPVM satisfies all the equilibrium conditions the exact PVM does, but at the same time it is more robust in the sense that rejections produced by the standard volatility and cross-equation restriction tests are not enough to reject the NEPVM. The paper presents the new variance bounds and cross-equation restrictions implied by the NEPVM and it shows how to test them. This paper also shows how to discriminate between the exact PVM and the NEPVM by testing for a deeper level of cointegration: multicointegration. The paper finished by analyzing empirically the cases of stock prices and dividens. short-and long-term interest rates and farmland prices. Although the exact PVM is rejected in the first two examples, as the literature has largely reported, we are unable to reject the NEPVM. This fact, together with the theoretical results contained in the paper, suggests that the pro po sed NEPVM could be compatible with sorne of the empírical findings in the literature

Semiparametric inference in correlated long memory signal plus noise models

This paper proposes an extension of the log periodogram regression in perturbed long memory series that accounts for the added noise, also allowing for correlation between signal and noise, which represents a common situation in many economic and financial series. Consistency (for d < 1) and asymptotic normality (for d < 3/4) are shown with the same bandwidth restriction as required for the original log periodogram regression in a fully observable series, with the corresponding gain in asymptotic efficiency and faster convergence over competitors. Local Wald, Lagrange Multiplier and Hausman type tests of the hypothesis of no correlation between the latent signal and noise are also proposed.long memory, signal plus noise, semiparametric inference, log-periodogram regression

Gaussian Semiparametric Estimation in Long Memory in Stochastic Volatility and Signal Plus Noise Models

This paper considers the persistence found in the volatility of many financial time series by means of a local Long Memory in Stochastic Volatility model and analyzes the performance of the Gaussian semiparametric or local Whittle estimator of the memory parameter in a long memory signal plus noise model which includes the Long Memory in Stochastic Volatility as a particular case. It is proved that this estimate preserves the consistency and asymptotic normality encountered in observable long memory series and under milder conditions it is more efficient than the estimator based on a log-periodogram regression. Although the asymptotic properties do not depend on the signal-to-noise ratio the finite sample performance rely upon this magnitude and an appropriate choice of the bandwidth is important to minimize the influence of the added noise. I analyze the effect of the bandwidth via Monte Carlo. An application to a Spanish stock index is finally included.long memory, stochastic volatility, semiparametric estimation, frequency domain

Semiparametric estimation in perturbed long memory series

The estimation of the memory parameter in perturbed long memory series has recently attracted attention motivated especially by the strong persistence of the volatility in many financial and economic time series and the use of Long Memory in Stochastic Volatility (LMSV) processes to model such a behaviour. This paper discusses frequency domain semiparametric estimation of the memory parameter and proposes an extension of the log periodogram regression which explicitly accounts for the added noise, comparing it, asymptotically and in finite samples, with similar extant techniques. Contrary to the non linear log periodogram regression of Sun and Phillips (2003), we do not use a linear approximation of the logarithmic term which accounts for the added noise. A reduction of the asymptotic bias is achieved in this way and makes possible a faster convergence in long memory signal plus noise series by permitting a larger bandwidth. Monte Carlo results confirm the bias reduction but at the cost of a higher variability. An application to a series of returns of the Spanish Ibex35 stock index is finally included.long memory, stochastic volatility, semiparametric estimation

Structural Changes in the Transmission Mechanism of Monetary Policy in Mexico: A Non-linear VAR Approach

In this paper we present a first approach to the study of the transformation in the transmission mechanism of monetary policy that has taken place in Mexico in recent years. For this purpose, we use a non-linear VAR model that allows for regime shifts. The comparison of the different regimes identified leads to the following main findings: a) there was a major structural change in the transmission mechanism around January 2001, date that coincides with the formal adoption of the inflation targeting framework; b) after this change, fluctuations in the real exchange rate have had smaller effects on the process of price formation, the formation of inflation expectations and the nominal interest rate; c) also, there have been stronger reactions of the nominal interest rate to increases in the output gap and the rate of inflation; and d) the movements of the nominal interest rate have a more effective influence on the real exchange rate and the rate of inflation.Monetary policy, Mexico, Monetary transmission mechanism