El mercado cambiario y los contenidos en la prensa: un análisis empírico

The links between the foreign Exchange market and the attention level allocated in a newspaper are analyzed. The evidence shows that higher values for the lagged attention index are associated to a lower level of mean devaluation and to higher volatility levels. These links are stronger in times of high volatility. Beyond linear associations, the attention index is found to have high predictive value for large variations in the exchange rate. The documented patterns are consistent with instances of exchange rate overreaction and with the coordination of actions through public signals.Se evalúan vínculos entre la evolución del mercado cambiario argentino y el nivel de atención asignado a este mercado en un medio gráfico durante el período 2002-2012. Las estimaciones indican que mayores valores de los rezagos del índice de atención están asociados a una menor tasa de devaluación esperada y a aumentos en las medidas de volatilidad. Estos vínculos son más intensos en períodos con mayor volatilidad. Más allá de las asociaciones lineales, se documenta que el índice tiene importante capacidad predictiva para el caso de grandes movimientos en el tipo de cambio. La evidencia es consistente con instancias de sobrerreacción del tipo de cambio y de coordinación de acciones en base a señales públicas

Analysis of financial time series using TDA: theoretical and empirical results

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2019, Director: Carles Casacuberta i Josep Vives i Santa Eulàlia[en] Topological Data Analysis (TDA) is a recently developed tool designed to study the geometry of finite data sets. In these notes, we describe the theory of persistent homology, which is the background underlying the application of TDA. Our work is both practical and theoretical. We describe in detail persistence landscape functions, which are a means of visualizing persistent homology, and study some of their properties while deriving a few novel results. From a statistical approach, our theoretical work corroborates the use of TDA to measure changes in the underlying distribution of a data set. We employ TDA to analyze the log returns of four main financial European indices throughout 2005–2015, comparing our results with the ones in the paper Topological Data Analysis of Financial Time Series: Landscapes of Crashes [19]. As in this article, we observe that the norms of persistence landscapes show strong growth prior to substantial financial instability

Predicting emotion in speech: a Deep Learning approach using Attention mechanisms

Speech Emotion Recognition (SER) has recently become a popular field of research because of its implications in human-computer interaction. In this study, the emotional state of the speaker is successfully predicted by using Deep Convolutional Neural Networks to automatically extract features from the spectrogram of a speech signal. Parting from a baseline model that uses a statistical approach to pooling, an alternative method is proposed by incorporating Attention mechanisms as a pooling strategy. Additionally, multi-task learning is explored as an improvement over the baseline model by assigning language recognition as an auxiliary task. The final results show a remarkable improvement in classification accuracy in respect to previous more conventional techniques, in particular Gaussian Mixture Models and i-vectors, as well as a notable improvement in performance of the proposed Attention mechanisms over statistical pooling.En las últimas décadas, Speech Emotion Recognition (SER), o el reconocimiento de emociones por voz, ha generado un fuerte interés en el ámbito del tratamiento del habla por sus implicaciones en la interacción humano-computador. En este trabajo, se consigue reconocer el estado emocional del hablante mediante redes convolucionales profundas, capaces de extraer de manera automática características contenidas en el espectrograma de la señal de voz. Partiendo de un modelo que utiliza análisis estadístico para pooling, se propone una estrategia alternativa para mejorar el rendimiento incorporando mecanismos de Atención. Como mejora añadida, se explora el campo del multi-task learning definiendo el reconocimiento del idioma como tasca auxiliar para el modelo. Los resultados obtenidos reflejan una mejora substancial en la precisión comparado con anteriores técnicas más convencionales, concretamente Gaussian Mixture Models y i-vectors, y una mejora notable en la precisión de los mecanismos de Atención respecto al pooling estadístico.En les últimes dècades, Speech Emotion Recognition (SER), o el Reconeixement d'Emocions per Veu, ha generat fort interès en l'àmbit del tractament de la parla per a les implicacions que presenta en la interacció humà-computador. En aquest treball s'aconsegueix reconèixer l'estat emocional del parlant utilitzant xarxes neuronals profundes que extreuen de manera automàtica característiques contingudes en l'espectrograma del senyal de veu. Partint d'un model que utilitza anàlisi estadística per a pooling, es proposa una estratègia alternativa per a millorar el rendiment incorporant mecanismes d'Atenció. Com a millora afegida, s'explora el camp del mulit-task learning definint el reconeixement de l'idioma com a tasca auxiliar per al model. Els resultats finals obtinguts reflecteixen una millora substancial en la precisió comparat amb anteriors mètodes, concretament respecte Gaussian Mixture Models i i-vectors, i una millora notable en la precisió dels mecanismes d'Atenció respecte el pooling estadístic

A scalable architecture for quantum computation with molecular nanomagnets

A proposal for a magnetic quantum processor that consists of individual molecular spins coupled to superconducting coplanar resonators and transmission lines is carefully examined. We derive a simple magnetic quantum electrodynamics Hamiltonian to describe the underlying physics. It is shown that these hybrid devices can perform arbitrary operations on each spin qubit and induce tunable interactions between any pair of them. The combination of these two operations ensures that the processor can perform universal quantum computations. The feasibility of this proposal is critically discussed using the results of realistic calculations, based on parameters of existing devices and molecular qubits. These results show that the proposal is feasible, provided that molecules with sufficiently long coherence times can be developed and accurately integrated into specific areas of the device. This architecture has an enormous potential for scaling up quantum computation thanks to the microscopic nature of the individual constituents, the molecules, and the possibility of using their internal spin degrees of freedom.Comment: 27 pages, 6 figure

Special Issue 'Spin Crossover (SCO) Research'

This special issue, entitled "Spin Crossover (SCO) Research", illustrates the current relevance of a focused topic, which is in turn highly versatile. Indeed, the collection of papers presented constitutes a sampler that shows the topical importance of this area by attracting the interest of many top researchers and how it is approached under a multidisciplinary perspective

Variations to Spin Crossover in [FexZn(1−x)(Me1,3bpp)2(ClO4)2] molecular alloys examined by Magnetometry and Single Crystal X-Ray Diffraction

Spin crossover (SCO) active solid solutions with formula [FexZn1-x(Me1,3bpp)2](ClO4)2 (x = 0.10, 0.15, 0.22, 0.33, 0.41, 0.48, 0.56 and 0.64, Me1,3bpp is a bis-pyrazolylpyridine) and the complex [Zn(Me1,3bpp)2](ClO4)2 have been prepared and characterized by single crystal X-ray diffraction. The structural data and the powder diffraction patterns of all the compounds have been compared with the reported isostructural molecular crystal [Fe(Me1,3bpp)2](ClO4)2. Increasing amounts of Zn diminishes monotonically the cooperativity of the SCO of the parent Fe(II) complex (T1/2=183 K) and cause a decrease of T1/2 in line with the negative chemical pressure exerted by the Zn(II) complexes on the Fe(II) lattice. The gradual variation of the magnetic properties as the composition changes are paralleled by the evolution of the structural parameters at the molecular, intermolecular and crystal lattice scales. Thermal trapping of a portion of the Fe(II) centers of these alloys by quenching the crystals to 2 K unveils that, upon warming, the temperature of relaxation of the metastable states is almost constant for all compositions

Controlled Heterometallic Composition in Linear Trinuclear [LnCeLn] Lanthanide Molecular Assemblies.

The combination of two different β-diketone ligands facilitates the size-controlled assembly of pure heterometallic [LnLn'Ln] linear compounds thanks to two different coordination sites present in the molecular scaffold. [HoCeHo], [ErCeEr], and [YbCeYb] analogues are presented here and are characterized both in the solid state and in solution, demonstrating the selectivity of this unique method to produce heterometallic 4f molecular entities

Designed Polynuclear Lanthanide Complexes for Quantum Information Processing

The design of dissymmetric organic ligands featuring combinations of 1,3-diketone and 2,6-diacetylpyridine coordination pockets has been exploited to produce dinuclear and trinuclear lanthanide-based coordination compounds. These molecules exhibit two or more non-equivalent Ln ions, most remarkably enabling the access to well-defined heterolanthanide compositions. The site-selective disposition of each metal ion within the molecular entities allows the study of each centre individually as a spin-based quantum bit, affording unparalleled versatility for quantum gate design. The inherent weak interaction between the Ln ions permits the performance of multi-qubit quantum logical operations realized through their derived magnetic states, or implementing quantum-error correction protocols. The different studies performed to date on these systems are revised, showing their vast potential within spin-based quantum information processing

El mercado cambiario y los contenidos en la prensa: un análisis empírico

Se evalúan vínculos entre la evolución del mercado cambiario argentino y el nivel de atención asignado a este mercado en un medio gráfico durante el período 2002-2012. Las estimaciones indican que mayores valores de los rezagos del índice de atención están asociados a una menor tasa de devaluación esperada y a aumentos en las medidas de volatilidad. Estos vínculos son más intensos en períodos con mayor volatilidad. Más allá de las asociaciones lineales, se documenta que el índice tiene importante capacidad predictiva para el caso de grandes movimientos en el tipo de cambio. La evidencia es consistente con instancias de sobrerreacción del tipo de cambio y de coordinación de acciones en base a señales públicas