Smiles all around: FX joint calibration in a multi-Heston model

We introduce a novel multi-factor Heston-based stochastic volatility model, which is able to reproduce consistently typical multi-dimensional FX vanilla markets, while retaining the (semi)-analytical tractability typical of affine models and relying on a reasonable number of parameters. A successful joint calibration to real market data is presented together with various in- and out-of-sample calibration exercises to highlight the robustness of the parameters estimation. The proposed model preserves the natural inversion and triangulation symmetries of FX spot rates and its functional form, irrespective of choice of the risk-free currency. That is, all currencies are treated in the same way.Comment: Journal of Banking and Finance. Accepte

Geographic accessibility analysis and evaluation of potential changes to the public transportation system

Modern public transportation systems are required to be more efficient. The efficiency and the quality of the service is based on several aspects, such as availability, frequency, travel speed, reliability and safety. Stop spacing system is a significant part of the public transport service design and it deeply affects its efficiency. In particular, the stop spacing system has consequences on the accessibility, access and egress time, travel speed, transit time and the operating costs. The purpose of this study is to propose potential changes to the surface public transportation system in the City of Milan to create a more efficient service. In particular, the study aims to analyze what happens if the stops spacing system changes, increasing the distance between the bus stops. The model developed in the thesis was created working on the distance between consecutive stops and the introduction of three new potential stop spacing systems, with a target distance between the stops set to 400, 500 and 600 meters. The model is mainly based on three different steps: (i) select the stops that could not be moved or eliminated because of the importance of their location; (ii) select the stops that could be moved or eliminated; (iii) relocate the stops considering the target distance between the stops (400, 500 and 600 meters). According to the model, eliminating some of the stops could have a positive effect on travel times and operating cost reductions. In particular, changing the stop spacing system eliminating an average of 1.7, 2.5 and 3.4 stops per route for the three model scenarios (respectively 400, 500 and 600 meters of target distance between the stops), would decrease the travel time by respectively, 3.0%, 4.4% and 5.7%. Results also indicate that in an optimal situation, with traffic light priority and public transport fast tracks for public transport vehicles, the travel time could decrease by 3.9%, 5.8% and 7.6%. The operating costs analyses indicate that the three different scenarios could reduce the annual cost per km by about 0.5%, 1% and 2%. The evaluation of the effects of the proposed potential changes to the surface public transport stop spacing system was also made analyzing the mobility demand and the accessibility. In particular, the network analyses made on the mobility demand show that the travel time averagely decreases by 1.6%, 1.9% and 2.2%, the transportation time decreases by 2.0%, 3.7% and 5.0% and the pedestrian time changes by -0.4%, +2.8% and +5.2% for the three model scenarios. In terms of minutes, the pedestrian time is balanced with a more efficient surface public transport system. The raster analyses made on the accessibility, using a model called PTAL, shows that the accessibility level didn’t change for 94.2%, 91.1%, 89.9% of the cells and that it is lowered just by 1.0%, 1.5% and 1.9% of the cells. The model developed in the study is merely theoretical and it generally gives positive and interesting results in terms of efficiency. However, to be able to understand its real efficiency it is necessary to make other studies on a closer scale.In a society which aims to make a major step in the direction of sustainability, it is necessary to promote efficient alternative modes of travel in the automobile-dominated urban travel markets. In this study, potential changes to the surface public transportation system in the City of Milan are evaluated. Surface public transportation system can be considered unattractive because of its lack of efficiency. One of the possible reasons that the service is not efficient is the placement of the stops. Stop spacing is a significant part of the public transport service design as it affects passengers’ walking time as well as the operating speed of a route, which affects both transit time and operating costs. A densely spaced public transport station obviously improves the geographic coverage and the accessibility, but it also increases in-vehicle time and supply costs. On the contrary, eliminating service stops speeds up the system and reduces the operating costs. In the study, new stop spacing models are evaluated with the purpose to get the service more efficient by increasing the distance between the stops. Working on a broad scale, the model has been created for three different scenarios, with a target distance between the stops set to 400, 500 and 600 meters. Results indicate that eliminating some surface public transport stops (an average of 1.7, 2.5 and 3.4 stops per route for the three model scenarios) could reduce the travel time spent on the service by, respectively, 3.0%, 4.4% and 5.7%. Results also indicate that the travel time could decrease more in an optimal situation, with traffic light priority and public transport fast tracks for public transport vehicles. The operating costs analyses show that the three different scenarios could reduce the annual cost per km till about 2%. In the study, the analyses made on the mobility demand and on the accessibility were used to evaluate potential effects on the reality of the proposed changes to the surface public transport stop spacing system. In particular, it is evaluated that, in the proposed scenarios, the accessibility level does not change for the majority of the areas and that the areas where the accessibility level improved are more than the ones where it is lowered. The model also has positive results on the mobility. In particular, simulating about 1300 urban movements, allowed to evaluate how the pedestrian time, the time spent on the service and the total travel time could potentially change. In particular, the total travel time and the time spent on board decrease and they decrease the more the distance between consecutive stops increases. On the contrary, the pedestrian time increases the more the distance between the stops increases, but a longer pedestrian time is balanced by a shorter time spent on board

Categorical Properties of Italian Verbs in Written Word Recognition

The study addresses the issue of lexical representation of inflected Italian verbal forms. Linguistic and experimental data suggest the existence of differences in lexical processing of verbs depending on morphological factors. We aimed at verifying whether lexical organization of verbs in the mental lexicon is affected by information about the grammatical category of mood. Two unmasked priming lexical decision experiments were carried out with different SOAs. Primetarget pairs composed of inflected verbs sharing or not mood information were compared. A number of control conditions were also included. The results show that information about mood becomes available in the early stages of lexical processing of verbs, but it is likely to induce priming effects a few hundred milliseconds after its pre-activation. This pattern provides evidence that mood is represented in the input component(s) and is an organizational criterion for verbal forms in the lexicon

Magnetic superlattice and finite-energy Dirac points in graphene

We study the band structure of graphene's Dirac-Weyl quasi-particles in a one-dimensional magnetic superlattice formed by a periodic sequence of alternating magnetic barriers. The spectrum and the nature of the states strongly depend on the conserved longitudinal momentum and on the barrier width. At the center of the superlattice Brillouin zone we find new Dirac points at finite energies where the dispersion is highly anisotropic, in contrast to the dispersion close to the neutrality point which remains isotropic. This finding suggests the possibility of collimating Dirac-Weyl quasi-particles by tuning the doping

Chiral spin channels in curved graphene pnpn junctions

We show that the chiral modes in circular graphene $pn$ junctions provide an advantage for spin manipulation via spin-orbit coupling compared to semiconductor platforms. We derive the effective Hamiltonian for the spin dynamics of the junction's zero modes and calculate their quantum phases. We find a sweet spot in parameter space where the spin is fully in-plane and radially polarized for a given junction polarity. This represents a shortcut to singular spin configurations that would otherwise require spin-orbit coupling strengths beyond experimental reach.Comment: 21 pages with 9 figure

Dispersive Drumhead States in Nodal-Line Semimetal Junctions

We consider a smooth interface between a topological nodal-line semimetal and a topologically trivial insulator (e.g., the vacuum) or another semimetal with a nodal ring of different radius. Using a low-energy effective Hamiltonian including only the two crossing bands, we show that these junctions accommodate a two-dimensional zero-energy level and a set of two-dimensional dispersive bands, corresponding to states localized at the interface. We characterize the spectrum, identifying the parameter ranges in which these states are present, and highlight the role of the nodal radius and the smoothness of the interface. We also suggest material-independent ways to detect and identify these states, using optical conductivity and infrared absorption spectroscopy in magnetic field.Comment: 19 pages, 13 figure

Multiple magnetic barriers in graphene

We study the behavior of charge carriers in graphene in inhomogeneous perpendicular magnetic fields. We consider two types of one-dimensional magnetic profiles, uniform in one direction: a sequence of N magnetic barriers, and a sequence of alternating magnetic barriers and wells. In both cases, we compute the transmission coefficient of the magnetic structure by means of the transfer matrix formalism, and the associated conductance. In the first case the structure becomes increasingly transparent upon increasing N at fixed total magnetic flux. In the second case we find strong wave-vector filtering and resonant effects. We also calculate the band structure of a periodic magnetic superlattice, and find a wave-vector-dependent gap around zero-energy.Comment: 9 pages, 18 figure

Modelling and recognition of protein contact networks by multiple kernel learning and dissimilarity representations

Multiple kernel learning is a paradigm which employs a properly constructed chain of kernel functions able to simultaneously analyse different data or different representations of the same data. In this paper, we propose an hybrid classification system based on a linear combination of multiple kernels defined over multiple dissimilarity spaces. The core of the training procedure is the joint optimisation of kernel weights and representatives selection in the dissimilarity spaces. This equips the system with a two-fold knowledge discovery phase: by analysing the weights, it is possible to check which representations are more suitable for solving the classification problem, whereas the pivotal patterns selected as representatives can give further insights on the modelled system, possibly with the help of field-experts. The proposed classification system is tested on real proteomic data in order to predict proteins' functional role starting from their folded structure: specifically, a set of eight representations are drawn from the graph-based protein folded description. The proposed multiple kernel-based system has also been benchmarked against a clustering-based classification system also able to exploit multiple dissimilarities simultaneously. Computational results show remarkable classification capabilities and the knowledge discovery analysis is in line with current biological knowledge, suggesting the reliability of the proposed system