4,386 research outputs found
Portfolio optimization in cryptocurrencies: a comparison of deep reinforcement learning and traditional approaches
Cryptocurrencies have become appealing investment options in recent years because of their
high potential returns. This asset class emerged as a unique investment opportunity with
distinguishing characteristics such as decentralized nature and uncorrelation with other assets.
Investing in this product, however, has become a hazardous venture due to its extreme volatility
and unpredictable price swings. As a result, a portfolio optimization is an essential tool for
investors seeking to reduce risk while aiming for high returns. This thesis studies the Deep
Reinforcement Learning models applied to cryptocurrency portfolio optimization compared to
traditional methodologies like Markowitz's and rudimentary equally weighted portfolios
Equilibrium mergers in a composite industry
This industry is formed by single-component producers whose components are combined to create composite goods. When a given firm has the possibility of merging with either a complement or a substitute good producer, its equilibrium choice depends on the degree of product differentiation in the composite good market. A merger between complements, which allows for mixed bundling, only happens when composite goods are very differentiated. Private incentives do not always go along with social interests and the equilibrium merger can differ from the socially optimal merger. After a merger, outsiders have also the opportunity to react and merge to other outsiders or to join the previous merge.merger, composite goods, substitutes, complements, pricing strategies, countermerger
Viabilidad de la recolección mecánica del pimiento de pimentón: Ensayos de campo.
La mecanización integral del cultivo del pimiento de pimentón pasa por la mecanización de la recolección. En este trabajo se muestran los resultados obtenidos al ensayar dos máquinas de judía verde sobre el cultivo sembrado a 20 cm y a 40 cm. Los resultados muestran la posibilidad de recoger mecánicamente este cultivo aunque serán necesarios mayor número de ensayos
Analysis of the Inland Port Regionalization Process in Spain
AbstractThe aim of this paper is to analyse and compare the ability of the main Spanish containers ports to penetrate into their inland territory along the last decade. To achieve this goal we firstly identify the inland origin of the container cargo by considering the location of the Spanish companies generating those flows in the peninsula. Then we determine the distribution of flows among the considered ports from 2000 to 2010, setting the boundaries of their hinterlands along that period. Finally we use two indexes to assess the evolution of these hinterlands in a complementary way: by their scope and their homogeneity.Furthermore, considering that the inter-port distribution of the traffic can change according to their composition, we repeat the analysis in a disaggregate way; that is, separately for each one of the main flows (by volume) of the Spanish foreign trade on the basis of the Combined Nomenclature Clasification.The main results show that the port of Valencia is the one whose hinterland has better evolved: by increasing its scope and by reducing its dependency both geographical as by type of flow. They also highlight that the main centres generating the maritime container flows are closer to this port than to the rest. Also these results allow us to conclude that this port regionalization process has not been oblivious to its economic environment but positively influenced by it
Refined Isogeometric Analysis for fluid mechanics and electromagnetism
Starting from a highly continuous isogeometric analysis discretization, we introduce hyperplanes that partition the domain into subdomains and reduce the continuity of the discretization spaces at these hyperplanes. As the continuity is reduced, the number of degrees of freedom in the system grows. The resulting discretization spaces are finer than standard maximal continuity IGA spaces. Despite the increase in the number of degrees of freedom, these finer spaces deliver simulation results faster with direct solvers than both traditional finite element and isogeometric analysis for meshes with a fixed number of elements. In this work, we analyze the impact of continuity reduction on the number of Floating Point Operations (FLOPs) and computational times required to solve fluid flow and electromagnetic problems with structured meshes and uniform polynomial orders. Theoretical estimates show that for sufficiently large grids, an optimal continuity reduction decreases the computational cost by a factor of . Numerical results confirm these theoretical estimates. In a 2D mesh with one million elements and polynomial order equal to five, the discretization including an optimal continuity pattern allows to solve the vector electric field, the scalar magnetic field, and the fluid flow problems an order of magnitude faster than when using a highly continuous IGA discretization. 3D numerical results exhibit more moderate savings due to the limited mesh sizes considered in this work
Determinación espectrofotométrica de la evolución del color de frutos durante la maduración post-recolección.
Se busca con este objetivos basados en variación presentan a lo de frutos. trabajo la obtención de criterios acuellas longitudes de onda que más largo de la maduración post-recolección Se ha seguido la ¡evolución de dos variedades de pera ("Blanquilla" y "Decana de Comice") y dos de manzana ("Golden Delicious" y "Starking") durante el periodo de maduración post recolección. Se han tomado muestras periódicas de cinco frutos de cada variedad y de cada uno de ellos, sobre la piel, se ha obtenido una curva espectrofotométrica y otra de su primera derivada mediante un espectrofotómetro Perkin-Elmer 555 dotado de una esfera integradora. El espectro estudiado abarca desde 340 hasta 800 nanómetros, es decir, el visible. Las curvas obtenidas han sido sometidas a tratamiento estadístico y a partir de los resultados derivados del mismo se han elegido un grupo de longitudes de onda para someterlas a análisis discriminante. A partir del mismo se establecen los criterios que mejor discriminan la variación de los frutos a lo largo de la maduración, toara cada variedad ensayada
Energy-norm-based and goal-oriented automatic hp adaptivity for electromagnetics: Application to waveguide Discontinuities
The finite-element method (FEM) enables the use of adapted meshes. The simultaneous combination of h (local variations in element size) and p (local variations in the polynomial order of approximation) refinements, i.e., hp-adaptivity, is the most powerful and flexible type of adaptivity. In this paper, two versions of a fully automatic hp-adaptive FEM for electromagnetics are presented. The first version is based on minimizing the energy-norm of the error. The second, namely the goal oriented strategy, is based on minimizing the error of a given (user-prescribed) quantity of interest. The adaptive strategy delivers exponential convergence rates for the error, even in the presence of singularities. The hp adaptivity is presented in the context of 2-D analysis of H -plane rectangular waveguide discontinuities. Stabilized variational formulations and H(curl) FEM discretizations in terms of quadrilaterals of variable order of approximation supporting anisotropy and hanging nodes are used. Comparison of energy-norm and goal-oriented hp-adaptive strategies in the context of waveguiding problems is provided. Specifically, the scattering parameters of the discontinuity are used as goal
Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model
Every artist has a creative process that draws inspiration from previous
artists and their works. Today, "inspiration" has been automated by generative
music models. The black box nature of these models obscures the identity of the
works that influence their creative output. As a result, users may
inadvertently appropriate, misuse, or copy existing artists' works. We
establish a replicable methodology to systematically identify similar pieces of
music audio in a manner that is useful for understanding training data
attribution. A key aspect of our approach is to harness an effective music
audio similarity measure. We compare the effect of applying CLMR and CLAP
embeddings to similarity measurement in a set of 5 million audio clips used to
train VampNet, a recent open source generative music model. We validate this
approach with a human listening study. We also explore the effect that
modifications of an audio example (e.g., pitch shifting, time stretching,
background noise) have on similarity measurements. This work is foundational to
incorporating automated influence attribution into generative modeling, which
promises to let model creators and users move from ignorant appropriation to
informed creation. Audio samples that accompany this paper are available at
https://tinyurl.com/exploring-musical-roots.Comment: 14 pages + references. Under conference revie
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