Examinando por Autor "Valle, Mauricio A."

Mostrando 1 - 6 de 6
  • Miniatura
    Ítem
    Análisis de canasta de mercado en supermercados mediante mapas auto-organizados
    (Universidade Federal do Paraná, 2021-11-08) Cordero, Joaquín; Bolt, Alfredo José; Valle, Mauricio A.
    Introducción: Una cadena importante de supermercados de la zona poniente de la capital de Chile, necesita obtener información clave para tomar decisiones. Esta información se encuentra disponible en las bases de datos, pero necesita ser procesada debido a la complejidad y cantidad de información, lo que genera una dificultad a la hora de visualizar. Método: Para este propósito, se ha desarrollado un algoritmo que utiliza redes neuronales artificiales, aplicando el método SOM de Kohonen. Para llevarlo a cabo, se han debido seguir ciertos procedimientos claves, como preparar la información, para luego utilizar solo los datos relevantes a las canastas de compra de la investigación. Luego de efectuado el filtrado, se tiene que preparar el ambiente de programación en Python para adaptarlo a los datos de la muestra, y luego proceder a entrenar el SOM con sus parámetros fijados luego de resultados de pruebas. Resultado: El resultado del SOM obtiene la relación entre los productos que más se compraron, posicionándolos topológicamente cerca, para conformar promociones y bundles, para que el retail mánager tome en consideración. Conclusión: En base a esto, se han hecho recomendaciones sobre canastas de compra frecuentes a la cadena de supermercados que ha proporcionado los datos utilizados en la investigación.
  • Miniatura
    Ítem
    The backbone of the financial interaction network using a maximum entropy distribution
    (World Scientific Publishing Company, 2022-10-19) Valle, Mauricio A.; Urbina, Felipe
    We modeled the stocks of the financial system as a set of many interacting like spins derived from binary daily returns. From the empirical observation of these returns, we used a Boltzmann machine to infer a distribution of states equivalent to a maximum entropy distribution. This model describes the interaction couplings between each stock pair in the system, which can be considered a complete network with N(N-1)/2 couplings. We then engage in a coupling removal process to find a critical graph that can describe the observed states of the system with the minimum number of edges. We interpret the critical graph as the backbone of the system, and it allows us to evaluate the importance of markets in their relation to others in the system. We also found that the structure of this critical graph is highly variable over time and appears to be dependent on the level of entropy of the system.
  • Miniatura
    Ítem
    Cheating modulated by time pressure in the matrix task
    (Springer Nature, 2022-02-11) Ferreira Campos, Vítor; Valle, Mauricio A.; Oliveira Bueno, José Lino
    No studies have investigated dishonesty during a time pressure extension greater than that of seconds. The objective was to determine if cheating groups report having completed a larger number of matrices than non-cheating groups in the Matrix Task, under different time pressures. In the experiment, participants were required to solve as many matrices as possible within a given time frame and then received a monetary reward for each correctly solved matrix. Participants of each cheating and non-cheating conditions were divided into three groups depending on the time pressure to solve the problems: 2.5, 5, and 10 min. Participants in the cheating group stated that they had solved more matrices than those of the non-cheating group, both under the 5-min pressure. However, the same did not happen under the time pressures of 2.5 and 10 min, indicating that time pressure modulates dishonest behavior in different ways, depending on the extent of the time pressure evaluated.
  • Miniatura
    Ítem
    Equity market description under high and low volatility regimes using maximum entropy pairwise distribution
    (MDPI, 2021-10-05) Valle, Mauricio A.; Lavín, Jaime F.; Magner, Nicolás S.
    The financial market is a complex system in which the assets influence each other, causing, among other factors, price interactions and co-movement of returns. Using the Maximum Entropy Principle approach, we analyze the interactions between a selected set of stock assets and equity indices under different high and low return volatility episodes at the 2008 Subprime Crisis and the 2020 COVID-19 outbreak. We carry out an inference process to identify the interactions, in which we implement the a pairwise Ising distribution model describing the first and second moments of the distribution of the discretized returns of each asset. Our results indicate that second-order interactions explain more than 80% of the entropy in the system during the Subprime Crisis and slightly higher than 50% during the COVID-19 outbreak independently of the period of high or low volatility analyzed. The evidence shows that during these periods, slight changes in the second-order interactions are enough to induce large changes in assets correlations but the proportion of positive and negative interactions remains virtually unchanged. Although some interactions change signs, the proportion of these changes are the same period to period, which keeps the system in a ferromagnetic state. These results are similar even when analyzing triadic structures in the signed network of couplings
  • Miniatura
    Ítem
    Modeling synchronization risk among sustainable exchange trade funds: a statistical and network analysis approach
    (MDPI, 2022-10-01) Magner, Nicolás; Lavín, Jaime F.; Valle, Mauricio A.
    We evaluate the environment, society, and corporate governance rating (ESG rating) contribution from a new perspective; the highest ESG rating mitigates the impact of unexpected change in the implied volatility on the systemic stock market risk. For this purpose, we use exchange- traded funds (ETF) classified by their ESG rating into quartiles to estimate the synchronization as a proxy by systemic risk. Then, for each ETF quartile, we study the effect of the implied volatility over the synchronization. Our study is the first to model sustainable ETFs’ synchronization by combining econometric modeling and network methods, including 100 ETFs representing 80% of the global ETF market size between 2013 and 2021. First, we find that a higher ESG rating mitigates the effect of implied volatility over ETF synchronization. Surprisingly, the effect is the opposite in the case of ETFs with lower ESG ratings, where an increase in the volatility expectation increases the synchronization. Our study depicts the effect of sustainable ETFs on lessening the systemic risk due to returns synchronization, this being a novel contribution of this asset class. Finally, this paper offers extensions to deepen the contribution of other asset classes of ETFs in terms of their synchronization behavior and impact on risk management and financial performance.
  • Miniatura
    Ítem
    A network-based approach to study returns synchronization of stocks: The case of global equity markets
    (Hindawi, 2021-11-09) Lavín, Jaime F.; Valle, Mauricio A.; Magner, Nicolás S.
    The synchronization in financial markets has increased during the rise of global markets. Nevertheless, global shocks provoke high levels of returns synchronization that jeopardize market stability. Using correlation-based networks, regressions, and VAR models, we measure and estimate the effect of global synchronization on the world equity markets of North America, Latin America, Europe, Asia, and Oceania between July 2001 and April 2020. We find that our measure of global stock synchronization is dynamic over time, its minimums coincide with significant financial shocks, and it shrinks to its minimum levels, indicating that the returns of global markets are moving in a synchronized way. Also, it is a significant and positive factor of regional synchronization. Regional markets react heterogeneously to global synchronization shocks suggesting both local and global factors are sources of synchronization. Our work helps market participants who need to measure, monitor, and manage the synchronization of returns in a parsimonious, dynamic, and empirically tractable way. Our evidence highlights the necessity of including synchronization as a risk factor to assess the decision-making criteria of a broad range of market participants ranging from regulators to investors. To policy-makers, governments, and central banks, our work is a call to incorporate events of high global synchronization into the radar of hazards of the whole market stability.