Artículos de Revistas

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https://repositorio.uft.cl/handle/20.500.12254/2372

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Examinando Artículos de Revistas por Autor "Valle, Mauricio A."

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  • Miniatura
    Ítem
    The backbone of the financial interaction network using a maximum entropy distribution
    (World Scientific Publishing Company, 2022-10-19) Valle, Mauricio A.
    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
    Equity market description under high and low volatility regimes using maximum entropy pairwise distribution
    (MDPI, 2021-10-05) Valle, Mauricio A.
    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