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The Input-Output Scheme to Model Financial Fluctuations in Peruvian Stock Markets

机译:秘鲁股票市场中金融波动模型的投入产出方案

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In this paper we use the well-known Input-Output scheme to model the temporal behavior of the ISBVL (ndice selectivo de la bolsa de valores de Lima) before and after the 2011 general elections in Peru. Because data exhibites abnormalities between January and July, dynamic instabilities are identified. We claim that a phase transition is manifested before and after the polls as consequence of accumulated uncertainties. Indeed, as observed on the ISBVL versus time curve, a strongly nonlinear region is identified over the time where the run-off took place. This phenomenon as reflected on the ISBVL leads to establish a phase transition from a linear to a nonlinear regime according to the behavior of the data. Furthermore, we noted that the nonlinear region is plagued by intrinsic fluctuations, noise and random events. In order to understand the phenomenology and dynamics associated a mathematical methodology in terms of convolution integrals based on input-output processes is presented. In concrete the transfer function corresponding to the nonlinear region is reconstructed. The exposed methodology in this note can be alternatively used for fitting those ISBVL curves featured by strong fluctuations and therefore to make predictions to some extent within a systematic error.
机译:在本文中,我们使用众所周知的“投入产出”方案对ISBVL(利马的选民)在2011年秘鲁大选前后的时间行为进行建模。由于数据在1月至7月之间显示异常,因此可以确定动态不稳定性。我们声称,由于不确定性的累积,在民意测验前后都出现了相变。实际上,从ISBVL随时间变化的曲线上可以看出,在径流发生的时间范围内可以识别出一个强烈的非线性区域。 ISBVL上反映的这种现象导致根据数据的行为建立从线性状态到非线性状态的相变。此外,我们注意到非线性区域受到固有波动,噪声和随机事件的困扰。为了理解现象学和动力学,提出了一种基于输入-输出过程的卷积积分方面的数学方法。具体而言,重构对应于非线性区域的传递函数。本说明中公开的方法可以替代地用于拟合那些以强烈波动为特征的ISBVL曲线,因此可以在系统误差内进行某种程度的预测。

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