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The Effect of Public Sector on the Financial Sector:An NN Approach in a View of Complexity

机译:公共部门对金融部门的影响:从复杂性角度看的NN方法

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摘要

In the existing literature there are many works which use NN for forecasting the financial market. Generally, these are centred on technical analysis and/or endogenous variations.rnA different approach is based on the use of "fundamentals". In this latter approach, the effect of fiscal variables between the fundamentals is disregarded.rnWe considered both technical-endogenous and fundamental variables at the same time for the forecasting. Particularly, we used the payment due by taxpayers (estimating the daily's burden) as explicative for differences in the level of Comit30 index. The sensibility of financial behaviour to the tax burden seemed to be characterised by a '"threshold" effect; that is to say a complex - non-linear behaviour.rnFinal forecasting reached is quite good. It is possible to demonstrate that the correct consideration of exogenous shocks, together with endogenous behaviour of the financial market, could be the key passage for a correct use of neural networks in complex systems. More, the importance of a proper non-linear consideration of the interrelation between fiscal and financial sectors was highlighted.
机译:在现有文献中,有许多使用神经网络来预测金融市场的著作。通常,这些以技术分析和/或内在变化为中心。不同的方法基于“基本原理”的使用。在后一种方法中,忽略了基本面之间的财政变量的影响。我们在预测时同时考虑了技术内生变量和基本面变量。特别是,我们使用纳税人应付款(估算每日负担)来解释Comit30指数水平的差异。金融行为对税收负担的​​敏感性似乎具有“阈值”效应。这就是说复杂的非线性行为。最终的预测是相当不错的。有可能证明,对外部冲击的正确考虑以及金融市场的内在行为,可能是在复杂系统中正确使用神经网络的关键途径。此外,强调了对财政和金融部门之间的相互关系进行适当的非线性考虑的重要性。

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