1,721,175 research outputs found

    Neural networks for large financial crashes forecast

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    The aim of this work is to examine how neural networks can be used for solving the problem of the forecast of large financial crashes due to the presence of speculative bubbles. Some microeconomic theories have been developed for the explanation of a bubble due to a cooperation among the investors. This behaviour can be detected by the presence of self-similarity in the indexes series near the crash time leading to a differential equation and thus to a dynamical system description, well suitable by a neural network approach. © 2004 Elsevier B.V. All rights reserved

    Productivity and costs for growing firms in presence of technological renewal processes

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    Wide empirical analyses investigated the size and growth rate distribution of business firms, providing a relevant empirical support to economic theory. We rely on such analyses and on studies on technology renewal costs and productivity, in order to draw sufficient conditions for the optimality of firms’ profit with respect to time. The relationships that hold among productivity, costs of renewal and growth rates of the companies at the optimal profit time are shown and suggestions for firms’ policies are proposed

    Microeconomic modeling of financial time series with long term memory

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    In this paper we fix a microeconomic model of exchange rates and we give the explicit relation between model's parameters and its long memory properties. This avoids long numerical calibration procedures and allows to build the model with the parameters suitable for the required long memory degree
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