Dynamics of financial time series in an inhomogeneous framework

In this paper we provide a microeconomic model to investigate the long term memory of financial time series of one share. In the framework we propose, each trader selects a volume of shares to trade and a strategy. Strategies differ for the proportion of fundamentalist/chartist evaluation of price. The share price is determined by the aggregate price. The analyses of volume distribution give an insight of imitative structure among traders. The main property of this model is t the functional relation between its parameters at the micro and macro level. This allows an immediate calibration of the model to the long memory degree of the time series under examination, therefore opening the way to the understanding the emergence of stylized facts of the market through opinion aggregation

Companies' decisions for profit maximization: a structural model

Huge analyses on firms data selected from public available databases accomplished the task to describe the size and growth of firms through interpolating functions. The structure and internal ¯rms organization that lead to the optimal pro¯t is a main matter of business studies and must take carefully into account internal work distribution and the subsequent productivity. Moreover factors external to ¯rms, like as the evolution of markets and the availability of new technologies show their immediate bias on the wealth of the firms. In this paper a model is developed for a set of firms producing a single commodity. The shape of the productivity that leads to profit optimization is drawn and discussed. Furthermore the optimal time for the firm to renew its technology is established and consequences on the productivity are examined

Options with underlying asset driven by a fractional brownian motion: crossing barriers estimates

Electronic version of an article published as New Mathematics and Natural Computation Vol. 06, No. 01, pp. 109-118 (2010) DOI: 10.1142/S1793005710001633 ©World Scientific Publishing Company https://www.worldscientific.com/doi/abs/10.1142/S1793005710001633 This paper aims at supplying a decision support system tool to investors having options written on an underlying asset driven by a fractional Brownian motion (fBm). The results presented here rely on the theory of nonlinear transformations of fBm and provide the calculus of the probability estimate that the underlying asset crosses nonlinear barriers. Recent results stating a Black and Scholes-like pricing formula for fBm monitor the expected behaviour of options on the basis of the dynamics of the underlying asset. We rely on the results drawn for plain vanilla options, leaving their extension to barrier options for future work. The theory of speculative bubbles due to endogenous causes provides a useful suggestion for the detection of periods in which these results should be used. The application of the above results is shown through the NASDAQ case study

A review of aggregation techniques for agent-based models: understanding the presence of long-term memory

A key feature of agent-based modeling is the understanding of the macroscopic behavior based on data at the microscopic level. In this respect, financial market models are requested to replicate, at the aggregate level, the stylized facts of empirical data. Among them, a remarkable role is played by the long term behavior. Indeed, the study of the long-term memory is relevant, in that it describes if and how past events continue to maintain their influence for the future evolution of a system. In economic applications, this is relevant for understanding the reaction of the system to micro- and macro-economic shocks. Moreover, further information on the long-term memory properties of a system can be obtained by analyzing agents heterogeneity and the outcome of their aggregation. The aim of this paper is to review a few techniques—though the most relevant in our opinion—for studying the long-term memory as emergent property of systems composed by heterogeneous agents. Theorems relevant to the present analysis are summarized and their applications in four structural models with long-term memory are shown. This property is assessed through the analysis of the functional relation between model parameters. This is a post-peer-review, pre-copyedit version of an article published in Quality and Quantity. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11135-014-9995-

Productivity and costs for firms in presence of technology renewal processes

Wide empirical analyses investigated 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 the 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

Firms clustering in presence of technological renewal processes

This paper aims at exploring companies' profit maximization in presence of a hierarchical organization among firms and when technological renewal processes take place. The introduction of a hierarchical structure among rms allows us to describe the reality of the industrial districts. In this respect, some policies for the management of the renewal process in the district are derived

The role of diversity in persistence aggregation

This is the pre-peer reviewed version of the following article: Cerqueti, R. and Rotundo, G. (2012), The role of diversity in persistence aggregation. Int. J. Intell. Syst., 27: 176-187, which has been published in final form at doi:10.1002/int.21519. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions This paper deals with the theoretical analysis of the long-term memory property of time series generated by the aggregation of heterogeneous terms. The diversity is captured by the different features regarding the persistence of each component. It is shown that the memory of the aggregation is driven by the one related to some key components. The argument is carried out by developing an equilibrium model for asset prices in a financial market with heterogeneous agents

Memory Property in Heterogeneously Populated Markets

This paper focuses on the long memory of prices and returns of an asset traded in a financial market.We consider a microeconomic model of the market, and we prove theoretical conditions on the parameters of the model that give rise to long memory. In particular, the long memory property is detected in an agents' aggregation framework under some distributional hypotheses on the market's parameters

The weighted cross-shareholding complex network: a copula approach to concentration and control in financial markets

In this work, we focus on the cross-shareholding structure in financial markets. Specifically, we build ad hoc indices of concentration and control by employing a complex network approach with a weighted adjacency matrix. To describe their left and right tail dependence properties, we explore the theoretical dependence structure between such indices through copula functions. The theoretical framework has been tested over a high-quality dataset based on the Italian Stock Market. In doing so, we clearly illustrate how the methodological setting works and derive financial insights. In particular, we advance calibration exercises on parametric copulas under the minimization of both Euclidean distance and entropy measure

Exploring the financial risk of a temperature index: a fractional integrated approach

This paper introduces a new temperature index, which can suitably represent the underlying of a weather derivative. Such an index is defined as the weighted mean of daily average temperatures measured in different locations. It may be used to hedge volumetric risk, that is the effect of unexpected fluctuations in the demand/supply for some specific commodities—of agricultural or energy type, for example—due to unfavorable temperature conditions. We aim at exploring the long term memory property of the volatility of such an index, in order to assess whether there exist some long-run paths and regularities in its riskiness. The theoretical part of the paper proceeds in a stepwise form: first, the daily average temperatures are modeled through autoregressive dynamics with seasonality in mean and volatility; second, the assessment of the distributional hypotheses on the parameters of the model is carried out for analyzing the long term memory property of the volatility of the index. The theoretical results suggest that the single terms of the index drive the long memory of the overall aggregation; moreover, interestingly, the proper selection of the parameters of the model might lead both to cases of persistence and antipersistence. The applied part of the paper provides some insights on the behaviour of the volatility of the proposed index, which is built starting from single daily average temperature time series. This is a post-peer-review, pre-copyedit version of an article published in Annals of Operations Research. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10479-018-3063-