Archivio 2013 129 seminari

While the empirical and theoretical industrial organization literature has traditionally focussed on the growth rate of firm size, we take the position that profit rates, measured as the ratio of operating income to total assets, are economically more fundamental than logarithmic time differences in firm size, and hence should attain more attention in economic inquiry. The reason why we consider the profit rate so important from an economic viewpoint is that the economy is ultimately driven by the reallocation of capital, and investment decisions are governed by the rate of return per unit of invested capital. Additionally, profit rates exhibit peculiar time series and cross-sectional properties that make them appear an adequate quantity to study the complex interactions of competitive firms in a statistical equilibrium framework. Considering a sample of more than 500 long-lived publicly-traded U.S. companies, the purpose of this contribution is to explore the statistical features of profit rates, and to compare our findings to the properties of another very prominent degree of freedom for this problem: the growth rate of firm size. We find that the empirical densities of both quantities can be reasonably well described by the family of Subbotin distributions, but there are characteristic differences in their autocorrelation structures. Moreover, while there is a negative effect of size on the mean absolute deviation of growth rates, it turns out that neither location nor the dispersion of profit rates depends of firm size. In the second part of this paper, we employ the statistical equilibrium model of competitive firms proposed by Alfarano et al. (2012) to model the dynamic evolution of profit rates and show that this particular stochastic process reproduces the statistical characteristics of the profit rate time series. Moreover, we use the solution of the transient density of this process to estimate the diffusion coefficient, which allows us to measure the characteristic time scale for the dissipation of excess profits.
We test the ability of the Cyclically Adjusted Price Earnings (CAPE) ratio introduced by Robert Shiller to predict the future long run performances of international stock markets. We devote the first part of the seminar to the empirical analysis of numerous equity indices. We question if the striking ability of CAPE to predict returns of the index is a genuine effect or if it is a spurious consequence of the persistence and endogeneity of the regressor. The evidence rooted on a bootstrap analysis of the regression plays in favour of statistically significant predictability of long run yields for the US market (Standard & Poor and NYSE monthly data are available since 1870 and 1926, respectively). The same analysis extended to ten different countries is less conclusive. We believe that this is largely due to fact that the time series employed in the analysis are quite short (MSCI data are recorded since January 1970). In the second part, we provide a theoretical justification of the empirical observations from the US market. We propose a simple model of the price dynamics in which the return growth depends on three components: a) a momentum component, naturally justified in terms of agents' belief that expected returns are higher in bullish markets than in bearish ones; b) a fundamental component proportional to the log earnings over price ratio at time zero. The initial value of the ratio determines the reference growth level, from which the actual stock price may deviate as an effect of random external disturbances, and c) a driving component ensuring the diffusive behaviour of stock prices. Under these assumptions, we are able to prove that, if we consider a sufficiently large number of periods, the expected rate of return and the expected gross return are linear in the initial time value of the log earnings over price ratio, and their variance goes to zero with rate of convergence equal to minus one.
The ordinary level-set method [1] used for tracking front contours is randomized to include the effects of turbulence.Turbulence randomly transports particle of the medium and therefore the contour gets a random character.The level-set method is randomized by considering a distribution of the contour according to theprobability density function of the turbulent displacement of the medium particles. In particular, this Lagrangian particle approach can be used to study the propagation of a reacting front in turbulent flows. A physical requirement connecting particle turbulent dispersion and the reacting front velocity is obtainedfrom equating the expansion rates of the front progression and of the reactant particles spread, so that the process follows to be fully determined by turbulence characteristics. The application of the method to turbulent premixed combustion is discussed [2]. The physical connection between particle dispersion and the front velocity compares favorably with experimental data. Moreover, in the case of a zero-curvature flame, with a non-Markovian parabolic model for turbulent dispersion, the formulation yields the classical Zimont equation extended to all elapsed times. The formulation extension to consider the acoustic noise is also addressed. The application of the method to model turbulence effects in wildland fire propagation [3] is also discussed. It emerges to be suitable, more than literature approaches based on the level-set method, to simulate the fire overcaming a fire breakzone because of the diffusion of the hot air behind it. [1] Sethian J.A. and Smereka P., Level set methods for fluid interfaces. Annu. Rev. Fluid Mech. 35, 341-372 (2003). [2] Pagnini G. and Bonomi E., Lagrangian formulation of turbulent premixed combustion. Phys. Rev. Lett. 107, 044503 (2011) [3] Pagnini G. and Massidda L., The randomized level-set method to model turbulence effects in woldland fire propagation. In D. Spano, V. Bacciu, M. Salis, C. Sirca (Eds.): Modelling Fire Behaviour and Risk, pp. 126-131. Proceedings of the International Conference on Fire Behaviour and Risk, Alghero, Italy, 4--6 October (2011)