Alessia Naccarato

The Gravitation of Market Prices as A Stochastic Process

The theory of value has been based ever since Adam Smith on the idea that the market prices of commodities, those at which actual trade takes place, gravitate around a central position known as natural prices. This paper seeks to develop a statistical idea of the process in question and suggests in particular that market prices can be said to gravitate around natural prices if the probability of their means being very close to natural prices after t observations tends to 1 as t tends to infinity. A set of possible conditions leading to that result is also presented.

Modelling the spatial variation of human population density using Taylor's power law, Italy 1971-2011

ABSTRACT Taylor’s power law (Tpl) is applied to the human population density of Italian regions and provinces for the period 1971–2011. Three different weighting systems are used to estimate Tpl at the national and subnational levels in which seemingly unrelated regression models are adopted. The following results were found: Tpl is suitable for human populations and sensitive to the adopted weighting system; Tpl’s slope is positive and, at a subnational level, has an inverse behaviour with respect to the spatial variability of the weighting variables; and Tpl’s slope can be viewed as an indicator of a population’s spatial distribution homogeneity.

A Multivariate VEC-BEKK Model for Portfolio Selection

The use of bivariate vector error correction models and Baba–Engl–Kraft–Kroner models is proposed for the selection of a stock portfolio (Markowitz portfolio) based on estimates of average returns on shares and the volatility of share prices. The model put forward is applied to a series of data regarding the prices of 150 shares traded on the Italian stock market (BIT) between 1 January 1975 and 31 August 2011.

BEKK Element-by-Element Estimation of a Volatility Matrix. A Portfolio Simulation

The use of a BEKK (Baba-Engle-Kraft-Kroner) model is proposed to estimate the volatility of a set of financial historical series with a view to the selection of a stock portfolio. An individual element on the diagonal of the volatility matrix is estimated by applying the model to the series of log returns both of the share i to which it refers and of the market index. An extra-diagonal element is instead estimated by using in the model the covariances between the series of log returns of the two shares i and j to which the element of the volatility matrix corresponds.