Roy Cerqueti

Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions

The yearly aggregated tax income data of all, more than 8000, Italian municipalities are analyzed for a period of five years, from 2007 to 2011, to search for conformity or not with Benford’s law, a counter-intuitive phenomenon observed in large tabulated data where the occurrence of numbers having smaller initial digits is more favored than those with larger digits. This is done in anticipation that large deviations from Benford’s law will be found in view of tax evasion supposedly being widespread across Italy. Contrary to expectations, we show that the overall tax income data for all these years is in excellent agreement with Benford’s law. Furthermore, we also analyze the data of Calabria, Campania and Sicily, the three Italian regions known for strong presence of mafia, to see if there are any marked deviations from Benford’s law. Again, we find that all yearly data sets for Calabria and Sicily agree with Benford’s law whereas only the 2007 and 2008 yearly data show departures from the law for Campania. These results are again surprising in view of underground and illegal nature of economic activities of mafia which significantly contribute to tax evasion. Some hypothesis for the found conformity is presented.

Evidence of economic regularities and disparities of Italian regions from aggregated tax income size data

This paper discusses the size distribution–in economic terms–of the Italian municipalities over the period 2007–2011. Yearly data are rather well fitted by a modified Lavalette law, while Zipf–Mandelbrot–Pareto law seems to fail in this doing. The analysis is performed either at a national as well as at a local (regional and provincial) level. Deviations are discussed as originating in so called king and vice-roy effects. Results confirm that Italy is shared among very different regional realities. The case of Lazio is puzzling.

Mean–Variance portfolio selection in presence of infrequently traded stocks

This paper deals with a mean–variance optimal portfolio selection problem in presence of risky assets characterized by low-frequency trading and, therefore, low liquidity. To model the dynamics of illiquid assets, we introduce pure-jump processes. This leads to the development of a portfolio selection model in a mixed discrete/continuous time setting. We pursue the twofold scope of analyzing and comparing either long-term investment strategies as well as short-term trading rules. The theoretical model is analyzed by applying extensive Monte Carlo experiments, in order to provide useful insights from a financial perspective.

Regularities and discrepancies of credit default swaps: a data science approach through Benford's law

In this paper, we search whether the Benfords law is applicable to monitor daily changes in sovereign Credit Default Swaps (CDS) quotes, which are acknowledged to be complex systems of economic content. This test is of paramount importance since the CDS of a country proxy its health and probability to default, being associated to an insurance against the event of its default. We fit the Benfords law to the daily changes in sovereign CDS spreads for 13 European countries, - both inside and outside the European Union and European Monetary Union. Two different tenors for the sovereign CDS contracts are considered: 5 yrs and 10 yrs, - the former being the reference and most liquid one. The time period under investigation is 2008-2015 which includes the period of distress caused by the European sovereign debt crisis. Moreover, (i) an analysis over relevant sub-periods is carried out, (ii) several insights are provided also by implementing the tracking of the Benfords law over moving windows. The main test for checking the conformance to Benfords law is - as usual - the

The impact of innovation on companies’ performance: an entropy-based analysis of the STAR market segment of the Italian Stock Exchange

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Statistical assessment of regional wealth inequalities: the Italian case

test, whose values are presented and discussed for all cases. The analysis is further completed by elaborations based on Chebyshevs distance and Kullback and Leiblers divergence. The results highlight differences by countries and tenors. In particular, these results suggest that liquidity seems to be associated to higher levels of distortion. Greece - representing a peculiar case - shows a very different path with respect to the other European countries.

A Tabu Search heuristic procedure in Markov chain bootstrapping

This paper proposes the use of a class of concentration-based entropy measures as a new instrument to quantify business performances through an analysis of growth, profitability and productivity. Such measures are tested against a complex analysis of the link between innovation and performance for firms listed in the STAR market segment of the Italian Stock Exchange. In so doing, two targets are achieved: (1) the identification of parameters that are relevant for explaining the relationship between innovation and performance for the considered sample, with special focus on innovation type, innovation level and business size; (2) the elaboration of a new methodology – based on information theory – for the analysis of the impact of innovation on performance. The study shows that type of innovation and size play a key role in determining company performance.

A Universal Rank-Size Law

This paper discusses region wealth size distributions, through their member cities aggregated tax income. As an illustration, the official data of the Italian Ministry of Economics and Finance has been considered, for all Italian municipalities, over the period 2007-2011. Yearly data of the aggregated tax income is transformed into a few indicators: the Gini, Theil, and Herfindahl-Hirschman indices. On one hand, the relative interest of each index is discussed. On the other hand, numerical results confirm that Italy is divided into very different regional realities, a few which are specifically outlined. This shows the interest of transforming data in an adequate manner and of comparing such indices. 1 ar X iv :1 41 0. 49 22 v1 [ qfi n. E C ] 1 8 O ct 2 01 4

Financing policies via stochastic control: a dynamic programming approach

Markov chain theory is proving to be a powerful approach to bootstrap finite states processes, especially where time dependence is non linear. In this work we extend such approach to bootstrap discrete time continuous-valued processes. To this purpose we solve a minimization problem to partition the state space of a continuous-valued process into a finite number of intervals or unions of intervals (i.e. its states) and identify the time lags which provide “memory” to the process. A distance is used as objective function to stimulate the clustering of the states having similar transition probabilities. The problem of the exploding number of alternative partitions in the solution space (which grows with the number of states and the order of the Markov chain) is addressed through a Tabu Search algorithm. The method is applied to bootstrap the series of the German and Spanish electricity prices. The analysis of the results confirms the good consistency properties of the method we propose.

Long-range properties and data validity for hydrogeological time series: The case of the Paglia river

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations.