A Stackelberg Differential Game with Overlapping Generations

We study a differential game, for the extraction of a renewable resource, in which players are overlapping generations of extractors. The framework of overlapping generation allows us to consider both intragenerational (players in the same generation) and intergenerational (players in different generations) competition. Since we consider overlapping generations, players have asynchronous horizons. We consider the case in which players, even if identical, face competition in an asymmetric way by mean of two different approaches: different costs and Leader-Follower competition. The leader-follower structure, as a consequence of the overlapping generation framework, is not fixed but depends on the time period in which each player is living in. The behaviour of the players can be of two ways: myopic or not myopic.Feedback Feedback Nash Equilibrium, resource extraction, overlapping generations, asynchronous horizon, asymmetric players, Stackelberg differential game.

A Differential Game for Renewable Resource Extraction Asymmetric Players and Asynchronous Horizons

In this paper we study a differential game, for resource extraction of a renewable good, in which players are overlapping generations of extractors. The framework of overlapping generation allows us to consider intragenerational (players in the same generation) and intergenerational (players in different generations) game equilibrium. We consider the case in which players, even if identical, face competition in an asymmetric way. Since we consider overlapping generations, players have asynchronous horizons, in contrast with a number of studies in intertemporal exploitation of resources in which players have identical time horizons.Feedback Nash Equilibrium, resource extraction, overlapping generations, asynchronous horizon, asymmetric players.

A Review on Strong Interpolation Theorem for Way Below Relation

The present paper aims to introduce the principal definitions and proof of fundamental properties of the so called "Way Below" relation. We introduce an alternative proof, with respect to \cite{Scott}, of the strong interpolation theorem. The strong interpolation theorem is the theoretical result which provide computational consistency to way below relation because it guarantee the use of successive algorithm in order to find a better and better approximation of the result.continuous lattice, way-below relation, strong interpolation

Resource extraction activity: an intergenerational approach

The problem of resource extraction (both renewable and nonrenewable) can be studied by considering two important aspects: competition among extractors and intergenerational equity. In resource extraction activity actions of present generations influence the choices of future generation in an obvious way. In order to capture these features we consider a differential game in which players are overlapping generations of extractors, in this way both competition and intergenerational equity are included in the model. An important feature of this model is that, since we consider overlapping generations, players have asynchronous horizons, in contrast with a number of studies in intertemporal exploitation of resources in which players have identical time horizons. The framework of overlapping generation allows us to consider intragenerational (players in the same generation) and intergenerational (players in different generations) game equilibrium in the contest of differential games with asynchronous horizons.Feedback Nash Equilibrium, resource extraction, overlapping generations, asynchronous horizon

Another unconsidered sinister effect of indusrty-specific crises? On the possible emergence of adverse selection phenomena on the survival of entrepreneurial ventures.

This article explores the possibility that under an intensely negative industry-specific shock, the commonly detected positive relationship between the human capital of founders and the survival prospects of start-up businesses may actually be reversed. Starting from an analysis of the issue from a theoretical perspective in order to derive the necessary and sufficient conditions for the emergence of these adverse selection phenomena in entrepreneurship, the study examines a sample of 179 Italian start-ups operating in the ICT services market created during the boom period from 1995 to early 2000. Econometric analyses provide evidence that, during an intense industry crisis (i.e., early 2000 to 2003), entrepreneurs with a substantial amount of human capital may pursue an exit strategy.High-tech entrepreneurship; Adverse selection; Industry crises.

Un approccio metrico per lo studio dei dati finanziari

In this paper I present a time series analysis based on a metrical approach. I use a definition of distance which depends on the sample correlation coefficient among bonds. The dataset consists on daily returns of US treasury bonds. By mean of a Linkage-Algorithm bonds are classified according to the distance which show the cluster structure. It is evident how the cluster structure depends strongly on maturity date, bonds are classified in three different clusters, one of them consists on long term bonds. The analysis is focused on long term bonds, introducing a modified time series, I show how is possible to evidentiate a complex cluster structure even in this class of bonds.Fixed income, clustering

On the determinants of the degree of openness of Open Source firms: An entry model

This paper examines the relationship between the degree of openness that software start-ups choose and some of the main industrial features faced by new entrants. Hypotheses derived from a formal model are tested through the implementation of econometric techniques and information provided by a novel database (ELISS). Theoretical predictions and empirical results indicate that the choice by start-ups of the degree of openness is negatively influenced by the sensitivity of consumers to price and is positively related both to the strength of network externalities their products exhibit and to the competitive advantage of the incumbent.open-source software; network effects; entry

Forecasting financial time series with Boltzmann entropy through neural networks

Neural networks have recently been established as state-of-the-art in forecasting financial time series. However, many studies show how one architecture, the Long-Short Term Memory, is the most widespread in financial sectors due to its high performance over time series. Considering some stocks traded in financial markets and a crypto ticker, this paper tries to study the effectiveness of the Boltzmann entropy as a financial indicator to improve forecasting, comparing it with financial analysts’ most commonly used indicators. The results show how Boltzmann’s entropy, born from an Agent-Based Model, is an efficient indicator that can also be applied to stocks and cryptocurrencies alone and in combination with some classic indicators. This critical fact allows obtaining good results in prediction ability using Network architecture that is not excessively complex

Boltzmann Entropy in Cryptocurrencies: A Statistical Ensemble Based Approach

In this paper we try to build a statistical ensemble to describe a cryptocurrency-based system, emphasizing an "affinity" between the system of agents trading in these currencies and statistical mechanics. We focus our study on the concept of entropy in the sense of Boltzmann and we try to extend such a definition to a model in which the particles are replaced by N agents completely described by their ability to buy and to sell a certain quantity of cryptocurrencies. After providing some numerical examples, we show that entropy can be used as an indicator to forecast the price trend of cryptocurrencies

Generative Adversarial Network for Market Hourly Discrimination

In this paper, we consider 2 types of instruments traded on the markets, stocks and cryptocurrencies. In particular, stocks are traded in a market subject to opening hours, while cryptocurrencies are traded in a 24-hour market. What we want to demonstrate through the use of a particular type of generative neural network is that the instruments of the non-timetable market have a different amount of information, and are therefore more suitable for forecasting. In particular, through the use of real data we will demonstrate how there are also stocks subject to the same rules as cryptocurrencies