A Stochastic Cobweb Dynamical Model

We consider the dynamics of a stochastic cobweb model with linear demand and a backward-bending supply curve. In our model, forward-looking expectations and backward-looking ones are assumed, in fact we assume that the representative agent chooses the backward predictor with probability , and the forward predictor with probability , so that the expected price at time is a random variable and consequently the dynamics describing the price evolution in time is governed by a stochastic dynamical system. The dynamical system becomes a Markov process when the memory rate vanishes. In particular, we study the Markov chain in the cases of discrete and continuous time. Using a mixture of analytical tools and numerical methods, we show that, when prices take discrete values, the corresponding Markov chain is asymptotically stable. In the case with continuous prices and nonnecessarily zero memory rate, numerical evidence of bounded price oscillations is shown. The role of the memory rate is studied through numerical experiments, this study confirms the stabilizing effects of the presence of resistant memory

A Video Game Based on Optimal Control and Elementary Statistics

The video game presented in this paper is a prey-predator game where two preys (human players) must avoid three predators (automated players) and must reach a location in the game field (the computer screen) called preys' home. The game is a sequence of matches and the human players (preys) must cooperate in order to achieve the best perform- ance against their opponents (predators). The goal of the predators is to capture the preys, which are the predators try to have a "rendez vous" with the preys, using a small amount of the "resources" available to them. The score of the game is assigned following a set of rules to the prey team, not to the individual prey. In some situations the rules imply that to achieve the best score it is convenient for the prey team to sacrifice one of his components. The video game pursues two main purposes. The first one is to show how the closed loop solution of an optimal control problem and elementary sta- tistics can be used to generate (game) actors whose movements satisfy the laws of classical mechanics and whose be- haviour simulates a simple form of intelligence. The second one is "educational", in fact the human players in order to be successful in the game must understand the restrictions to their movements posed by the laws of classical mechanics and must cooperate between themselves. The video game has been developed having in mind as players for children aged between five and thirteen years. These children playing the video game acquire an intuitive understanding of the basic laws of classical mechanics (Newton's dynamical principle) and enjoy cooperating with their teammate. The video game has been experimented on a sample of a few dozen children. The children aged between five and eight years find the game amusing and after playing a few matches develop an intuitive understanding of the laws of classical me- chanics. They are able to cooperate in making fruitful decisions based on the positions of the preys (themselves), of the predators (their opponents) and on the physical limitations to the movements of the game actors. The interest in the game decreases when the age of the players increases. The game is too simple to interest a teenager. The game engine consists in the solution of an assignment problem, in the closed loop solution of an optimal control problem and in the adaptive choice of some parameters. At the beginning of each match, and when necessary during a match, an assign- ment problem is solved, that is the game engine chooses how to assign to the predators the preys to chase. The resulting assignment implies some cooperation among the predators and defines the optimal control problem used to compute the strategies of the predators during the match that follows. These strategies are determined as the closed loop solution of the optimal control problem considered and can be thought as a (first) form of artificial intelligence (AI) of the preda- tors. In the optimal control problem the preys and the predators are represented as point masses moving according to Newton's dynamical principle under the action of friction forces and of active forces. The equations of motion of these point masses are the constraints of the control problem and are expressed through differential equations. The formula- tion of the decision process through optimal control and Newton's dynamical principle allows us to develop a game where the effectiveness and the goals of the automated players can be changed during the game in an intuitive way sim- ply modifying the values of some parameters (i.e. mass, friction coefficient, ...). In a sequence of game matches the predators (automated players) have "personalities" that try to simulate human behaviour. The predator personalities are determined making an elementary statistical analysis of the points scored by the preys in the game matches played and consist in the adaptive choice of the value of a parameter (the mass) that appears in the differential equations that define the movements of the predators. The values taken by this parameter determine the behaviour of the predators and their effectiveness in chasing the preys. The predators personalities are a (second) form of AI based on elementary statistics that goes beyond the intelligence used to chase the preys in a match. In a sequence of matches the predators using this second form of AI adapt their behaviour to the preys' behaviour. The video game can be downloaded from the website: http://www.ceri.uniroma1.it/ceri/zirilli/w10/

The Calibration of Some Stochastic Volatility Models Used in Mathematical Finance

Stochastic volatility models are used in mathematical finance to describe the dynamics of asset prices. In these models, the asset price is modeled as a stochastic process depending on time implicitly defined by a stochastic differential Equation. The volatility of the asset price itself is modeled as a stochastic process depending on time whose dynamics is described by a stochastic differential Equation. The stochastic differential Equations for the asset price and for the volatility are coupled and together with the necessary initial conditions and correlation assumptions constitute the model. Note that the stochastic volatility is not observable in the financial markets. In order to use these models, for example, to evaluate prices of derivatives on the asset or to forecast asset prices, it is necessary to calibrate them. That is, it is necessary to estimate starting from a set of data the values of the initial volatility and of the unknown parameters that appear in the asset price/volatility dynamic Equations. These data usually are observations of the asset prices and/or of the prices of derivatives on the asset at some known times. We analyze some stochastic volatility models summarizing merits and weaknesses of each of them. We point out that these models are examples of stochastic state space models and present the main techniques used to calibrate them. A calibration problem for the Heston model is solved using the maximum likelihood method. Some numerical experiments about the calibration of the Heston model involving synthetic and real data are presented

Robotic Versus Laparoscopic Adrenalectomy: Pluriannual Experience in a High-Volume Center Evaluating Indications and Results

Background: Robotic adrenalectomy offers several clinical benefits if compared with laparoscopic adrenalectomy; however, its superiority is still under debate. The aim of this study was the investigation of differences between the two techniques, and a comparison when approaching right or left side adrenal lesions was further conducted. Materials and Methods: All patients undergoing laparoscopic and robotic unilateral adrenalectomy at our institution from January 2006 to December 2019 were collected and retrospectively analyzed. Statistical analysis was conducted; differences between the two cohorts were reported. Results: A total of 160 cases were included (84 patients in laparoscopic adrenalectomy-group [LA-g] 76 cases in robotic adrenalectomy-group [RA-g]). The groups were homogeneous for demographic data. No intraoperative complications were reported; mean amount of intraoperative blood loss was comparable. No cases of conversion to open surgery were required. RA-g presented a longer operative time than LA-g for right adrenalectomy (P = .05), no differences were noted for left side (P = .187). Overall morbidity was 21% for LA-g and 10.5% for RA-g (P = .087), with an inferior rate of surgical complications for RA-g (P = .024), and for robotic left adrenalectomy than robotic right procedure (P = .03). Length of hospital stay was shorter for RA-g (P = .005). Conclusions: Robotic adrenalectomy presents similar outcomes as laparoscopic approach with some benefits for selected cases. Left adrenal lesions seem to receive greater advantages from robotic technique. Large randomized controlled trials are required to determine the role of robotic adrenal surgery and if the indication can be standardized based on the laterality of adrenal procedure

In celebration of the 60th birthday of Professor Alemdar Hasanoğlu (Hasanov)

n/

Il modello di Black-Scholes per la determinazione del pezzo delle opzioni europee

Stabilimento Tipografico De Rosa, Cosenz

Boundary layers and non-linear vibrations in an axially moving beam

The non-linear oscillations of a one-dimensional axially moving beam with vanishing flexural stiffness and weak non-linearities are analysed. The solution of the initial-boundary value problem for the partial differential equation that describes the motion of the beam when two parameters related to the flexural stiffness and the non-linear terms vanish is expanded into a perturbative double series. Two singular perturbation effects due to the small flexural stiffness and to the weak non-linear terms arise: (i) a boundary layer effect when the flexural stiffness vanishes, (ii) a secular effect. Some tests are performed to compare the first order perturbative solution with an approximate solution obtained by a finite difference scheme. The effect of the oscillation amplitude combined with the presence of small bending stiffness and axial transport velocity is investigated enlighting some interesting aspects of axially moving systems. The value of the perturbative series as a computational tool is shown