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Prof. Guglielmo D'Amico
Department of Economics, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy

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Research Keywords & Expertise

0 Stochastic Modeling
0 Renewable energies
0 Financial Mathematics
0 inequality measures
0 Markov and semi-Markov processes

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Markov and semi-Markov processes
Stochastic Modeling
Financial Mathematics

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Journal article
Published: 20 August 2021 in Mathematics
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In this paper, a new reliability measure, named sequential interval reliability, is introduced for homogeneous semi-Markov repairable systems in discrete time. This measure is the probability that the system is working in a given sequence of non-overlapping time intervals. Many reliability measures are particular cases of this new reliability measure that we propose; this is the case for the interval reliability, the reliability function and the availability function. A recurrent-type formula is established for the calculation in the transient case and an asymptotic result determines its limiting behaviour. The results are illustrated by means of a numerical example which illustrates the possible application of the measure to real systems.

ACS Style

Vlad Stefan Barbu; Guglielmo D’Amico; Thomas Gkelsinis. Sequential Interval Reliability for Discrete-Time Homogeneous Semi-Markov Repairable Systems. Mathematics 2021, 9, 1997 .

AMA Style

Vlad Stefan Barbu, Guglielmo D’Amico, Thomas Gkelsinis. Sequential Interval Reliability for Discrete-Time Homogeneous Semi-Markov Repairable Systems. Mathematics. 2021; 9 (16):1997.

Chicago/Turabian Style

Vlad Stefan Barbu; Guglielmo D’Amico; Thomas Gkelsinis. 2021. "Sequential Interval Reliability for Discrete-Time Homogeneous Semi-Markov Repairable Systems." Mathematics 9, no. 16: 1997.

Journal article
Published: 05 July 2021 in Energies
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This paper provides evidence on how the variability of the power produced by a wind farm and its revenue are affected by implementing a ramp-rate limitation strategy and by adding a storage device to the system. The wind farm receives penalties whenever the ramp-rate limitations are not respected and may be supported by batteries to avoid this scenario. In this paper, we model the battery usage as a discrete time homogeneous Markov chain with rewards thanks to which it is possible to simulate the state of the charge of the battery and to calculate the amount of penalties suffered by the wind farm during any period. An application is performed considering the power produced by a hypothetical wind turbine located in Sardinia (Italy) using real wind speed data and electricity prices from a period of 10 years. We applied the concept of ramp-rate limitation on our hourly dataset, studying several limitation scenarios and battery capacities.

ACS Style

Guglielmo D’Amico; Filippo Petroni; Salvatore Vergine. An Analysis of a Storage System for a Wind Farm with Ramp-Rate Limitation. Energies 2021, 14, 4066 .

AMA Style

Guglielmo D’Amico, Filippo Petroni, Salvatore Vergine. An Analysis of a Storage System for a Wind Farm with Ramp-Rate Limitation. Energies. 2021; 14 (13):4066.

Chicago/Turabian Style

Guglielmo D’Amico; Filippo Petroni; Salvatore Vergine. 2021. "An Analysis of a Storage System for a Wind Farm with Ramp-Rate Limitation." Energies 14, no. 13: 4066.

Research article
Published: 31 May 2021 in Annals of Finance
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Incorporation of technical risk in compound real options has been considered in Cassimon et al. (2011) concerning the valuation of multi-stage pharmaceutical R&D. There, the technical success probabilities at each development stage were assumed to be generated independently of each other. This assumption can be unrealistic in many applied problems, pharmaceutical R&D included. We present a valuation procedure dealing with dependent success probabilities and random development stage times. This greater flexibility allows a better description of the sequence of decision stages and results, which in turn, impact the value of the considered project. The theoretical results are illustrated through a numerical example that shows the implementation of the model to a pharmaceutical R&D problem.

ACS Style

Guglielmo D’Amico; Giovanni Villani. Valuation of R&D compound option using Markov chain approach. Annals of Finance 2021, 1 -26.

AMA Style

Guglielmo D’Amico, Giovanni Villani. Valuation of R&D compound option using Markov chain approach. Annals of Finance. 2021; ():1-26.

Chicago/Turabian Style

Guglielmo D’Amico; Giovanni Villani. 2021. "Valuation of R&D compound option using Markov chain approach." Annals of Finance , no. : 1-26.

Journal article
Published: 08 March 2021 in Mathematics
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In this paper, we computed general interval indicators of availability and reliability for systems modelled by time non-homogeneous semi-Markov chains. First, we considered duration-dependent extensions of the Interval Reliability and then, we determined an explicit formula for the availability with a given window and containing a given point. To make the computation of the window availability, an explicit formula was derived involving duration-dependent transition probabilities and the interval reliability function. Both interval reliability and availability functions were evaluated considering the local behavior of the system through the recurrence time processes. The results are illustrated through a numerical example. They show that the considered indicators can describe the duration effects and the age of the multi-state system and be useful in real-life problems.

ACS Style

Guglielmo D’Amico; Raimondo Manca; Filippo Petroni; Dharmaraja Selvamuthu. On the Computation of Some Interval Reliability Indicators for Semi-Markov Systems. Mathematics 2021, 9, 575 .

AMA Style

Guglielmo D’Amico, Raimondo Manca, Filippo Petroni, Dharmaraja Selvamuthu. On the Computation of Some Interval Reliability Indicators for Semi-Markov Systems. Mathematics. 2021; 9 (5):575.

Chicago/Turabian Style

Guglielmo D’Amico; Raimondo Manca; Filippo Petroni; Dharmaraja Selvamuthu. 2021. "On the Computation of Some Interval Reliability Indicators for Semi-Markov Systems." Mathematics 9, no. 5: 575.

Journal article
Published: 12 January 2021 in Stochastics and Quality Control
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In this paper we advance a nonlinear optimization problem for hedging wind power variability by using a dispatchable energy source (DES) like gas. The model considers several important aspects such as modeling of wind power production, electricity price, nonlinear penalization scheme for energy underproduction and interrelations among the considered variables. Results are given in terms of optimal co-generation policy with DES. The optimal policy is interpreted and analyzed in different penalization scenarios and related to a 48 MW hypothetical wind park. The model is suitable for integration of wind energy especially for isolated grids. Some probabilistic results for special moments of a Log-Normal distribution are obtained; they are necessary for the evolution of the optimal policy.

ACS Style

Guglielmo D’Amico; Bice Di Basilio; Filippo Petroni. Hedging the Risk of Wind Power Production Using Dispatchable Energy Source. Stochastics and Quality Control 2021, 1 .

AMA Style

Guglielmo D’Amico, Bice Di Basilio, Filippo Petroni. Hedging the Risk of Wind Power Production Using Dispatchable Energy Source. Stochastics and Quality Control. 2021; ():1.

Chicago/Turabian Style

Guglielmo D’Amico; Bice Di Basilio; Filippo Petroni. 2021. "Hedging the Risk of Wind Power Production Using Dispatchable Energy Source." Stochastics and Quality Control , no. : 1.

Original paper
Published: 31 October 2020 in Letters in Spatial and Resource Sciences
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This article deals with the production of energy through photovoltaic (PV) panels. The efficiency and quantity of energy produced by a PV panel depend on both deterministic factors, mainly related to the technical characteristics of the panels, and stochastic factors, essentially the amount of incident solar radiation and some climatic variables that modify the efficiency of solar panels such as temperature and wind speed. The main objective of this work is to estimate the energy production of a PV system with fixed technical characteristics through the modeling of the stochastic factors listed above. Besides, we estimate the economic profitability of the plant, net of taxation or subsidiary payment policies, considered taking into account the hourly spot price curve of electricity and its correlation with solar radiation, via vector autoregressive models. Our investigation ends with a Monte Carlo simulation of the models introduced. We also propose the pricing of some quanto options that allow hedging both the price risk and the volumetric risk.

ACS Style

Laura Casula; Guglielmo D’Amico; Giovanni Masala; Filippo Petroni. Performance estimation of photovoltaic energy production. Letters in Spatial and Resource Sciences 2020, 13, 267 -285.

AMA Style

Laura Casula, Guglielmo D’Amico, Giovanni Masala, Filippo Petroni. Performance estimation of photovoltaic energy production. Letters in Spatial and Resource Sciences. 2020; 13 (3):267-285.

Chicago/Turabian Style

Laura Casula; Guglielmo D’Amico; Giovanni Masala; Filippo Petroni. 2020. "Performance estimation of photovoltaic energy production." Letters in Spatial and Resource Sciences 13, no. 3: 267-285.

Journal article
Published: 17 August 2020 in Energies
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Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR).

ACS Style

Guglielmo D’Amico; Giovanni Masala; Filippo Petroni; Robert Adam Sobolewski. Managing Wind Power Generation via Indexed Semi-Markov Model and Copula. Energies 2020, 13, 4246 .

AMA Style

Guglielmo D’Amico, Giovanni Masala, Filippo Petroni, Robert Adam Sobolewski. Managing Wind Power Generation via Indexed Semi-Markov Model and Copula. Energies. 2020; 13 (16):4246.

Chicago/Turabian Style

Guglielmo D’Amico; Giovanni Masala; Filippo Petroni; Robert Adam Sobolewski. 2020. "Managing Wind Power Generation via Indexed Semi-Markov Model and Copula." Energies 13, no. 16: 4246.

Journal article
Published: 17 August 2020 in Mathematics
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This paper presents an insurance contract that the supplier of wind power may subscribe to with an insurance company in order to immunize his/her revenue against the volatility of wind power and prices. Based on empirical evidence, we found that wind power and electricity prices are correlated. Then, we adopted a joint stochastic process to model both time series, which is based on indexed semi-Markov chains for the wind power generation process and on a general Markovian process for the electricity price process. Using a joint stochastic model allows the insurance company to compute the fair premium that the wind power producer has to pay in order to hedge the risk against inadequate revenues. Recursive type equations are obtained for the prospective mathematical reserves of the insurance contract. The model and the validity of the results are illustrated through a real data application.

ACS Style

Guglielmo D’Amico; Fulvio Gismondi; Filippo Petroni. Insurance Contracts for Hedging Wind Power Uncertainty. Mathematics 2020, 8, 1376 .

AMA Style

Guglielmo D’Amico, Fulvio Gismondi, Filippo Petroni. Insurance Contracts for Hedging Wind Power Uncertainty. Mathematics. 2020; 8 (8):1376.

Chicago/Turabian Style

Guglielmo D’Amico; Fulvio Gismondi; Filippo Petroni. 2020. "Insurance Contracts for Hedging Wind Power Uncertainty." Mathematics 8, no. 8: 1376.

Articles
Published: 05 September 2019 in Scandinavian Actuarial Journal
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We propose a dividend stock valuation model where multiple dividend growth series and their dependencies are modelled using a multivariate Markov chain. Our model advances existing Markov chain stock models. First, we determine assumptions that guarantee the finiteness of the price and risk as well as the fulfilment of transversality conditions. Then, we compute the first- and second-order price-dividend ratios by solving corresponding linear systems of equations and show that a different price-dividend ratio is attached to each combination of states of the dividend growth process of each stock. Subsequently, we provide a formula for the computation of the variances and covariances between stocks in a portfolio. Finally, we apply the theoretical model to the dividend series of three US stocks and perform comparisons with existing models. The results could also be applied for actuarial purposes as a general stochastic investment model and for calculating the initial endowment to fund a portfolio of dependent perpetuities.

ACS Style

Guglielmo D'amico; Riccardo De Blasis. A multivariate Markov chain stock model. Scandinavian Actuarial Journal 2019, 2020, 272 -291.

AMA Style

Guglielmo D'amico, Riccardo De Blasis. A multivariate Markov chain stock model. Scandinavian Actuarial Journal. 2019; 2020 (4):272-291.

Chicago/Turabian Style

Guglielmo D'amico; Riccardo De Blasis. 2019. "A multivariate Markov chain stock model." Scandinavian Actuarial Journal 2020, no. 4: 272-291.

Journal article
Published: 20 August 2019 in International Journal of Financial Studies
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In this paper, we propose a semi-Markov chain to model the salary levels of participants in a pension scheme. The aim of the models is to understand the evolution in time of the salary of active workers in order to implement it in the construction of the actuarial technical balance sheet. It is worth mentioning that the level of the contributions in a pension scheme is directly proportional to the incomes of the active workers; in almost all cases, it is a percentage of the worker’s incomes. As a consequence, an adequate modeling of the salary evolution is essential for the determination of the contributions paid to the fund and thus for the determination of the fund’s sustainability, especially currently, when all jobs and salaries are subject to changes due to digitalization, ICT, innovation, etc. The model is applied to a large dataset of a real compulsory Italian pension scheme of the first pillar. The semi-Markovian hypothesis is tested, and the advantages with respect to Markov chain models are assessed.

ACS Style

Guglielmo D'amico; Ada Lika; Filippo Petroni. Risk Management of Pension Fund: A Model for Salary Evolution. International Journal of Financial Studies 2019, 7, 44 .

AMA Style

Guglielmo D'amico, Ada Lika, Filippo Petroni. Risk Management of Pension Fund: A Model for Salary Evolution. International Journal of Financial Studies. 2019; 7 (3):44.

Chicago/Turabian Style

Guglielmo D'amico; Ada Lika; Filippo Petroni. 2019. "Risk Management of Pension Fund: A Model for Salary Evolution." International Journal of Financial Studies 7, no. 3: 44.

Journal article
Published: 15 February 2019 in Stochastics and Quality Control
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The major drawback of wind energy relies in its variability in time, which necessitates specific strategies to be settled. One such strategy can be the coordination of wind power production with a co-located power generation of dispatchable energy source (DES), e.g., thermal power station, combined heat and power plant, gas turbine or compressed air energy storage. In this paper, we consider an energy producer that generates power by means of a wind park and of a DES and sells the produced energy to an isolated grid. We determine the optimal quantity of energy produced by a DES, given the unit cost of this energy, that a power producer should buy and use to hedge against the risk inherent in the production of energy through wind turbines. We determine the optimal quantity by solving a static optimization problem taking into account the possible dependence between the amount of energy produced by wind turbines and electricity prices by using a copula function. Several particular cases are studied that allow the determination of the optimal solution in an analytical closed form. Finally, a numerical example concerning a real 48 MW wind farm located in Poland and Polish Power Exchange shows the possibility of implementing the model in real-life problems.

ACS Style

Guglielmo D’Amico; Filippo Petroni; Robert Adam Sobolewski. Optimal Control of a Dispatchable Energy Source for Wind Energy Management. Stochastics and Quality Control 2019, 34, 19 -34.

AMA Style

Guglielmo D’Amico, Filippo Petroni, Robert Adam Sobolewski. Optimal Control of a Dispatchable Energy Source for Wind Energy Management. Stochastics and Quality Control. 2019; 34 (1):19-34.

Chicago/Turabian Style

Guglielmo D’Amico; Filippo Petroni; Robert Adam Sobolewski. 2019. "Optimal Control of a Dispatchable Energy Source for Wind Energy Management." Stochastics and Quality Control 34, no. 1: 19-34.

Preprint
Published: 05 December 2018 in SSRN Electronic Journal
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We propose a dividend stock valuation model where multiple dividend growth series and their dependencies are modelled using a multivariate Markov chain. Our model advances existing Markov chain stock models. First, we determine assumptions that guarantee the finiteness of the price and risk as well as the fulfilment of transversality conditions. Then, we compute the first and second order price-dividend ratios by solving corresponding linear systems of equations and show that a different price-dividend ratio is attached to each combination of states of the dividend growth process of each stock. Subsequently, we provide a formula for the computation of the variances and covariances between stocks in a portfolio. Finally, we apply the theoretical model to the dividend series of three US stocks and perform comparisons with existing models.

ACS Style

Guglielmo D’Amico; Riccardo De Blasis. A Multivariate Markov Chain Stock Model. SSRN Electronic Journal 2018, 1 .

AMA Style

Guglielmo D’Amico, Riccardo De Blasis. A Multivariate Markov Chain Stock Model. SSRN Electronic Journal. 2018; ():1.

Chicago/Turabian Style

Guglielmo D’Amico; Riccardo De Blasis. 2018. "A Multivariate Markov Chain Stock Model." SSRN Electronic Journal , no. : 1.

Conference paper
Published: 05 December 2018 in Stochastic Processes and Applications
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In this paper we study the high frequency dynamic of financial volumes of traded stocks by using a semi-Markov approach. More precisely we assume that the intraday logarithmic change of volume is described by a weighted-indexed semi-Markov chain model. Based on this assumptions we show that this model is able to reproduce several empirical facts about volume evolution like time series dependence, intra-daily periodicity and volume asymmetry. Results have been obtained from a real data application to high frequency data from the Italian stock market from first of January 2007 until end of December 2010.

ACS Style

Guglielmo D’Amico; Fulvio Gismondi; Filippo Petroni. A New Approach to the Modeling of Financial Volumes. Stochastic Processes and Applications 2018, 363 -373.

AMA Style

Guglielmo D’Amico, Fulvio Gismondi, Filippo Petroni. A New Approach to the Modeling of Financial Volumes. Stochastic Processes and Applications. 2018; ():363-373.

Chicago/Turabian Style

Guglielmo D’Amico; Fulvio Gismondi; Filippo Petroni. 2018. "A New Approach to the Modeling of Financial Volumes." Stochastic Processes and Applications , no. : 363-373.

Research article
Published: 13 October 2018 in Annals of Finance
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This paper uses an Indexed Markov Chain to model high frequency price returns of quoted rms. Introducing an Index process permits consideration of endogenous market volatility, and two important stylized facts of financial time series can be taken into account: long memory and volatility clustering. This paper rst proposes a method to optimally determine the state space of the Index process, which is based on a change-point approach for Markov chains. Furthermore, we provide an explicit formula for the probability distribution function of the rst change of state of the Index process. Results are illustrated with an application to intra-day firm prices.

ACS Style

Guglielmo D’Amico; Ada Lika; Filippo Petroni. Change point dynamics for financial data: an indexed Markov chain approach. Annals of Finance 2018, 15, 247 -266.

AMA Style

Guglielmo D’Amico, Ada Lika, Filippo Petroni. Change point dynamics for financial data: an indexed Markov chain approach. Annals of Finance. 2018; 15 (2):247-266.

Chicago/Turabian Style

Guglielmo D’Amico; Ada Lika; Filippo Petroni. 2018. "Change point dynamics for financial data: an indexed Markov chain approach." Annals of Finance 15, no. 2: 247-266.

Journal article
Published: 25 June 2018 in International Journal of Financial Studies
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In this paper, we apply information theory measures and Markov processes in order to analyse the inequality in the distribution of the financial risk in a pool of countries. The considered financial variables are sovereign credit ratings and interest rates of sovereign government bonds of European countries. This paper extends the methodology proposed in our previous work, by allowing the possibility to consider a continuous time process for the credit rating evolution so that complete observations of rating histories and credit spreads can be considered in the analysis. Obtained results suggest that the continuous time model fits real data better than the discrete one and confirm the existence of a different risk perception among the three main rating agencies: Fitch, Moody’s and Standard & Poor’s. The application of the model has been performed by a software we developed, the full code is available on-line allowing the replication of all results.

ACS Style

Guglielmo D’Amico; Philippe Regnault; Stefania Scocchera; Loriano Storchi. A Continuous-Time Inequality Measure Applied to Financial Risk: The Case of the European Union. International Journal of Financial Studies 2018, 6, 62 .

AMA Style

Guglielmo D’Amico, Philippe Regnault, Stefania Scocchera, Loriano Storchi. A Continuous-Time Inequality Measure Applied to Financial Risk: The Case of the European Union. International Journal of Financial Studies. 2018; 6 (3):62.

Chicago/Turabian Style

Guglielmo D’Amico; Philippe Regnault; Stefania Scocchera; Loriano Storchi. 2018. "A Continuous-Time Inequality Measure Applied to Financial Risk: The Case of the European Union." International Journal of Financial Studies 6, no. 3: 62.

Journal article
Published: 01 June 2018 in European Journal of Operational Research
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ACS Style

Guglielmo D’Amico; Filippo Petroni. Copula based multivariate semi-Markov models with applications in high-frequency finance. European Journal of Operational Research 2018, 267, 765 -777.

AMA Style

Guglielmo D’Amico, Filippo Petroni. Copula based multivariate semi-Markov models with applications in high-frequency finance. European Journal of Operational Research. 2018; 267 (2):765-777.

Chicago/Turabian Style

Guglielmo D’Amico; Filippo Petroni. 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance." European Journal of Operational Research 267, no. 2: 765-777.

Conference paper
Published: 27 May 2018 in Advances in Intelligent Systems and Computing
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Performing a maintenance of wind energy system components under good wind conditions may lead to energy not served and finally – to financial losses. The best starting time of preventive maintenance will be, that reduces the energy not served in most. To find this time, a decision model is desired, where many circumstances should be taken into account, i.e. (i) the number and the order of components to be maintained, (ii) component maintenance duration, and (iii) wind turbine(s) output power prediction. Usually, preventive maintenance is planned a few days or weeks in advance. One of the decision problem representations can be influence diagram that enables choosing a decision alternative that has the lowest expected utility (energy not served). The paper presents an decision model that can support decisions-making on starting time of preventive maintenance and maintenance order of wind energy system components. The model relies on influence diagram. The conditional probability distribution of a chance nodes of the diagram are obtained relying on Bayesian networks (BN), whereas the utilities of value node in the diagram are calculated thanks to the second order semi-Markov chains (SMC). The example shows the application of the model in real case of two wind turbines located in Poland. Both the parameters of Bayesian network nodes and semi-Markov chain are derived from real data recorded by SCADA system of the both turbines and weather forecast.

ACS Style

Robert Adam Sobolewski; Guglielmo D’Amico; Filippo Petroni. Decision Model of Wind Turbines Maintenance Planning. Advances in Intelligent Systems and Computing 2018, 440 -450.

AMA Style

Robert Adam Sobolewski, Guglielmo D’Amico, Filippo Petroni. Decision Model of Wind Turbines Maintenance Planning. Advances in Intelligent Systems and Computing. 2018; ():440-450.

Chicago/Turabian Style

Robert Adam Sobolewski; Guglielmo D’Amico; Filippo Petroni. 2018. "Decision Model of Wind Turbines Maintenance Planning." Advances in Intelligent Systems and Computing , no. : 440-450.

Article
Published: 07 February 2018 in Sankhya B
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This study presents a model of income evolution from which dynamic versions of commonly used static poverty measures are derived. The dynamic indexes are calculated both for finite- and infinite-size economic systems. Probabilistic convergence results prove that the infinite-size system can be conveniently used to approximate the finite-size system in an effective way. Secondly, poverty indexes estimation based on micro-data are discussed under different sampling schemes and it is proved that they are strongly consistent. A hypothetical example is used to show the dynamic evolution of the poverty and the estimation methodologies.

ACS Style

Guglielmo D’Amico; Philippe Regnault. Dynamic Measurement of Poverty: Modeling and Estimation. Sankhya B 2018, 80, 305 -340.

AMA Style

Guglielmo D’Amico, Philippe Regnault. Dynamic Measurement of Poverty: Modeling and Estimation. Sankhya B. 2018; 80 (2):305-340.

Chicago/Turabian Style

Guglielmo D’Amico; Philippe Regnault. 2018. "Dynamic Measurement of Poverty: Modeling and Estimation." Sankhya B 80, no. 2: 305-340.

Preprint
Published: 05 February 2018
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A new branch based on Markov processes is developing in the recent literature of financial time series modeling. In this paper, an Indexed Markov Chain has been used to model high frequency price returns of quoted firms. The peculiarity of this type of model is that through the introduction of an Index process it is possible to consider the market volatility endogenously and two very important stylized facts of financial time series can be taken into account: long memory and volatility clustering. In this paper, first we propose a method for the optimal determination of the state space of the Index process which is based on a change-point approach for Markov chains. Furthermore we provide an explicit formula for the probability distribution function of the first change of state of the index process. Results are illustrated with an application to intra-day prices of a quoted Italian firm from January $1^{st}$, 2007 to December $31^{st}$ 2010.

ACS Style

Guglielmo D'amico; Ada Lika; Filippo Petroni. Indexed Markov Chains for financial data: testing for the number of states of the index process. 2018, 1 .

AMA Style

Guglielmo D'amico, Ada Lika, Filippo Petroni. Indexed Markov Chains for financial data: testing for the number of states of the index process. . 2018; ():1.

Chicago/Turabian Style

Guglielmo D'amico; Ada Lika; Filippo Petroni. 2018. "Indexed Markov Chains for financial data: testing for the number of states of the index process." , no. : 1.

Preprint
Published: 01 January 2018
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A new branch based on Markov processes is developing in the recent literature of financial time series modeling. In this paper, an Indexed Markov Chain has been used to model high frequency price returns of quoted firms. The peculiarity of this type of model is that through the introduction of an Index process it is possible to consider the market volatility endogenously and two very important stylized facts of financial time series can be taken into account: long memory and volatility clustering. In this paper, first we propose a method for the optimal determination of the state space of the Index process which is based on a change-point approach for Markov chains. Furthermore we provide an explicit formula for the probability distribution function of the first change of state of the index process. Results are illustrated with an application to intra-day prices of a quoted Italian firm from January $1^{st}$, 2007 to December $31^{st}$ 2010.

ACS Style

Guglielmo D'amico; Ada Lika; Filippo Petroni. Indexed Markov Chains for financial data: testing for the number of states of the index process. 2018, 1 .

AMA Style

Guglielmo D'amico, Ada Lika, Filippo Petroni. Indexed Markov Chains for financial data: testing for the number of states of the index process. . 2018; ():1.

Chicago/Turabian Style

Guglielmo D'amico; Ada Lika; Filippo Petroni. 2018. "Indexed Markov Chains for financial data: testing for the number of states of the index process." , no. : 1.