This paper investigates the activity of a multi-utility that uses Waste-to-Energy (WtE) and cogen... more This paper investigates the activity of a multi-utility that uses Waste-to-Energy (WtE) and cogeneration (COG) plants to provide services in the heat and in the electricity markets. We assume that it employs WtE and COG units to participate in the day-ahead and real-time electricity markets and, with the support of heat-only units, it satisfies the heat demand of local district heating areas (DHAs). We use stochastic programming to develop three linked problems that describe the sequence of the decision process regarding the operation of WtE and COG facilities: (i) the first problem considers the point of view of the multi-utility that defines the day-ahead and the real-time heat scheduling of its plants and the maximum amount of electricity that WtE and COG units can offer in the day-ahead electricity market, taking into account the uncertainty of the real-time heat demand; (ii) the second problem models the day-ahead electricity market cleared by the Power Exchange, where the elec...
In order to characterize non-linear system dynamics and to generate term structures of joint dist... more In order to characterize non-linear system dynamics and to generate term structures of joint distributions, we propose a flexible and multidimensional approach, which exploits Wasserstein barycentric coordinates for histograms. We apply this methodology to study the relationships between the performance in the European market of the renewable energy sector and that of the fossil fuel energy one. Our methodology allows us to estimate the term structure of conditional joint distributions. This optimal barycentric interpolation can be interpreted as a posterior version of the joint distribution with respect to the prior contained in the past histograms history. Once the underlying dynamics mechanism among the set of variables are obtained as optimal Wasserstein barycentric coordinates, the learned dynamic rules can be used to generate term structures of joint distributions.
Considering the attention placed on SMEs in the new Basel Capital Accord, we propose a set of Bay... more Considering the attention placed on SMEs in the new Basel Capital Accord, we propose a set of Bayesian and classical longitudinal models to predict SME default probability, taking unobservable firm and business sector heterogeneities as well as analysts' recommendations into account. We compare this set of models in terms of forecasting performances, both in-sample and out-of-sample. Furthermore, we propose a novel financial loss function to measure the costs of an incorrect classification, including both the missed ...
In a competitive environment a proper evaluation of the financial status and performance of a fir... more In a competitive environment a proper evaluation of the financial status and performance of a firm is an important issue. Different kind and source of infor- mation should be taken into account. Among the possible solutions, we propose to use Bayesian Networks as a quantitative management tool for firm performance eval- uation. Via the use of the network we can combine accounting data with qualitative information related to industry environment, ownership, management and board com- position. Bayesian Networks allow to describe the relationship between the examined variables in an immediate way, and permit to identify, in a mouse click time scenarios that could lead to financial distress.
Studies in Classification, Data Analysis, and Knowledge Organization, 2018
In order to model and explain the dynamics of the market, different types and sources of informat... more In order to model and explain the dynamics of the market, different types and sources of information should be taken into account. We propose to use a Bayesian network as a quantitative financial tool for market signals detection. We combine and incorporate in the model, accounting, market, and sentiment data. The network is used to describe the relationships among the examined variables in an immediate way. Furthermore, it permits to identify in a mouse-click time scenario that could lead to operative signals. An application to the analysis of S&P 500 index is presented.
This paper investigates the activity of a multi-utility that uses Waste-to-Energy (WtE) and cogen... more This paper investigates the activity of a multi-utility that uses Waste-to-Energy (WtE) and cogeneration (COG) plants to provide services in the heat and in the electricity markets. We assume that it employs WtE and COG units to participate in the day-ahead and real-time electricity markets and, with the support of heat-only units, it satisfies the heat demand of local district heating areas (DHAs). We use stochastic programming to develop three linked problems that describe the sequence of the decision process regarding the operation of WtE and COG facilities: (i) the first problem considers the point of view of the multi-utility that defines the day-ahead and the real-time heat scheduling of its plants and the maximum amount of electricity that WtE and COG units can offer in the day-ahead electricity market, taking into account the uncertainty of the real-time heat demand; (ii) the second problem models the day-ahead electricity market cleared by the Power Exchange, where the elec...
In order to characterize non-linear system dynamics and to generate term structures of joint dist... more In order to characterize non-linear system dynamics and to generate term structures of joint distributions, we propose a flexible and multidimensional approach, which exploits Wasserstein barycentric coordinates for histograms. We apply this methodology to study the relationships between the performance in the European market of the renewable energy sector and that of the fossil fuel energy one. Our methodology allows us to estimate the term structure of conditional joint distributions. This optimal barycentric interpolation can be interpreted as a posterior version of the joint distribution with respect to the prior contained in the past histograms history. Once the underlying dynamics mechanism among the set of variables are obtained as optimal Wasserstein barycentric coordinates, the learned dynamic rules can be used to generate term structures of joint distributions.
Considering the attention placed on SMEs in the new Basel Capital Accord, we propose a set of Bay... more Considering the attention placed on SMEs in the new Basel Capital Accord, we propose a set of Bayesian and classical longitudinal models to predict SME default probability, taking unobservable firm and business sector heterogeneities as well as analysts' recommendations into account. We compare this set of models in terms of forecasting performances, both in-sample and out-of-sample. Furthermore, we propose a novel financial loss function to measure the costs of an incorrect classification, including both the missed ...
In a competitive environment a proper evaluation of the financial status and performance of a fir... more In a competitive environment a proper evaluation of the financial status and performance of a firm is an important issue. Different kind and source of infor- mation should be taken into account. Among the possible solutions, we propose to use Bayesian Networks as a quantitative management tool for firm performance eval- uation. Via the use of the network we can combine accounting data with qualitative information related to industry environment, ownership, management and board com- position. Bayesian Networks allow to describe the relationship between the examined variables in an immediate way, and permit to identify, in a mouse click time scenarios that could lead to financial distress.
Studies in Classification, Data Analysis, and Knowledge Organization, 2018
In order to model and explain the dynamics of the market, different types and sources of informat... more In order to model and explain the dynamics of the market, different types and sources of information should be taken into account. We propose to use a Bayesian network as a quantitative financial tool for market signals detection. We combine and incorporate in the model, accounting, market, and sentiment data. The network is used to describe the relationships among the examined variables in an immediate way. Furthermore, it permits to identify in a mouse-click time scenario that could lead to operative signals. An application to the analysis of S&P 500 index is presented.
Uploads