Abstract: Abstract Whereas much research has largely investigated the safe haven, diversifier and hedge proprieties of cryptocurrency, very few papers have analyzed the hedging issue of cryptocurrency with other assets. As such, this paper attempts to investigate the possibility if Bitcoin can be hedged by selected fiat currencies (EUR, JPY and GBP) as Bitcoin prices have experienced high and persistent volatility. To do so, we compute optimal hedge ratios between Bitcoin and fiat currencies over the period 02/02/2012–30/11/2017 based on the VAR-DCC-GARCH model, VAR-ADCC-GARCH model and VAR-component GARCH-DCC model. A rolling window analysis is employed to establish out-of-sample one-step-ahead forecasts of dynamic conditional correlations between different assets. This leads to establish time-varying hedge ratios and thus dynamic cross-hedging Bitcoin/fiat currency markets. The empirical results clearly show the time-varying correlations between Bitcoin and fiat currencies under different specifications, implying a dynamic behavior of the relationship between such assets. For all the proposed models, such dynamic correlations are rather characterized by trending downward over the period under study. The results also display time-varying hedge ratios which lead to an ongoing regular demand for rebalancing the hedged positions under different specifications. As a matter of fact, using various models which take into account different aspects of volatility and correlation structures allows to better implement dynamic hedging strategies. PubDate: 2021-01-06
Abstract: Abstract This paper analyzes the relationships between volatilities of five cryptocurrencies, American indices (S&P500, Nasdaq, and VIX), oil, and gold. The results of the BEKK-GARCH model show evidence of a higher volatility spillover between cryptocurrencies and lower volatility spillover between cryptocurrencies and financial assets. The results of the DCC-GARCH model identify an important effect of the launch of Bitcoin futures. During the stability period, the overarching implications of the results are that there is a persistence of correlation between cryptocurrencies in high positive value and low dynamic conditional correlations between cryptocurrencies and financial assets. Also, we find that Bitcoin and gold are considered hedges for the US investors before the coronavirus crisis. Our results show that cryptocurrencies may offer diversification benefits for investors and are diversifiers during the stability period. At the beginning of 2020, we observe that the conditional correlation increased between cryptocurrencies, stock indexes, and oil which confirm the effect of the coronavirus contagion between them. Unlike gold, digital assets are not a safe haven for US investors during the coronavirus crisis. PubDate: 2021-01-03
Abstract: Abstract This research work is based on the concept of the one-factor copula model together with the discrete Fourier transform, which is applied to reduce the dimensionality problems associated with the basket default swap pricing. We employ the Gaussian, the student-t and the Clayton one-factor copula to estimate the conditional probability of default. Incorporating the Fourier transform together with the distribution function of a counting process, we derive the quasi-analytical expression for the computation of the swap payment legs. We compute the conditional characteristic function for the corresponding portfolio loss distribution using the fast Fourier transform. Then, employ numerical integration with the aid of the inverse fast Fourier transform to retrieve the distribution function or the unconditional characteristic function. Our results show that in the absence of the trending simulation method, a semi-analytic method which involves the applications of the discrete Fourier transform can be utilized to price the basket credit default swaps. PubDate: 2021-01-02
Abstract: Abstract Low-rank problems are nothing but nonlinear minimization problems over polyhedrons where a linear transformation of the variables provides an objective function which actually depends on very few variables. These problems are often used in applications, for example, in concave quadratic minimization problems, multiobjective/bicriteria programs, location–allocation models, quantitative management science, data envelopment analysis, efficiency analysis and performance measurement. The aim of this paper is to deepen on the study of a solution method for a class of rank-two nonconvex problems having a polyhedral feasible region expressed by means of inequality/box constraints and an objective function of the kind \(\phi (c^Tx+c_0,d^Tx+d_0)\) . The rank-two structure of the problem allows to determine various localization conditions and underestimation functions. The stated theoretical conditions allow to determine a solution algorithm for the considered class of rank-two problems whose performance is witnessed by means of a deep computational test. PubDate: 2020-12-01
Abstract: Abstract In light of increasing health expenditure and following an economic crisis, the ADSE system (a health insurance system exclusive for the Portuguese civil servants) introduced a new policy where members were allowed to leave the system, and also for new employees to opt out. This decision, however, was permanent, and, as it will be shown, far from trivial. The aim of this study is to provide some indications on the total costs of both the ADSE and a private health insurance plan over the working life of an individual, taking into account certain life-changing events such as marriage and children. The choice is made based on the net present value of these total costs, and it is rational from a financial perspective. Because such a permanent decision is highly dependent on the assumptions made, a sensitivity analysis to certain variables, in particular, income, prices of medical treatments and frequency of use, is performed in order to discover the break-even point, that is, the value at which the individual would be indifferent between the two options. PubDate: 2020-12-01
Abstract: Abstract We consider the overlapping generation model formulated in Dioikitopoulos (J Econ Dyn Control 93:260–276, 2018). Its innovative approach involves endogenous adaptations of the deficit/surplus to debt and income levels through an empirically estimated fiscal policy rule. We improve the analysis of the model in order to tackle the issue of debt sustainability. In detail, we derive the analytic expressions of stationary states of the model as well as necessary and sufficient existence conditions.Moreover, our mathematical analysis sheds new light on the role of fiscal parameters and policy prescriptions. As a result, low deficit levels can be associated with the presence of steady-state configurations, which is a prerequisite for sustainable economic patterns to be achieved. PubDate: 2020-12-01
Abstract: Abstract Coherence of preferences has been a long standing issue in decision analysis. This paper focuses on preferences expressed by means of pairwise comparison matrices. In particular, by following the idea proposed in previous papers concerning the relation between some coherence conditions and row orders of the matrix, we provide similar relations for further coherence conditions that are the restricted max–max transitivity, the index exchange ability and the quasi-consistency. PubDate: 2020-12-01
Abstract: Abstract Coherence of preferences, and the measurement of its violation, has been a long-standing issue in decision analysis. This paper continues the inquiry into coherence conditions for pairwise comparisons following a distance-based approach, in which the deviations from coherence conditions are measured on a continuous scale. Firstly, we consider eight coherence conditions already introduced in the literature and provide a complete study on their inclusion relations. Then, we consider four of these conditions and introduce optimization problems to quantify the extent of their violation. PubDate: 2020-12-01
Abstract: Abstract The analytic hierarchy process is a widely used multi-criteria decision-making method that involves the construction of pairwise comparison matrices. To infer a decision, a consistent or near-consistent matrix is desired, and therefore, several methods have been developed to control or improve the overall consistency of the matrix. However, controlling the overall consistency does not necessarily prevent having strong local inconsistencies. Local inconsistencies are local distortions which can lead to rank reversal when a new alternative is added or deleted. To address this problem, we propose an algorithm for controlling the inconsistency during the construction of the pairwise comparison matrix. The proposed algorithm assists decision makers whilst entering their judgments and does not allow strong local inconsistencies. This algorithm is based on the transitivity rule and has been verified through statistical simulations. Appropriate thresholds of acceptable evaluations have been inferred from these simulations. We demonstrate that the proposed algorithm is a helpful decision aid to decision makers when entering pairwise comparison judgments. PubDate: 2020-11-05
Abstract: Abstract We extend the arithmetic multi-factor electricity spot price model proposed by Benth et al. (Appl Math Finance 14(2):153–169, 2007) by adding stochastic mean-level processes to their model and by taking additional information on the future behavior of these mean-level processes into account. The available anticipative information is modeled by an initially enlarged filtration in our paper. We further derive pricing formulas for electricity forwards under future information and investigate the associated information premium. PubDate: 2020-10-06
Abstract: Abstract This paper proposes to measure the museums performance with a model that combines the Data Envelopment Analysis (DEA) and Balanced Scorecard (BSC) methodologies with a third method, the analytic hierarchy process (AHP), which is often used to support decision making. Starting from the two-stage DEA–BSC model of Basso et al. (Omega Int J Manag Sci 81:67–84, 2018), which integrates DEA and BSC, we explore the advantages to consider also the AHP methodology, with the aim to include the judgement of some museums’ experts on the relative importance of the BSC perspectives in the performance evaluation model. A first approach uses directly the AHP priorities derived from the judgements expressed by the museums’ experts interviewed to determine the weights to aggregate the four BSC performance scores into an overall performance indicator. A second approach uses the judgments of the museums’ experts indirectly to introduce proper restrictions on the output weights of the second-stage DEA model. With this approach, we overcome the problem arising from the dispersion of the preferences within the group of experts, that may heavily affects the first approach. Both approaches proposed in this contribution are applied to the case study of the municipal museums of Venice. PubDate: 2020-09-22
Abstract: Abstract Data envelopment analysis (DEA) is a nonparametric frontier assessment method used to evaluate the relative efficiency of similar decision-making units (DMUs). This method provides benchmarking information regarding the removal of inefficiency. In conventional DEA models, the view of the decision maker (DM) is ignored and the performance of each DMU is solely determined by the observations retrieved. The current paper exploits the structural similarity existing between DEA and multiple objective programming to define a model that incorporates the preferences of DMs in the evaluation process of DMUs. Given the potential unfeasibility of the input and output targets selected by the DM, the model defines an interactive procedure that considers minimum and maximum acceptable objective levels. Given the feasible levels located closer to the targets selected by the DM, a program improving upon the feasible allocations is designed so that the suggested benchmark approximates the requirements fixed by the DM as much as possible. A real-life case study is included to illustrate the efficacy and applicability of the proposed hybrid procedure. PubDate: 2020-09-20
Abstract: Abstract This paper studies the properties of an inconsistency index of a pairwise comparison matrix under the assumption that the index is defined as a norm-induced distance from the nearest consistent matrix. Under additive representation of preferences, it is proved that an inconsistency index defined in this way is a seminorm in the linear space of skew-symmetric matrices and several relevant properties hold. In particular, this linear space can be partitioned into equivalence classes, where each class is an affine subspace and all the matrices in the same class share a common value of the inconsistency index. The paper extends in a more general framework some results due, respectively, to Crawford and to Barzilai. It is also proved that norm-based inconsistency indices satisfy a set of six characterizing properties previously introduced, as well as an upper bound property for group preference aggregation. PubDate: 2020-08-30
Abstract: Abstract In this note, the characterization problem of individual demand and excess demand functions is revisited. It is assumed that the individual’s income is price dependent. When the income function is homogeneous of degree one, we show that similar conditions characterize both demand and excess demand functions. PubDate: 2020-08-24
Abstract: Abstract In this contribution, we propose a healthcare decision support system. Nowadays, it is commonly recognized that quantitative tools and decision support can increase the benefits and the performances of healthcare systems, and for this, different multiple criteria methods were proposed in many branches of medicine. The approach we propose is based on non-additive measures and the Choquet integral. This methodology has been intensively applied in many real-world applications, given its capability to represent interactions among criteria, and thus to model a wide range of preference structures. Considering that the diagnosis procedure needs also to take the clinical expertise into account, this method appears particularly tailored for a diagnosis support, mainly when statistical models cannot be applied and/or available data are scarce and knowledge can be inferred by physicians’ opinions. In particular, we propose a disease risk evaluation and compute some associated indicators. Furthermore, an error estimation is performed. As an application, a cardiovascular risk diagnosis model is presented. The proposed methodology, that allows to quantify the disease risk taking into account individual’s medical conditions, can be used for improving healthcare service quality or for pricing and reserving health insurance policies. An application to health insurance pricing is provided. PubDate: 2020-08-19
Abstract: Abstract This paper examines the dynamic effects of consumption externalities in Bosi and Seegmuller (J Math Econ 46:475–492, 2010). We show that only the patient agent holds the entire capital stock at the steady state, while the impatient agent works to finance his consumption. Our main result states that consumption externalities represent the main mechanism that explains the emergence of endogenous fluctuations due to self-fulfilling expectations. Finally, consumption externalities promote the appearance of deterministic cycles of period two. PubDate: 2020-08-14
Abstract: Abstract In conventional data envelopment analysis (DEA) models, the efficiency measurement is carried out by using deterministic data typically referring to past observations. However, in many operative contexts, decision makers are called to predict the future performance for planning and control purposes. In these situations, ignoring the stochastic nature of data might lead to misleading results. The paper proposes a stochastic DEA approach based on the chance constrained paradigm and accounts for risk measured in terms of tail \(\gamma \) -mean. A deterministic equivalent reformulation is presented under the assumption of discrete distributions. The computational experiments are carried out on an empirical case study related to the evaluation of the credit risk. The results demonstrate the validity of the proposed approach as proactive evaluation technique. PubDate: 2020-08-13
Abstract: Abstract Groundwater is a common resource that has been wasted for years. Today, we pay the consequences of such inappropriate exploitation and we are aware that it is necessary to realize policies in order to guarantee the use of this resource for future generations. In fact, the irrational exploitation of water by agents, nevertheless it is a renewable resource, may cause its exhaustion. In our paper, we develop a differential game to determine the efficient extraction of groundwater resource among overlapping generations. We consider intragenerational as well as intergenerational competition between extractors that exploit the resource in different time intervals, and so the horizons of the players in the game are asynchronous. Feedback equilibria have been computed in order to determine the optimal extraction rate of “young” and “old” agents that coexist in the economy. The effects of the withdrawal by several generations are numerically and graphically analyzed in order to obtain results on the efficiency of the groundwater resource. PubDate: 2020-07-07
Hybrid journal (It can contain Open Access articles)
