Abstract: In this paper, we come up with an original trading strategy on Bitcoins. The methodology we propose is profit-oriented, and it is based on buying or selling the so-called Contracts for Difference, so that the investor’s gain, assessed at a given future time t, is obtained as the difference between the predicted Bitcoin price and an apt threshold. Starting from some empirical findings, and passing through the specification of a suitable theoretical model for the Bitcoin price process, we are able to provide possible investment scenarios, thanks to the use of a Recurrent Neural Network with a Long Short-Term Memory for predicting purposes. PubDate: 2021-03-13

Abstract: We derive sufficient conditions for non-emptiness of the efficient sets for stochastic dominance relations, usually employed in economics and finance. We do so via the concept of stochastic spanning and its characterization by a saddle-type property. Under the appropriate framework, sufficiency takes the form of semicontinuity of a related functional. In some cases, this boils down to weak continuity of the parameterization of the underlying set of probability distributions. PubDate: 2021-03-11

Abstract: This work aims to offer a contribution in the analysis and management, from an economic and financial point of view, of the flood risk, and extended to the hydrogeological risk, from the perspective of a public administration. As main responsible actor for containing the phenomenon through the maintenance of the territory, public administration is responsible for the cost of restoring of the services that have been damaged by this type of phenomenon. The assets of which the public administration must ensure the restoration are all public infrastructures (i.e. transportation, energy and water supply system, communication) together with the damage suffered by private property, if these affect services to be guaranteed to the population. In this work, the authors propose possible strategies that a public administration can put in place to deal with flood risk. Three main strategies are analysed: an absolute passivity that provides for the payment of damages as they occur (i.e. business-as-usual scenario), a classic insurance scheme, a resilient and innovative insurance scheme. The economic–financial profiles of these strategies proposed in this work put an emphasis on how the assumption of a time horizon can change the convenience of one strategy compared to the others. This study highlights the key role of the quantification of flood risk mitigation measure from an engineering perspective, and their potential issues to pursue these objectives in connection to the regulatory framework of the public administrations. This synergy is supported by the potential use of Blockchain-based tools. Within the paper is highlighted the key role that such platform IT data management platform could have within risk analysis and management schemes, both as a data collection tool and as certification of the various steps necessary to complete the process. PubDate: 2021-03-01

Abstract: The global reforms to public pension schemes over the last thirty years have progressively reduced individuals’ post-retirement social security income. In order to compensate for this, individuals join pension funds and individual plans to increase their wealth at retirement. These types of fully funded plans generally give individuals the opportunity to withdraw the capital accumulated into their scheme or to convert it into an annuity. In this paper, we analyse individuals’ post-retirement choices to allocate the wealth at retirement between consumption, risk-free investments and a life annuity. We develop a discrete time optimisation model, in a deterministic framework, with a constant relative risk aversion (CRRA) utility function. We study the effect of a bequest motive and the annuity rate used by the insurer on the optimal choice. Several numerical applications are presented to illustrate the optimal annuitisation decision results and the optimal consumption paths. PubDate: 2021-02-25

Abstract: This study demonstrates the possibility of cyclic capital accumulation in the case in which there are delays in capital implementation and estimation of capital depreciation. For this purpose, a two-sector growth model with Cobb–Douglas production function is built. It is shown that the stability of the balanced growth may change as lengths of delay change. It is also shown that on the stability switching curve the stability is lost and bifurcates to a limit cycle via a Hopf bifurcation. PubDate: 2021-02-17

Abstract: In this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three cryptocurrencies, Bitcoin, Ethereum, and Litecoin, over the period September 1,2015–March 31, 2020. Time series were first mapped into a complex network by the horizontal visibility algorithm in order to revel the structure of their temporal characters and dynamics. Then, the synchrony of the time series was investigated to determine the possibility that the cryptocurrencies under study co-bubble simultaneously. Findings reveal similar complex structures for the three virtual currencies in terms of number and internal composition of communities. To the aim of our analysis, such result proves that price and volume dynamics of the cryptocurrencies were characterized by cyclical patterns of similar wavelength and amplitude over the time period considered. Yet, the value of the slope parameter associated with the exponential distributions fitted to the data suggests a higher stability and predictability for Bitcoin and Litecoin than for Ethereum. The study of synchrony between the time series investigated displayed a different degree of synchronization between the three cryptocurrencies before and after a collapse event. These results could be of interest for investors who might prefer to switch from one cryptocurrency to another to exploit the potential opportunities of profit generated by the dynamics of price and volumes in the market of virtual currencies. PubDate: 2021-02-16

Abstract: We propose a new approach to handle the problem of portfolio optimization for non-life insurance company incorporating the solvency capital requirement (SCR), market views and their confident levels, several equality and inequality real-world constraints and transaction costs. We analyze two case studies: first, we consider a tri-objective optimization problem in which we minimize the Market SCR, the variance of the so-called basic own funds (BOF) and maximize the return of portfolio; secondly, we consider bi-objective optimization problem in which we minimize the variance of BOF and maximize the return of portfolio while considering the Market SCR as a constraint. We introduce a scenario-based framework in which the reference model is given by an internal model. By entropy pooling approach, we blended market views and their confident levels with the reference model to build the posterior distribution. The latter is used to compute the variance of BOF and the portfolio return. In both case studies, we obtain good results in term of risk-reward tradeoff and diversification. PubDate: 2021-02-08

Abstract: In this paper, we apply dynamic factor analysis to model the joint behaviour of Bitcoin, Ethereum, Litecoin and Monero, as a representative basket of the cryptocurrencies asset class. The empirical results suggest that the basket price is suitably described by a model with two dynamic factors. More precisely, we detect one integrated and one stationary factor until the end of August 2019 and two integrated factors afterwards. Based on this evidence, we define a multiple long-short trading strategy which proves profitable when the second factor is stationary. PubDate: 2021-02-05

Abstract: In recent years, the study of the evolution of non-compliant behaviour in public procurement has been widely developed due to the growing economic relevance of this phenomenon. When such a question is formalized in terms of a dynamical model, new insights can be pursued, related to the possible evolution from a situation with low dishonesty level to high dishonesty level or vice versa. The present model considers an evolutionary adaptation process explaining whether honest or dishonest behaviour prevails in society at any given time by assuming endogenous monitoring by the State. We will distinguish between a scenario in which firms converge to monomorphic configurations (all honest or all dishonest) and a scenario in which firms converge to polymorphic compositions (that is with coexistence of both groups), depending on the relevant parameters. By making use of both analytical tools and numerical simulations, the present work aims at explaining the effectiveness of economic policies to reduce or eliminate non-compliant behaviour. Social stigma is found to play a key role: if the “inner attitude toward honesty” of a country is not strong enough, then dishonesty cannot be ruled out. However, increasing both the fine level attached to dishonest behaviour and the monitoring effort by the State can reduce asymptotic dishonesty levels and escape form the dishonesty trap. PubDate: 2021-01-23 DOI: 10.1007/s10203-021-00317-y

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 DOI: 10.1007/s10203-020-00314-7

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 DOI: 10.1007/s10203-020-00312-9

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 DOI: 10.1007/s10203-020-00310-x

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 DOI: 10.1007/s10203-020-00288-6

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 DOI: 10.1007/s10203-020-00290-y

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 DOI: 10.1007/s10203-020-00309-4

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 DOI: 10.1007/s10203-020-00297-5

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 DOI: 10.1007/s10203-020-00304-9

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 DOI: 10.1007/s10203-020-00292-w