1,721,020 research outputs found
The asymptotic loss distribution in a fat-tailed factor model of portfolio credit risk
Full text linkThis paper extends the standard asymptotic results concerning the percentage loss distribution in the Vasicek uniform model to a setup where the systematic risk factor is non-normally distributed. We show that the asymptotic density in this new setup can still be obtained in closed form; in particular, we derive the return distributions, the densities and the quantile functions when the common factor follows two types of normal mixture distributions (a two-population scale mixture and a jump mixture) and the Student’s t distribution. Finally, we present a real-data application of the technique to data of the Intesa - San Paolo credit portfolio. The numerical experiments show that the asymptotic loss density is highly flexible and provides the analyst with a VaR which takes into account the event risk incorporated in the fat-tailed distribution of the common factor.Factor model, asymptotic loss, Value at Risk.
A Monte Carlo EM Algorithm for the Estimation of a Logistic Auto-logistic Model with Missing Data
Full text linkThis paper proposes an algorithm for the estimation of the parameters of a Logistic Auto-logistic Model when some values of the target variable are missing at random but the auxiliary information is known for the same areas. First, we derive a Monte Carlo EM algorithm in the setup of maximum pseudo-likelihood estimation; given the analytical intractability of the conditional expectation of the complete pseudo-likelihood function, we implement the E-step by means of Monte Carlo simulation. Second, we give an example using a simulated dataset. Finally, a comparison with the standard non-missing data case shows that the algorithm gives consistent results.Spatial Missing Data, Monte Carlo EM Algorithm, Logistic Auto-logistic Model, Pseudo-Likelihood.
Spatial models for flood risk assessment
Full text linkThe problem of computing risk measures associated to flood events is extremely important not only from the point of view of civil protection systems but also because of the necessity for the municipalities of insuring against the damages. In this work we propose, in the framework of an integrated strategy, an operating solution which merges in a conditional approach the information usually available in this setup. First we use a Logistic Auto-Logistic (LAM) model for the estimation of the univariate conditional probabilities of flood events. This approach has two fundamental advantages: it allows to incorporate auxiliary information and does not require the target variables to be indepen- dent. Then we simulate the joint distribution of floodings by means of the Gibbs Sampler. Finally we propose an algorithm to increase ex post the spatial autocorrelation of the simulated events. The methodology is shown to be effective by means of an application to the estimation of the flood probability of Italian hydrographic regions.Flood Risk, Conditional Approach, LAM Model, Pseudo-Maximum Likelihood Estimation, Spatial Autocorrelation, Gibbs Sampler.
A note on maximum likelihood estimation of a Pareto mixture
Full text linkIn this paper we study Maximum Likelihood Estimation of the parameters of a Pareto mixture. Application of standard techniques to a mixture of Pareto is problematic. For this reason we develop two alternative algorithms. The first one is the Simulated Annealing and the second one is based on Cross-Entropy minimization. The Pareto distribution is a commonly used model for heavy-tailed data. It is a two-parameter distribution whose shape parameter determines the degree of heaviness of the tail, so that it can be adapted to data with different features. This work is motivated by an application in the operational risk measurement field: we fit a Pareto mixture to operational losses recorded by a bank in two different business lines. Losses below an unknown threshold are discarded, so that the observed data are truncated. The thresholds used in the two business lines are unknown. Thus, under the assumption that each population follows a Pareto distribution, the appropriate model is a mixture of Pareto where all the parameters have to be estimated.
Compliance by believing: an experimental exploration on social norms and impartial agreements
Full text linkThe main contribution of this paper is twofold. First of all, it focuses on the decisional process that leads to the creation of a social norm. Secondly, it analyses the mechanisms through which subjects conform their behaviour to the norm. In particular, our aim is to study the role and the nature of Normative and Empirical Expectations and their influence on people’s decisions. The tool is the Exclusion Game, a sort of ‘triple mini-dictator game’. It represents a situation where 3 subjects – players A - have to decide how to allocate a sum S among themselves and a fourth subject - player B - who has no decisional power. The experiment consists of three treatments. In the Baseline Treatment participants are randomly distributed in groups of four players and play the Exclusion Game. In the Agreement Treatment in each group participants are invited to vote for a specific non-binding allocation rule before playing the Exclusion Game. In the Outsider Treatment, after the voting procedure and before playing the Exclusion Game, a player A for each group (the outsider) is reassigned to a different group and instructed about the rule chosen by the new group. In all the treatments, at the end of the game and before players are informed about the decisions taken during the Exclusion Game by the other co-players, first order and second order expectations (both normative and empirical) are elicited through a brief questionnaire. The first result we obtained is that subjects’ choices are in line with their empirical (not normative) expectations. The second result is that even a non-binding agreement induces convergence of empirical expectations – and, consequently, of choices. The third results is that expectation of conformity is higher in the partner protocol. This implies that a single outsider breaks the ‘trust and cooperation’ equilibrium.fairness, social norms, beliefs, psychological games, experimental games
Structural models and empirical analysis of technology accumulation and diffusion: a continuous-time econometric approach
No full textin New Econometric Modelling Research, Nova Science Publishers, New York, forthcoming
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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