Aleš Ahčan
University of Ljubljana
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Publication
Featured researches published by Aleš Ahčan.
Post-communist Economies | 2013
Sašo Polanec; Aleš Ahčan; Miroslav Verbič
In this article we analyse old-age retirement decisions of Slovenian men and women eligible to retire in the period 1997–2003. In comparison with established market economies we find relatively high probabilities of retirement that decline with age. This unusual pattern can partly be attributed to weak incentives to work, inherent in the design of the pension system and reflected in predominantly negative values of accruals, and to transition-specific increase in wage inequality in the late 1980s and early 1990s. This is reflected in low wages and relatively high pensions of less productive (skilled) workers and vice versa. We find that the probability of retirement decreases with option value of work and net wages, although the response to the former, when controlling for the latter, is rather weak. Our results also imply that less educated individuals and individuals with greater personal wealth are more likely to retire.
Archive | 2003
Janez Praanikar; Velimir Anton Bole; Aleš Ahčan; Matjaz Koman
In this paper we investigate the export participation of Slovene firms. We first show that sunk costs are an important factor for explaining the export behavior of Slovene firms. Next we show that when the absorption power of the exporting market declines, firms still trade with their established buyers (hysteresis) despite the fact that due to lower prices their exporting revenues decline. We show that this can be explained with high exit costs, which consist of switching costs (costs of replacing stable buyers with new ones) and cost of reducing the production (compensation money for excess workers) and high re-entry costs.
Journal of Computational and Applied Mathematics | 2017
Matej Jovan; Aleš Ahčan
Merton’s model (Merton 1974) has long been a standard for estimating companys probability of default (PD) for listed companies. The major advantage of Mertons model is the use of current market prices to determine the probability of default. The logic behind the model is simple; the market prices best reflect all the relevant information (being forward looking estimates of companys prospect) and should be (and are) superior to the balance sheet disclosures, which at best are ex post realizations of companys performance. It is thus a pity that the benefits (strengths) of Mertons model are hindered by a significant shortcoming of the model namely the assumption of normally distributed returns. As numerous authors point out (Barndorff-Nielsen 1995, Barndorff-Nielsen 1997, Prause 1999, Eberlein 2001, Brambilla et al. 2015), stock returns are not normally distributed which significantly limits the use of model in practice. Moreover the estimates of PDs can be biased downwards exposing the banks to the possibility of undercapitalisation and systematic shocks. It is the purpose of this paper to remedy this situation. Firstly we extend the Merton model by allowing for normal inverse Gaussian (NIG) distributed returns. As several authors point out using the examples of options (Schoutens 2009), NIG in most cases provides a robust statistical platform for estimating stock returns. We further extend our approach by constructing a robust EM algorithm for estimating PDs within the Merton NIG framework. We also test the reliability of the NIG improved Merton model against classical Mertons model for estimating PDs. Applying our results to Ljubljana stock exchange we find that the PD estimates using classical Mertons model are biased, whereas the estimates from NIG Mertons model are robust.
Journal of Computational and Applied Mathematics | 2011
Aleš Ahčan; Igor Masten; Sašo Polanec; Mihael Perman
This paper develops an analytical approximation for the distribution function of a terminal value of a periodic series of buy-and-hold investments placed over a fixed time horizon for the case when log-returns of assets follow a p-th order vector auto-regressive process. The derivation is based on a first order Taylor conditioned approximation with a suitably chosen conditioning variable. The results indicate a remarkably good fit between the approximating procedure and simulations based on realistic parameters.
Quality Engineering | 2005
Janez Prašnikar; Ziga Debeljak; Aleš Ahčan
Journal of Computational and Applied Mathematics | 2006
Aleš Ahčan; Grzegorz Darkiewicz; Marc Goovaerts; Tom Hoedemakers
Insurance Mathematics & Economics | 2014
Aleš Ahčan; Darko Medved; Annamaria Olivieri; Ermanno Pitacco
8th International Congress on Insurance: Mathematics & Economics (IME2004) | 2004
Aleš Ahčan; Grzegorz Darkiewicz; Jan Dhaene; Marc Goovaerts; Tom Hoedemakers
Insurance Mathematics & Economics | 2012
Aleš Ahčan
MPRA Paper | 2010
Sašo Polanec; Aleš Ahčan; Miroslav Verbič