University of Ljubljana, Faculty of Economics

About: University of Ljubljana, Faculty of Economics is a based out in . It is known for research contribution in the topics: Productivity & Tourism. The organization has 251 authors who have published 533 publications receiving 16109 citations.

Prediction of relative position of CT slices using a computational intelligence system

Abstract: Graphical abstractDisplay Omitted One of the most common techniques in radiology is the computerized tomography (CT) scan. Automatically determining the relative position of a single CT slice within the human body can be very useful. It can allow for an efficient retrieval of slices from the same body region taken in other volume scans and provide useful information to the non-expert user. This work addresses the problem of determining which portion of the body is shown by a stack of axial CT image slices. To tackle this problem, this work proposes a computational intelligence system that combines semantics-based operators for Genetic Programming with a local search algorithm, coupling the exploration ability of the former with the exploitation ability of the latter. This allows the search process to quickly converge towards (near-)optimal solutions. Experimental results, using a large database of CT images, have confirmed the suitability of the proposed system for the prediction of the relative position of a CT slice. In particular, the new method achieves a median localization error of 3.4cm on unseen data, outperforming standard Genetic Programming and other techniques that have been applied to the same dataset. In summary, this paper makes two contributions: (i) in the radiology domain, the proposed system outperforms current state-of-the-art techniques; (ii) from the computational intelligence perspective, the results show that including a local searcher in Geometric Semantic Genetic Programming can speed up convergence without degrading test performance.

Improved Holt-Winters Method: A Case of Overnight Stays of Tourists in Republic Of Slovenia

Abstract: Exponential smoothing methods are very commonly used for forecasting demand because they are simple, fast and inexpensive The Holt-Winters (HW) methods estimate three smoothing parameters, associated with level, trend and seasonal factors The seasonal variation can be of either an additive or multiplicative form The multiplicative version is used more widely and on average works better than the additive, but if a data series contains some values equal to zero, the multiplicative HW method may not be used In this paper we propose an improved additive HW method and we treat the initial values for the level, trend and seasonal components as well as three smoothing constants as decision variables Through our results we demonstrate that a considerable reduction in forecast error (mean square error) can be achieved The presented new method is applied to the case of overnight stays of tourists in Republic of Slovenia and comparisons with other methods are made on this case study data

Statistical Analysis of Model Risk Concerning Temperature Residuals and its Impact on Pricing Weather Derivatives

Abstract: In this paper we model the daily average temperature via an extended version of the standard Ornstein Uhlenbeck process driven by a Levy noise with seasonally adjusted asymmetric ARCH process for volatility. More precisely, we model the disturbances with the Normal inverse Gaussian (NIG) and Variance gamma (VG) distribution. Besides modeling the residuals we also compare the prices of January out of the money call and put options under normally distributed disturbances and NIG and VG distributed disturbances. The results of numerical analysis demonstrate that the normal model fails to capture adequately tail risk, and consequently significantly misprices out of the money options. Thus one should take extreme care in choosing the appropriate statistical model.

The Term Structure of Implicit Discount Rates in Security Valuation

Abstract: A reformulation of the residual income model is used to generate estimates of discount rates implicit in UK security prices. The terminal value of the infinite valuation model is incorporated into the coefficient on current earnings. By varying the length of the forecast horizon, different combinations of implicit discount rates are revealed that allow the estimation of time-variant costs of equity. Results indicate no specific pattern of discount rates, thus revealing neither myopia on short-term earnings nor excessive optimism on long(er)-term earnings. Surprisingly, there is weak evidence that if any myopia exists, it is concentrated in larger and lower price-earnings firms.