http://ktisis.cut.ac.cy/handle/10488/4909 Search the Channel search http://ktisis.cut.ac.cy/simple-search http://ktisis.cut.ac.cy/handle/10488/6885 Title: European option pricing by using the support vector regression approach<br/><br/>Authors: Andreou, Panayiotis; Charalambous, Chris; Martzoukos, Spiros H.<br/><br/>Abstract: We explore the pricing performance of Support Vector Regression for pricing SandP 500 index call options. Support Vector Regression is a novel nonparametric methodology that has been developed in the context of statistical learning theory, and until now it has not been widely used in financial econometric applications. This new method is compared with the Black and Scholes (1973) option pricing model, using standard implied parameters and parameters derived via the Deterministic Volatility Functions approach. The empirical analysis has shown promising results for the Support Vector Regression models. http://ktisis.cut.ac.cy/handle/10488/6804 Title: Stable parallel algorithms for computing and updating the qr decomposition<br/><br/>Authors: Kontoghiorghes, Erricos John; Clarke, Michael R B<br/><br/>Abstract: n this paper we propose new stable parallel algorithms based on Householder transformations and compound Given's rotations to compute the QR decomposition of a rectangular matrix. The predicted execution time of all algorithms on the massively parallel SIMD array processor AMT DAP-510, have been obtained and analyzed. Modified versions of these algorithms are also considered for updating the QR decomposition, when rows are inserted to the data matrix. http://ktisis.cut.ac.cy/handle/10488/1271 Title: An Improved Oceanic Rainfall Retrieval Algorithm and Results from Seawinds<br/><br/>Authors: Ahmad, K. A.; Jones, W.L.; Kasparis, Takis<br/><br/>Abstract: This paper describes the development of an oceanic rainfall retrieval algorithm that combines both the simultaneous active (radar backscatter) and passive (microwave brightness temperatures) observations from the SeaWinds scatterometer on the QuikSCAT satellite. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and the National Center for Environmental Prediction (NCEP) wind fields. The rain is retrieved on a wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. Due to its broad swath coverage, SeaWinds affords additional independent sampling of the oceanic rainfall, which may contribute to NASA's future Global Precipitation Mission. Results emphasize the powerful rain detection capabilities of the SeaWinds retrieval algorithm. http://ktisis.cut.ac.cy/handle/10488/1261 Title: Triangulated, connected sets for building detection from irregularly spaced LiDAR<br/><br/>Authors: Shorter, N.; Kasparis, Takis<br/><br/>Abstract: A novel method for building detection from irregularly spaced Light Detection and Ranging (LiDAR) data is presented. Using features from the triangulation of the LiDAR data, the proposed method identifies ground points, and differentiates those points from building and non building points. Furthermore, the method differentiates the buildings from one another, subsequently recognizing each building as a unique entity. The primary objective in the design of the proposed algorithm is to completely automate the building detection process such that no user intervention (window or parameter adjustment, selection of control points, apriori knowledge dependency, etc.) is necessary.