Clustering and Classification in Option Pricing

This paper reviews the recent option pricing literature and investigates how clustering and classification can assist option pricing models. Specifically, we consider non-parametric modular neural network (MNN) models to price the S&P-500 European call options. The focus is on decomposing and classifying options data into a number of sub-models across moneyness and maturity ranges that are processed individually. The fuzzy learning vector quantization (FLVQ) algorithm we propose generates decision regions (i.e., option classes) divided by ‘intelligent’ classification boundaries. Such an approach improves generalization properties of the MNN model and thereby increases its pricing accuracy

Option Pricing With Modular Neural Networks

This paper investigates a nonparametric modular neural network (MNN) model to price the S&P-500 European call options. The modules are based on time to maturity and moneyness of the options. The option price function of interest is homogeneous of degree one with respect to the underlying index price and the strike price. When compared to an array of parametric and nonparametric models, the MNN method consistently exerts superior out-of-sample pricing performance. We conclude that modularity improves the generalization properties of standard feedforward neural network option pricing models (with and without the homogeneity hint)

PSALM – patent mining tool for competitive intelligence

Patentni dokument je vrijedan izvor informacija. Međutim, nije lako izvući korisne informacije iz njega niti je jednostavno pratiti evidenciju o svim patentima koji mogu biti relevantni. Ovaj rad opisuje strukturu, module, performanse i funkcionalnost PSALM-a, nedavno razvijenog softverskog alata za analizu konkurenata temeljenog na patentnim podacima. PSALM omogućuje preobrazbu sirovih patentnih podataka u smislene i korisne informacije za donošenje poslovnih odluka. Alat se temelji na MySQL bazi podataka i web robotu, oba su podržana potprogramima razvijenima u Java i PHP-u. Patent Search and Analysis for Landscaping and Management (PSALM) alat sakuplja patentne podatke iz javno dostupnih baza podataka, prikuplja i analizira bibliografske parametre patenata, ali i radi dubinsku analizu teksta. Cilj ovog rada je opisati strukturu i funkcije razvijenog softvera, pokazati učinkovitost i točnost njegovih modula (za procesuiranje teksta, grupiranje, vizualizaciju), ali i pokazati njegovu upotrebljivosti kroz dubinski studij slučaja.Patent document is a valuable source of information. However, it is neither easy to extract useful information from patents nor simple to track evidence about all patents that may be relevant. This paper describes PSALM (Patent Search and Analysis for Landscaping and Management), a recently developed software tool for competitive intelligence based on patent data. PSALM enables transformation of raw patent data into meaningful and useful information for business decision making. The tool is based on MySQL database and web robot, both supported by routines developed in Java and PHP. PSALM tool assembles patent data from publicly available data bases, collects and analyses bibliographic parameters of patents, but also does text mining and clustering. The objective of this paper is to describe the structure and functions of developed software, to show efficiency and accuracy of its modules (text processing, clustering, visualisation), as well as to demonstrate its usability through an in-depth case study

QUALINET white paper on definitions of Immersive Media Experience (IMEx)

With the coming of age of virtual/augmented reality and interactive media, numerous definitions, frameworks, and models of immersion have emerged across different fields ranging from computer graphics to literary works. Immersion is oftentimes used interchangeably with presence as both concepts are closely related. However, there are noticeable interdisciplinary differences regarding definitions, scope, and constituents that are required to be addressed so that a coherent understanding of the concepts can be achieved. Such consensus is vital for paving the directionality of the future of immersive media experiences (IMEx) and all related matters. The aim of this white paper is to provide a survey of definitions of immersion and presence which leads to a definition of immersive media experience (IMEx). The Quality of Experience (QoE) for immersive media is described by establishing a relationship between the concepts of QoE and IMEx followed by application areas of immersive media experience. Influencing factors on immersive media experience are elaborated as well as the assessment of immersive media experience. Finally, standardization activities related to IMEx are highlighted and the white paper is concluded with an outlook related to future developments

Multi–Scale Synthesized View Assessment Based on Morphological Pyramids

International audienc

DIBR-synthesized image quality assessment based on morphological multi-scale approach

International audienc

Experiences and procedures on making technical documentation for the objects of historical and cultural heritage

This paper evaluates advantages of application of digital photogrammetry for the purposes of production of technical documentation for the objects under protection, comparing it with the classical photogrammetric procedures. Based on gained experiences, paper reviews procedures for the completely digital production of technical documentation. Process of making technical documentation is divided in two logical stages. First stage comprises of photogrammetric recording, necessary field measurements and production of archive documentation. Archive documentation is in completely digital form and it includes: geometrically rectified photogrammetric photos, data on control points, parameters of exterior orientation for all photos and digital orthophotos as a preliminary source of geometric information. Second stage involves the production of detailed documentation with data describing object geometry such as: floor plans, facades, sections, etc, by using suitable CAD tools. Considering that this constitutes the most complicated and the most expensive part of making technical documentation, this stage is done when needed. Proposed method will be illustrated in paper by using experiences gained on projects of making technical documentations for objects of historical and cultural heritage for the towns of Kragujevac (Serbia and Montenegro) and Banja Luka (Republic of Srpska)

Experiences and procedures on making technical documentation for the objects of historical and cultural heritage

This paper evaluates advantages of application of digital photogrammetry for the purposes of production of technical documentation for the objects under protection, comparing it with the classical photogrammetric procedures. Based on gained experiences, paper reviews procedures for the completely digital production of technical documentation. Process of making technical documentation is divided in two logical stages. First stage comprises of photogrammetric recording, necessary field measurements and production of archive documentation. Archive documentation is in completely digital form and it includes: geometrically rectified photogrammetric photos, data on control points, parameters of exterior orientation for all photos and digital orthophotos as a preliminary source of geometric information. Second stage involves the production of detailed documentation with data describing object geometry such as: floor plans, facades, sections, etc, by using suitable CAD tools. Considering that this constitutes the most complicated and the most expensive part of making technical documentation, this stage is done when needed. Proposed method will be illustrated in paper by using experiences gained on projects of making technical documentations for objects of historical and cultural heritage for the towns of Kragujevac (Serbia and Montenegro) and Banja Luka (Republic of Srpska)

Morphological Difference of Closings Operator for No-Reference Quality Evaluation of DIBR-Synthesized Images

International audienceImages synthesized using Depth-Image-Based Rendering (DIBR) techniques are characterized by complex structural distortion. Multi-resolution multi-scale sparse image representation generated using morphological Difference of Closings operator (DoC) is used to efficiently capture structure-related distortion of synthesized images in the noreference DoC-GRNN image quality assessment model. Nonlinear morphological Difference of Closings operator (DoC) with an array of line-shaped structuring elements of increasing length is used to extract perceptually important details of object structure at different scales and resolutions. The sparsity of DoC band is calculated as scalar feature. The extracted features are mapped to the quality score by general regression neural network (GRNN). We have explored the influence of the direction of an array of line-shaped structuring elements on the model's performances. The DoC-GRNN model shows high agreement with perceptual quality scores, comparable to the state-of-the-art metrics, when evaluated on the stereoscopic DIBR-synthesized images of MCL-3D dataset