Найти книгу: "Clustering Methodology for Symbolic Data"

The book is a collection of papers presented at the conference «Russia and Norway: Physical and Symbolic Borders» held in St Petersburg in April 2005 in connection with the opening of the exhibition «Norway – Russia. Neighbours through the ages». In the book different aspects of the history of the Norwegian-Russian border are covered by historians from Moscow, St Petersburg, Arkhangelsk, Copenhagen, Cambridge, Bergen and Tromso. The papers are diverse and refer to different chronological periods. One group of articles deals with problems connected with the medieval border treaties between Norway and Novgorodian Russia, others with the diplomatic history of the border convention of 1826, as well as its effect on ethnic minorities living in the border area. One author addresses the present-day delimitation controversy between Norway and Russia in the Barents Sea. Other articles deal with symbolic borders, for example, barriers in translating Russian literature into Norwegian, and borders between the two cultures, experienced by the Russian emigrants in Norway after the Russian Revolution. And finally, there are articles without explicit references to the concept of borders, where the authors investigate in more general terms different aspects of Norwegian-Russian relations.

Uncover hidden fraud and red flags using efficient data analytics Fraud Data Analytics Methodology addresses the need for clear, reliable fraud detection with a solid framework for a robust data analytic plan. By combining fraud risk assessment and fraud data analytics, you'll be able to better identify and respond to the risk of fraud in your audits. Proven techniques help you identify signs of fraud hidden deep within company databases, and strategic guidance demonstrates how to build data interrogation search routines into your fraud risk assessment to locate red flags and fraudulent transactions. These methodologies require no advanced software skills, and are easily implemented and integrated into any existing audit program. Professional standards now require all audits to include data analytics, and this informative guide shows you how to leverage this critical tool for recognizing fraud in today's core business systems. Fraud cannot be detected through audit unless the sample contains a fraudulent transaction. This book explores methodologies that allow you to locate transactions that should undergo audit testing. Locate hidden signs of fraud Build a holistic fraud data analytic plan Identify red flags that lead to fraudulent transactions Build efficient data interrogation into your audit plan Incorporating data analytics into your audit program is not about reinventing the wheel. A good auditor must make use of every tool available, and recent advances in analytics have made it accessible to everyone, at any level of IT proficiency. When the old methods are no longer sufficient, new tools are often the boost that brings exceptional results. Fraud Data Analytics Methodology gets you up to speed, with a brand new tool box for fraud detection.

An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with Levy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distribution in financial modeling and the best methodologies for employing it. The book's framework includes the basics of probability distributions and explains the alpha-stable distribution and the tempered stable distribution. The authors also explore discrete time option pricing models, beginning with the classical normal model with volatility clustering to more recent models that consider both volatility clustering and heavy tails. Reviews the basics of probability distributions Analyzes a continuous time option pricing model (the so-called exponential Levy model) Defines a discrete time model with volatility clustering and how to price options using Monte Carlo methods Studies two multivariate settings that are suitable to explain joint extreme events Financial Models with Levy Processes and Volatility Clustering is a thorough guide to classical probability distribution methods and brand new methodologies for financial modeling.

Written for enterprise risk management (ERM) practitioners who recognize ERM?s value to their organization, Enterprise Risk Management: A Methodology for Achieving Strategic Objectives thoroughly examines operational risk management and allows you to leverage ERM methodology in your organization by putting author and ERM authority Gregory Monahan's Strategic Objectives At Risk (SOAR) methodology to work. A must-read for anyone interested in risk management as a strategic, value-adding tool, this no-nonsense book shows you how to use ERM and SOAR to empower your company to go from stuck to competitive.