{"product_id":"data-analysis-and-applications-4-financial-data-analysis-and-methods-hardback-9781786306241","title":"Data Analysis and Applications 4; Financial Data Analysis and Methods (Hardback) 9781786306241","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eData Analysis and Applications 4\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eFinancial Data Analysis and Methods\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eAndreas Makrides (Edited by), A Makrides (Author), Alex Karagrigoriou (Edited by), Christos H. Skiadas (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781786306241, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 20 March 2020\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e320 pages\u003cbr\u003e23.9 x 16.3 x 2.3 cm, 0.59 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eData analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages.   This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into three parts: Financial Data Analysis and Methods, Statistics and Stochastic Data Analysis and Methods, and Demographic Methods and Data Analysis- providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1 Financial Data Analysis and Methods 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Forecasting Methods in Extreme Scenarios and Advanced Data Analytics for Improved Risk Estimation 3\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGeorge-Jason SIOURIS, Despoina SKILOGIANNI and Alex Karagrigoriou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 3\u003c\/p\u003e \u003cp\u003e1.2 The low price effect and correction 6\u003c\/p\u003e \u003cp\u003e1.2.1 Percentage value at risk and low price correction 9\u003c\/p\u003e \u003cp\u003e1.2.2 Expected Percentage Shortfall (EPS) and Low Price Correction 12\u003c\/p\u003e \u003cp\u003e1.2.3 Adjusted Evaluation Measures 14\u003c\/p\u003e \u003cp\u003e1.2.4 Backtesting and Method’s Advantages 15\u003c\/p\u003e \u003cp\u003e1.3 Application 17\u003c\/p\u003e \u003cp\u003e1.3.1 The Alpha warrant 17\u003c\/p\u003e \u003cp\u003e1.3.2 The ARTX stock 24\u003c\/p\u003e \u003cp\u003e1.4 Conclusion 28\u003c\/p\u003e \u003cp\u003e1.5 Acknowledgements 30\u003c\/p\u003e \u003cp\u003e1.6 References 30\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Credit Portfolio Risk Evaluation with Non-Gaussian One-factor Merton Models and its Application to CDO Pricing 33\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eTakuya FUJII and Takayuki SHIOHAMA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 33\u003c\/p\u003e \u003cp\u003e2.2 Model and assumptions 36\u003c\/p\u003e \u003cp\u003e2.3 Asymptotic evaluation of credit risk measures 40\u003c\/p\u003e \u003cp\u003e2.4 Data analysis 44\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 48\u003c\/p\u003e \u003cp\u003e2.6 Acknowledgements 48\u003c\/p\u003e \u003cp\u003e2.7 References 48\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Towards an Improved Credit Scoring System with Alternative Data: the Greek Case 51\u003cbr\u003e\u003c\/b\u003e\u003ci\u003ePanagiota GIANNOULI and Christos E. KOUNTZAKIS\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 51\u003c\/p\u003e \u003cp\u003e3.2 Literature review: stages of credit scoring 52\u003c\/p\u003e \u003cp\u003e3.3 Performance definition 53\u003c\/p\u003e \u003cp\u003e3.4 Data description 54\u003c\/p\u003e \u003cp\u003e3.4.1 Alternative data in credit scoring 54\u003c\/p\u003e \u003cp\u003e3.4.2 Credit scoring data set 54\u003c\/p\u003e \u003cp\u003e3.4.3 Data pre-processing 55\u003c\/p\u003e \u003cp\u003e3.5 Models’ comparison 56\u003c\/p\u003e \u003cp\u003e3.6 Out-of-time and out-of-sample validation 58\u003c\/p\u003e \u003cp\u003e3.7 Conclusion 59\u003c\/p\u003e \u003cp\u003e3.8 References 59\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 EM Algorithm for Estimating the Parameters of the Multivariate Stable Distribution 61\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eLeonidas SAKALAUSKAS and Ingrida VAICIULYTE\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 61\u003c\/p\u003e \u003cp\u003e4.2 Estimators of maximum likelihood approach 63\u003c\/p\u003e \u003cp\u003e4.3 Quadrature formulas 67\u003c\/p\u003e \u003cp\u003e4.4 Computer modeling 68\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 71\u003c\/p\u003e \u003cp\u003e4.6 References 71\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2. Statistics and Stochastic Data Analysis and Methods 75\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Methods for Assessing Critical States of Complex Systems 77\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eValery ANTONOV\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 77\u003c\/p\u003e \u003cp\u003e5.2 Heart rate variability 78\u003c\/p\u003e \u003cp\u003e5.3 Time-series processing methods 80\u003c\/p\u003e \u003cp\u003e5.4 Conclusion 87\u003c\/p\u003e \u003cp\u003e5.5 References 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Resampling Procedures for a More Reliable Extremal Index Estimation 89\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDora PRATA GOMES and M. Manuela NEVES\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction and motivation 89\u003c\/p\u003e \u003cp\u003e6.2 Properties and difficulties of classical estimators 92\u003c\/p\u003e \u003cp\u003e6.3 Resampling procedures in extremal index estimation 93\u003c\/p\u003e \u003cp\u003e6.3.1 A simulation study of mean values and mean square error patterns of the estimators 94\u003c\/p\u003e \u003cp\u003e6.3.2 A choice of δ and k: a heuristic sample path stability criterion 96\u003c\/p\u003e \u003cp\u003e6.4 Some overall comments 98\u003c\/p\u003e \u003cp\u003e6.5 Acknowledgements 99\u003c\/p\u003e \u003cp\u003e6.6 References 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Generalizations of Poisson Process in the Modeling of Random Processes Related to Road Accidents 103\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFranciszek GRABSKI\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 103\u003c\/p\u003e \u003cp\u003e7.2 Non-homogeneous Poisson process 104\u003c\/p\u003e \u003cp\u003e7.3 Model of the road accident number in Poland 106\u003c\/p\u003e \u003cp\u003e7.3.1 Estimation of model parameters 107\u003c\/p\u003e \u003cp\u003e7.3.2 Anticipation of the accident number 108\u003c\/p\u003e \u003cp\u003e7.4 Non-homogeneous compound Poisson process 109\u003c\/p\u003e \u003cp\u003e7.5 Data analysis 113\u003c\/p\u003e \u003cp\u003e7.6 Anticipation of the accident consequences 113\u003c\/p\u003e \u003cp\u003e7.7 Conclusion 116\u003c\/p\u003e \u003cp\u003e7.8 References 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Dependability and Performance Analysis for a Two Unit Multi-state System with Imperfect Switch 119\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eVasilis P. KOUTRAS, Sonia MALEFAKI and Agapios N. PLATIS\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 120\u003c\/p\u003e \u003cp\u003e8.2 Description of the system under maintenance and imperfect switch 122\u003c\/p\u003e \u003cp\u003e8.3 Dependability and performance measures 124\u003c\/p\u003e \u003cp\u003e8.3.1 Transient phase 125\u003c\/p\u003e \u003cp\u003e8.3.2 Asymptotic analysis 128\u003c\/p\u003e \u003cp\u003e8.4 Optimal maintenance policy 129\u003c\/p\u003e \u003cp\u003e8.4.1 Optimal maintenance policy for maximizing system availability 130\u003c\/p\u003e \u003cp\u003e8.4.2 Optimal maintenance policy for minimizing total expected operational cost 130\u003c\/p\u003e \u003cp\u003e8.4.3 Optimal maintenance policy for multi-objective optimization problems 131\u003c\/p\u003e \u003cp\u003e8.5 Numerical results 132\u003c\/p\u003e \u003cp\u003e8.5.1 Transient and asymptotic dependability and performance 132\u003c\/p\u003e \u003cp\u003e8.5.2 Optimal asymptotic maintenance policies implemented in the transient phase 143\u003c\/p\u003e \u003cp\u003e8.6 Conclusion and future work 147\u003c\/p\u003e \u003cp\u003e8.7 Appendix 148\u003c\/p\u003e \u003cp\u003e8.8 References 152\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Models for Time Series Whose Trend Has Local Maximum and Minimum Values 155\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eNorio WATANABE\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 155\u003c\/p\u003e \u003cp\u003e9.2 Models 156\u003c\/p\u003e \u003cp\u003e9.2.1 Model 1 156\u003c\/p\u003e \u003cp\u003e9.2.2 Model 2 158\u003c\/p\u003e \u003cp\u003e9.3 Simulation 159\u003c\/p\u003e \u003cp\u003e9.4 Estimation of the piecewise linear trend 161\u003c\/p\u003e \u003cp\u003e9.5 Conclusion 164\u003c\/p\u003e \u003cp\u003e9.6 References 165\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 How to Model the Covariance Structure in a Spatial Framework: Variogram or Correlation Function? 167\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGiovanni PISTONE and Grazia VICARIO\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 167\u003c\/p\u003e \u003cp\u003e10.2 Universal Krige setup 168\u003c\/p\u003e \u003cp\u003e10.3 The variogram matrix 170\u003c\/p\u003e \u003cp\u003e10.4 Inverse variogram matrix Γ −1 173\u003c\/p\u003e \u003cp\u003e10.5 Projecting on span (1) ⊥ 177\u003c\/p\u003e \u003cp\u003e10.6 Elliptope 179\u003c\/p\u003e \u003cp\u003e10.7 Conclusion 182\u003c\/p\u003e \u003cp\u003e10.8 Acknowledgements 182\u003c\/p\u003e \u003cp\u003e10.9 References 183\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Comparison of Stochastic Processes 185\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJesús Enrique GARCÍA, Ramin GHOLIZADEH and Verónica Andrea GONZÁLEZ-LÓPEZ\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 185\u003c\/p\u003e \u003cp\u003e11.2 Preliminaries 186\u003c\/p\u003e \u003cp\u003e11.3 Application to linguistic data 191\u003c\/p\u003e \u003cp\u003e11.4 Conclusion 195\u003c\/p\u003e \u003cp\u003e11.5 References 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3 Demographic Methods and Data Analysis 197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Conjoint Analysis of Gross Annual Salary Re-evaluation: Evidence from Lombardy ELECTUS Data 199\u003cbr\u003e\u003c\/b\u003e\u003ci\u003ePaolo MARIANI, Andrea MARLETTA and Mariangela ZENGA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 199\u003c\/p\u003e \u003cp\u003e12.2 Methodology 201\u003c\/p\u003e \u003cp\u003e12.2.1 Coefficient of economic valuation 202\u003c\/p\u003e \u003cp\u003e12.3 Application and results 204\u003c\/p\u003e \u003cp\u003e12.4 Conclusion 211\u003c\/p\u003e \u003cp\u003e12.5 References 212\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Methodology for an Optimum Health Expenditure Allocation 215\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGeorge MATALLIOTAKIS\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 215\u003c\/p\u003e \u003cp\u003e13.2 The Greek case 216\u003c\/p\u003e \u003cp\u003e13.3 The basic table for calculations 219\u003c\/p\u003e \u003cp\u003e13.4 The health expenditure in hospitals 221\u003c\/p\u003e \u003cp\u003e13.5 Conclusion 221\u003c\/p\u003e \u003cp\u003e13.6 References 222\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Probabilistic Models for Clinical Pathways: The Case of Chronic Patients 225\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eStergiani SPYROU, Anatoli KAZEKTSIDOU and Panagiotis BAMIDIS\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 225\u003c\/p\u003e \u003cp\u003e14.2 Models and clinical practice 227\u003c\/p\u003e \u003cp\u003e14.3 The Markov models in medical diagnoses 228\u003c\/p\u003e \u003cp\u003e14.3.1 The case of chronic patients 229\u003c\/p\u003e \u003cp\u003e14.3.2 Results 231\u003c\/p\u003e \u003cp\u003e14.4 Conclusion 232\u003c\/p\u003e \u003cp\u003e14.5 References 233\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 On Clustering Techniques for Multivariate Demographic Health Data 235\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAchilleas ANASTASIOU, George MAVRIDOGLOU, Petros HATZOPOULOS and Alex KARAGRIGORIOU\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 235\u003c\/p\u003e \u003cp\u003e15.2 Literature review 236\u003c\/p\u003e \u003cp\u003e15.3 Classification characteristics 237\u003c\/p\u003e \u003cp\u003e15.3.1 Distance measures 238\u003c\/p\u003e \u003cp\u003e15.3.2 Clustering methods 239\u003c\/p\u003e \u003cp\u003e15.4 Data analysis 240\u003c\/p\u003e \u003cp\u003e15.4.1 Data 240\u003c\/p\u003e \u003cp\u003e15.4.2 The analysis 242\u003c\/p\u003e \u003cp\u003e15.5 Conclusion 249\u003c\/p\u003e \u003cp\u003e15.6 References 249\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16 Tobacco-related Mortality in Greece: The Effect of Malignant Neoplasms, Circulatory and Respiratory Diseases, 1994–2016 251\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKonstantinos N. ZAFEIRIS\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 251\u003c\/p\u003e \u003cp\u003e16.1.1 Smoking-related diseases 253\u003c\/p\u003e \u003cp\u003e16.2 Data and methods 254\u003c\/p\u003e \u003cp\u003e16.3 Results 256\u003c\/p\u003e \u003cp\u003e16.3.1 Life expectancy at birth 256\u003c\/p\u003e \u003cp\u003e16.3.2 Effects of the diseases of the circulatory system on longevity 258\u003c\/p\u003e \u003cp\u003e16.3.3 Effects of smoking-related neoplasms on longevity 261\u003c\/p\u003e \u003cp\u003e16.3.4 Effects of respiratory diseases on longevity 265\u003c\/p\u003e \u003cp\u003e16.4 Discussion and conclusion 268\u003c\/p\u003e \u003cp\u003e16.5 References 272\u003c\/p\u003e \u003cp\u003eList of Authors 277\u003c\/p\u003e \u003cp\u003eIndex 281\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Mathematics [\u003ca title=\"See our other books on Mathematics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Mathematics%20%5BPB%5D%22\"\u003ePB\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-ISTE","offers":[{"title":"Brand New","offer_id":52446750146840,"sku":"9781786306241","price":100.57,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781786306241.jpg?v=1785112770","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/data-analysis-and-applications-4-financial-data-analysis-and-methods-hardback-9781786306241","provider":"Freshly Printed Books","version":"1.0","type":"link"}