Advanced Data Analysis, Business Analytics and Intelligence

Transcription

1 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence April 13-14, 2013, Ahmedabad, India ABSTRACT BOOKLET

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3 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence April 13-14, 2013 Indian Institute of Management Ahmedabad, India

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5 ICADABAI-2013 The 3 rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence (ICADABAI-2013) is being organized with the purpose of exploring the frontiers of theory and applications of Data Analysis, Business Analytics and Business Intelligence in the context of rapidly changing economic and business environment. The conference brings together leading academic researchers and practitioners from universities, research institutions and industries from India and abroad to a common platform with a view to facilitate the sharing of research based knowledge and cutting edge applications. Dr Vikram Sarabhai and a few other public spirited industrialists founded the Indian Institute of Management, Ahmedabad (IIMA) in 1961 as an autonomous body with the active collaboration of the Government of India, Government of Gujarat, and industry. The Institute had initial collaboration with Harvard Business School which greatly influenced the Institute s approach to education. Gradually it emerged as a confluence of the best of eastern and western management approaches having strong ties with both industry and government. The 1 st IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence (ICADABAI- 2009), was held on 6-7 June 2009 and was attended by about 120 participants from academia and industry. A total of 116 research papers and case studies were presented in this conference. The second conference in this series ICADABAI-2011 was held at IIM, Ahmedabad on 8-9 January, 2011 and was attended by about 140 participants from academia and industry. The two day conference had three key-note speeches delivered by eminent academicians and practitioners and two panel discussions on special topics aligned to the theme of the conference. One panel discussion addressed the topic of Business Intelligence while the other addressed the issues relating to Data Quality. This conference saw academicians and practitioners present a total of 100 research papers and case studies. The present conference, which is the third in this series, is being attended by more than 140 participants from academia and industry. It would see six key-note speeches by eminent academicians and business leaders and presentation of about 110 research papers and case studies. As a Knowledge management initiative both the ICADABAI-2009 and ICADABAI-2011 were video recorded. The conference documentations (in the form of interactive DVDs) of these two conferences are available for reference of academicians and practitioners. The ICADABAI-2013 conference would also be video recorded which will later be turned into interactive DVDs. The conference participants can acquire a copy of the documentation by contacting the Conference Convener. Conference Convener: Conference Team: Prof. Arnab Kumar Laha, IIM Ahmedabad Ms. Pravida Raja, IIM Ahmedabad Prof. Mahesh K. C., SLIMS-Ahmedabad

6 Members of International Programme Committee: Neeraj Arora Wisconsin School of Business, Madison, USA Sankarshan Basu Indian Institute of Management, Bangalore Sudip Bhattacharjee University of Connecticut, USA Anand Bodapati University of California, Los Angeles, USA Smarajit Bose Indian Statistical Institute Anil Kumar Ghosh Indian Statistical Institute Mrinal K Ghosh Indian Institute of Science Sujit K Ghosh North Carolina State University, USA Ravindra Khattree Oakland University, USA Ranjan Maitra Iowa State University, USA Chiranjit Mukhopadhyay Indian Institute of Science Ganapati Panda Indian Institute of Technology, Bhubaneswar Nityananda Sarkar Indian Statistical Institute Ashis SenGupta Indian Statistical Institute Vishal Singh New York University, USA N. Balakrishna Cochin Institute of Science and Technology, India Ashok Banerjee Indian Institute of Management, Calcutta Sumanta Basu Indian Institute of Management, Calcutta Atanu Biswas Indian Statistical Institute Sharad W Borle Rice University, USA Samarjit Das Indian Statistical Institute Aurobindo Ghosh Singapore Management University Pulak Ghosh Indian Institute of Management, Bangalore Sandeep Juneja Tata Institute of Fundamental Research, India Debasis Kundu Indian Institute of Technology, Kanpur Neeraj Misra Indian Institute of Technology, Kanpur Harikesh Nair Stanford University, USA Indrajit Ray University of Birmingham, UK Subrata Sarkar Indira Gandhi Institute of Development Research, India Janat Shah Indian Institute of Management, Udaipur Anshuman Tripathy Indian Institute of Management, Bangalore Session Organizers: Atanu Biswas Indian Statistical Institute Anil Kumar Ghosh Indian Statistical Institute Debdutta Pal Indian Institute of Management, Indore Ranjan Maitra Iowa State University, USA Kousik Guhathakurta Indian Institute of Management, Kozhikode Nityananada Sarkar Indian Statistical Institute 04 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

7 Referees: Sharad W Borle Rice U. Vineet Virmani IIM-Ahmedabad Prahalad Venkateshan IIM-Ahmedabad Sachin Jayaswal IIM-Ahmedabad V.V.Rao IIM-Ahmedabad Kavitha Ranganathan IIM-Ahmedabad Anand Kumar Jaiswal IIM-Ahmedabad Dhiman Bhadra IIM-Ahmedabad Shobhesh Agrawal IIM-Ahmedabad Subrata Sarkar IGIDR Brajesh Kumar JGBS-NCR Biju Varkkey IIM-Ahmedabad Debdatta Pal IIM-Indore Anshuman Tripathy IIM-Bangalore Joshy Jacob IIM-Ahmedabad Ramani K V IIM-Ahmedabad Saral Mukherjee IIM-Ahmedabad Abhishek IIM-Ahmedabad Rudra P Pradhan IIT-Kharagpur Sanjay Verma IIM-Ahmedabad Viswanath Pingali IIM-Ahmedabad Himadri Roy Chaudhuri IMI-Kolkata Neharika Vohra IIM-Ahmedabad Sankarshan Basu IIM-Bangalore Mahesh K.C SLIMS-Ahmedabad Debjit Roy IIM-Ahmedabad Ajay Pandey IIM-Ahmedabad Dheeraj Sharma IIM-Ahmedabad Kartik D IIM-Ahmedabad Sumanta Basu IIM-Calcutta Arnab K Laha IIM-Ahmedabad B.H.Jajoo IIM-Ahmedabad Sanjeev Tripathi IIM-Ahmedabad Samarjit Das ISI-Kolkata Ramanathan S IIM-Ahmedabad Vijaya Sherry Chand IIM-Ahmedabad Nityananda Sarkar ISI-Kolkata Indrajit Ray U. Birmingham Arvind Sahay IIM-Ahmedabad Ganapati Panda IIT-Bhubhneswar Chetan Soman IIM-Ahmedabad Preeta Vyas AIIM-Ahmedabad N. Venkiteswaran IIM-Ahmedabad Arijit Laha Infosys Jayant R Varma IIM-Ahmedabad Apratim Guha IIM-Ahmedabad 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 05

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9 Contents KN-1 Big Data : The challenges to official statistics...13 TCA Anant KN-2 KN-3 Online Early Detection of Change for High Volatility Multivariate Portfolios and Updating VaR...13 Ashis SenGupta Art, Science and the Secret Sauce - A recipe for building world class analytics capability...15 Srikanth Velamakanni S-028 Role of Inclusive Financial Services in Empowering the MSME sector for a Green Economy: An Indian Perspective...15 Raka Banerji, Sudipti Banerjea S-043 Commodity Indices: Defining their Role in Indian Market-Understanding Dynamic Conditional Correlation with Stock Index in Multi-resolution Set-up...16 Rahul Deora, Brajesh Kumar S-018 Devising the Usp in Sporadic Markets - A Study Done on Wedding Planners in Tamilnadu...16 P.Baba Gnanakumar S-139 Applications of Bayesian Networks in Business Intelligence...17 Heena Timani S-181 Improvements to be introduced in the algorithms of CVRP and VRPB when solved over instances involving asymmetric distances and heterogeneous fleet Kaviti Keshav Kumar, Sunil Agrawal S-081 Determinants of Lapsation of Policies: An Investigation in Indian Insurance Sector...18 Sunita Mall, Seshadev Sahoo S-083 On Testing Exponentiality against NBAFR Alternatives...18 Aditi Pal, Murari Mitra, M.Z. Anis S-117 A Cognitive Business Intelligence System for Dynamic Portfolio Design...19 Shyam A V, Swain A K S-150 Signals of Initial Public Offering (IPO) Underpricing: Indian IPO Market Smitha V Shenoy, K Srinivasan S-112 Rainfall Insurance in India...20 Aditya Bansal, Girish Singhal, Sudhir Dutt S-075 Predictive Modeling of Non-compliance Detection...21 Venugopal Jarugumalli, Suresh Venkata, Sathyanarayana Ramani, KV Nathan S-118 Design of Marketing Promotions of Low-Ticket sized Consumer Goods and Services using Probabilistic Simulation Modelling...21 Sachin Sapte S-099 Business simulations: Building uncertainty into learning and strategy...22 Debashish Banerjee S-177 Using Analytics to pitch the right product to customers at inbound channels...22 Subhankar Mukherjee S-175 Modelling of Indian Stock Prices using Nonhomogeneous Poisson Processes with Time Trends...24 Rupal Shah, K. Muralidharan S-056 A Non Markovian Time Dependent Point Process Approach To Estimate Cumulative Loss Due To Defaults...24 KSS Iyer, Abhijit Chirputkar 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 07

10 S-113 Time Series Analysis Using Wavelet Filters Improved Instance Based Learning For Multi-Step Predictions...25 Pushpalatha M P, Nalini N S-141 Forecasting inflation expectation using financial market data...25 Shreyes Upadhyay, Madhav Kumar S-035 On Nonparametric Phase-II Joint Monitoring of Location and Scale based on a Single Chart...26 Shovan Chowdhury, Amitava Mukherjee, Subha Chakraborti S-084 Economic Measurement and Empirical Analysis of Health Inequality in Odisha-Application of Econometric & Statistical Methods...26 Usha Kamilla, Divya Gupta S-180 Modeling and Simulation of Glaucoma Risk Appraisal (GRA) Based on Clinical Data and Automated Early Nerve Fiber Layer Defects Detection using Feature Extraction in Retinal Colored Stereo Fundus Images...27 Jyotika Pruthi, Saurabh Mukherjee S-024 Alternative Goodness of Fit for Continuous Dependent Variable...27 Sandeep Das S-069 Hierarchical Models in Marketing Mix and Price Promotion Analysis...28 Zaki Ashraf, Lakshmi Prasad V S-077 Retailer Pricing Impact of Cross Channel Price and Store on Sales Lakshmi Prasad V, Priya Viswanathan S-147 Advance Analytics Shaping The Marketing Strategy of Insurance Organizations - An Approach...29 P. H. A. Desik, Ravi Babu, Sureshkumar Dubagunta, Samarendra B S-071 Scientific Business Forecasting: Case of Vehicle Demand Forecasting in Indian Market...30 Nilmadhab Mandal S-202 Hellinger Type Distance using Probability Generating Functions in Parameter Estimation for MultivariateDiscrete Distributions...30 C. M. Ng, S. H. Ong, H. M. Srivastava S-193 Statistical Analysis for the Discrete Charlier Series Distribution...31 Tan ZM, Chua KC, Ong SH S-167 Zero-inflated integer-valued time series processes...31 Raju Maiti, Atanu Biswas, Apratim Guha, Seng Huat Ong S-096 SB-robustness of Performance Measures of Control Chart...31 Arnab Kumar Laha, Pravida Raja A.C S-199 Purchase Intention of Extended Warranty - An Integrated Model...32 Jithesh Kumar K. S-197 A Study on Coordination Mechanism for Return Policy Contracts with Warranty...32 Shirsendu Nandi S-203 Patterns of PED Test Sanctions in Professional Sports Baseline and Implications for Research...32 Deepak Dhayanithy S-195 Sectoral Choice of Credit in Rural India...33 Debdatta Pal, Arnab K. Laha S-046 Application of Data Mining techniques for energy loss Estimation with partial Data...33 Atul Pratap Singh S-068 A Combined Structured and Unstructured Data Mining Approach to Identify the Opportunity in SMB Unified Communication Space...34 Aswinraj Govindaraj, Paromita Sen, Karen Zhang, Michael Glander, Daryl Berry, Jacob Chi 08 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

11 S-145 Improving Employee s Learning Performance by Prediction using Decision Tree Algorithm...34 Vandana Sharma, Solomon Manuelraj S-130 Optimizing Agency Efficiency for Aadhaar enrolments using Data Analytics...35 K Vinay Kumar S-033 Study on Effectiveness of Mobile Telephone Services in Assam and the North East...35 Niranjan Agarwal, K.M.Date S-072 VIRTUAL ADDICTION-a terrific Mania...36 Sangeeta Trott S 187 Modeling Sales of Automobiles With Customer Engagement in Facebook...37 Tuhin Chattopadhyay S-019 Identifying the factors influencing purchasing decision of consumer of a new product-a study in Consumer Psychology...37 Madhuchhanda Karmakar S-013 Key Determinants of Mortgage Default: A Cross Sectional Analysis...38 Sanjay Kr. Mishra, Arti Devi S-047 Impact of Operating Efficiency on Valuation of Firms...39 Dyal Bhatnagar, Pritpal Singh Bhullar S-085 Value Implication of Analysts Recommendations: Empirical Evidence from Indian IPO Market...39 Seshadev Sahoo S-189 Change point detection in Gamma distributions with economic applications...40 K.Sanath S-041 Data Quality and Health Management Tool...40 Anuja A Kokrady, Anup Merkap S-093 Dynamic Insurance Pricing Analytics A GLM Perspective...40 P.H.A. Desik, Suresh Kumar Dubagunta, Bhishma Gajavelli, Vivek Rathi S-098 Comparison of linear and logistic regression for segmentation...41 Debashish Banerjee, Kranthi Ram Nekkalapu S-123 Data Mining: Discover Hidden Value...42 Sachchidanand Singh S-133 E-Commerce verses M-Commerce: The future of Online Marketing, A comparative study...42 Madhusmita Choudhury, I.G.Srikanth S-190 Ra.One Success or Failure?...43 Indu Mehta, Richard Suman Halder S-116 Data Envelopment Analysis Approach for Analyzing Human Competency and Enhancing Service Quality...43 Reshmi Manna, Ravi Shankar S-040 Greedy Search and Genetic Algorithm - Combined approach in 3PL Optimization...44 Vivekanandhan.P, Paramasivam.A, Anand.S, Vasanthavanan.T, Gopinath.B S-191 Prioritization of Barriers Faced By Independent Power Producers in Wind Power Industry A Multi Criteria Approach...45 Mallikarjune Gowda M.C., Bharath Repaka, Puttabore Gowda, Rajakumar D G, Chandrashekar R S-020 Analytical Network Process (ANP) Based Modeling For Analysing The Risks In Traditional, Agile And Lean Supply Chain Mahesh Chand, Tilak Raj, Ravi Shankar S-030 Mobility Mining Techniques for Big Data Analysis in Supply Chain Traffic...46 Sajimon Abraham, Siby Zacharias, P. Sojan Lal S-031 Multi-Echelon Efficiency Decomposition of Serial Supply Chains...46 Mithun J. Sharma, Yu, Song Jin 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 09

12 S-110 Impact of World IT Stock Indices on Indian IT Stock Indices- A Linear Regression Modelling Approach...47 Dharmender Jhamb S-160 An Empirical Analysis of Governance Practices of Indian Firms...47 Arunima Haldar, S.V.D. Nageswara Rao S-170 Macroeconomic Factors and FDI determining impact on India s growth and development: a Cointegration Analysis...48 Preeti Flora, Gaurav Agrawal, Manoj Kumar Dash S-183 Interpreting Financial Datasets by Time Series Data mining Techniques: A Search for Similarities and Features...48 Anushree Goutam Ringne, Durga Toshniwal S-036 Board Independence and Firm Performance in India...48 Pranati Mohapatra S-149 Structural Equation Modeling: A study on Cyber Banking in India...49 Divya Gupta, Usha Kamilla S-188 Combining Expert Opinions for Probabilistic Risk Analysis...50 Sriram Bharadwaj R, Arnab K Laha S-025 An Experiment on Role of Anchoring Bias in Financial and Economic Decision Making. 50 Gautam Bandyopadhyay, Arindam Banerjee, Prithiraj Banerjee, Parijat Upadhyay S-205 Donor profiling and donation enhancement strategy: A project completed for Save the Children...51 Uma Venkataraman S-206 Improving court case tracking efficiency for Delhi High Court...51 Uma Venkataraman S-207 Data Quality Improvement for Automated Data Flow Project implementation of Allahabad Bank...52 Uma Venkataraman KN-4 Analytics Journey to ROI...52 Amit Khanna KN-5 Big Data and Marketing Analytics...53 Arvind Sahay KN-6 Big Data Analytics: Transforming big data into big value...54 Sudipta K. Sen S-200 Discrete-Valued Time Series Using Categorical ARMA Models...54 Peter X.-K. Song, R. Keith Freeland, Atanu Biswas, Shulin Zhang S-194 Optimal sample proportion for a two-treatment clinical trial in presence of surrogate endpoints...55 Buddhananda Banerjee, Atanu Biswas, Saumen Mandal S-201 Vital roles of generating functions in Lie-theoretic approach...55 Manik C Mukherjee S-196 Bootstrapping for Significance in Clustering Ranjan Maitra, Soumen Lahiri, Volodymyr Melnykov S-049 On the use of K-means algorithm with Mahalanobis distances...56 Igor Melnykov, Volodymyr Melnykov S-198 A Method of Combing Mixture Components for Colour Estimation Problems...56 Subhra Sankar Dhar, Kajsa Mollersen, Fred Godtliebsen S-159 Robustness of tests for the concentration parameter of circular normal distribution: A breakdown approach...57 Arnab Kumar Laha, Mahesh K.C S-059 Social Media Analytics...57 Suresh Chakravarthy, Sandeep Kumar Sharma, Sandeep Kumar Sethi, Latesh Joshi, Jitesh Dhupar, Pavan Kumar Vedam 10 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

13 S-140 Developing Advertising Response Models through two Level Regression...58 Priya Viswanathan, Lakshmi Prasad V S-143 Method for Improving Customer Insights Using Unstructured Data in Retail...59 Suresh Veluchamy, Gopal Govindasamy S-097 Logistic Regression or Neural Network for Risk Assessment...59 Vandita Bansal, Subarna Roy S-109 Empirical Investigation of Indian Currency Dynamics: Pricing, Volatility and Forecasting...59 Sanjay K Singh S-135 A Simplified Algorithm of X-11 Census Method II Seasonal Adjustment Program and An Alternative software of Proc X11/X12 in SAS for Monthly and Quarterly Data..60 Ariful Islam Mondal, Saran Ishika Maiti S-142 Performance Evaluation of the Listed Companies in Indian IT Industry based on Factor Analysis...60 Manisha Sharma, Prashant Gupta S-154 Analysis of the Effect of Service Broker Policy on the Costing of Cloud Computing Based Services...61 Vikas Kumar, Jitendra Singh S-086 Risk Analysis of FDI in Multi-Brand Retail Sector in India Piyush Nawathe, Sumit Kumar S-103 Attribution Modeling for online Companies: A study of different approaches...62 Zubin Joy Saini, Pratyush Kumar, Vishal Aggarwal, Ramneesh Singla S-162 Assessing Response Towards Internet Advertisements Using RCE Scale (With Special Reference To Banking Products And Services)...62 Deepak Jaroliya, Pragya Jaroliya S-073 Business Analytics and Business Intelligence: A boon or bane for Public Sector Enterprises...63 Shaheen, Mishra R K, Hamendra Kumar Dangi S-204 Quality in Management Education- Analytics and Rankings...64 Kalika Bansal, Arnab Kumar Laha S-027 A restricted r-k class estimator in the mixed regression model with non-spherical disturbances...64 Shalini Chandra, Nityananda Sarkar S-011 Finance-Social Development and Economic Growth: The Panel VAR Application...65 Rudra P. Pradhan, Bele Samadhan, Sasikanta Tripathy, Subhanish Dey S-063 Financial Development and Economic Growth in Emerging Asian Countries: A Panel Co integration Approach...65 Ved Pal Sheera, Ashwani Bishnoi S-088 Causal Relationship between the major worlds financial markets with particular attention on United States & European Union Using Cross Correlation Arima, Sas/Ets...66 Changani Jagdish, Amit Saraswat, Dinesh Thapak S-171 Comparing nonlinear dynamics of emerging and developed stock markets using Empirical Mode Decomposition...66 Kousik Guhathakurta, Soumyajit Panigrahi, Shana Vijay Gawande S-126 Does Investors Risk Appetite affect Value-at-Risk (VaR)? - A Study on Selected Indian Stocks...67 Piyali Dutta Chowdhury, Basabi Bhattacharya S-185 Simultaneous Modelling of Skewness and Sparse Time- Varying Jumps in Asset Return with Stochastic Volatility...67 Sujay K Mukhoti, Pulak Ghosh 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 11

14 S-029 Solving Sales Force Allocation problem using a Differential Evolution algorithm...68 Debayan Bose, Bindu Narayan S-070 Adapting to emerging visualization techniques for advanced data analytics...68 Yugandhar Chodagam, Panini Jannabhatla, Raghu Nemani, Anoop Nambiar S-125 Data Visualization: Techniques and Applications...69 Priyam Banerjee, Geetanjali Chakraborty, Abhimanyu Dasgupta S-080 Themes and Sentiment Classification Using Support Vector Machines...69 Subhamitra Chatterjee S-166 Building an ensemble of machine learners to predict the US Census mail return rates...70 Shashishekhar Godbole, Madhav Kumar, Shreyes Upadhyay S-067 VaR for a generalized IGARCH type non-stationary data using extreme value theory Arabin Kumar Dey, Shyam Sundar Soumitra Josyula S-066 Use of Forced Distribution System in Appraising Employee s Performance: Its Problem and Solution...70 Rachana Chattopadhyay, Anil Kumar Ghosh S-064 Some strategic aspects of supply chain configurations...71 Debapriya Sen S-065 Statistical simulation using Markov Chain Monte Carlo (MCMC) method and its adaptations G K Basak, Arunangshu Biswas S-153 Campaign Effectiveness and Design of Letter Campaign...73 Vineeta Nair, Milind Kokate, Siddhartha Roy, Girdhar Agarwal S-155 Propensity to Pay Model...73 Milind Kokate, Vineeta Nair Prashant Shinde, Agarwal G. G., Siddhartha Roy S-156 Time Series Analysis for Call Volume Forecasting in Contact Centre used for Manpower Planning and Scheduling...74 Prashant Anant Shinde, Siddhartha Roy S-078 Warranty Analytics...75 Geetanjali Chakraborty, Abhimanyu Dasgupta S-178 Enhancing the value of Predictive in-silico Models in Pre-Clinical Pharmaceutical Research Projects, by providing enriched information to researchers, using data analysis and visualization approaches...75 Sanjay Srivastava, Pierre Bonneau S-100 Advanced Market Mix Modeling Techniques: Evaluation and Comparison...76 Rajat Narang, Anika Mahajan, Rohan Aggarwal S-102 Deriving Optimal Bundle Use of Combination of Anchored MaxDiff and TURF...76 Supriya Suri, Jayant Rajpurohit, Manish Mittal S-106 Package Optimization Through Conjoint and TURF Analysis Rajat Narang, Raj Ganla, Kanika Malik, Anant Prakash S-208 Analyzing alternate storage strategies in mobile rack-based order-pick Systems...78 Shobhit Nigam, Debjit Roy S-114 Estimating the Likelihood of a Customer Purchase...78 Susan Mani 12 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

15 KN-1 Big Data : The challenges to official statistics TCA Anant Chief Statistician of India, and Secretary, Ministry of Statistics and Programme Implementation. Official Statistics in the last 60 years or so has evolved enormously. In the period before the second world war, the work of National Statistical Office may have been limited to giving a simple descriptive statistics of the nation based on relatively few sources of administrative records. The period after the war saw rapid growth in the range and scope of statistics put out by National Statistics Offices. These now include at one end measures of economic activity such as National Income to a range of measures of social development and human well-being on the other end. But these developments are overwhelmed by the sheer size and scope of information which has become available in the last 20 years through the growth of communication, internet and the widespread availability of computing resources. The rise of the internet has made available wide range of data. The data arrives from the fact that individuals, Governments and businesses are using the new technology to maintain records and manage their affairs. Thus it is in principle possible to observe a individual on where he goes from his mobile, what he buys from his credit card so on. On the one hand these raise the possibility of detailed descriptions of our society on the other the fears of loss of privacy. KN-2 Online Early Detection of Change for High Volatility Multivariate Portfolios and Updating VaR Ashis SenGupta Applied Statistics Unit, Indian Statistical Institute, Kolkata, INDIA Due to the initiation of the open market and the emergence of international players in our domestic financial horizon, prices of shares, stocks and even bonds have been experiencing high volatility previously not encountered. The term volatility refers to the variability of the financial returns, which may change from time to time. Financial data exhibit certain patterns, which are crucial to be identified in order to achieve satisfactory model specification. Of special concern among these patterns is the display of fat tails, which translates to high volatility or infinite variance. Asymmetry in the distribution is another such important feature. In the modelling and forecasting of returns from financial investments or for exchange rates, volatility plays a key role. It relates to risk management, derivative pricing and hedging, market making, market timing and portfolio selection. Its impact on the change in price is profound. An option trader would like to know the volatility that is expected over the future life of the contract. To hedge his contract, he may be interested in knowing how volatile the stock market is in future. More generally, an investor seeks an early determination of the possible change in his investment portfolio during the course of trading. Gaussian assumption has been the fundamental key underlying the theory of modelling the modern portfolios. Usually, efficient portfolios are given by the traditional mean-variance trade-off consideration, where the investor has to maximize the expected return (profit) for a given variance (volatility). In the portfolio analysis framework, the variance corresponds to the risk measure. Thus, for high volatility non-gaussian, specially fat-tailed distributions with infinite variance, alternate measures must be defined. 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 13

16 Given the high volatility exhibited in various price markets, the early detection of change-point in price distributions is of crucial current interest. We first present methods for detecting change retrospectively. Next, online optimal decision rules are presented for such early detection as using distributions in the exponential family. It is proven that a well designed multivariate portfolio consisting of suitably correlated profiles can achieve this detection at an earlier stage compared to univariate decision rules applied independently. This important feature is shown to persist even for low shift-to- noise ratio environments. It is then recalled that unfortunately high volatility distributions are seldom, if at all, members of the exponential family. Cauchy and double exponential distributions are some such popular models. We thus study the performance of our rules for sensitivity and robustness with respect to these distributions. The work of Mandelbrot has shown the appropriateness of more general families, which include these two distributions, for price distributions. However, in general these families do not possess any analytical closed form for their probability density functions. This leads to the complexity of inference involving the parameters of such distributions. In this era of emerging complex problems, multidisciplinary research in mathematical sciences has become indispensable. Directional statistics is one such scientific innovation as which on one hand is developed from the conglomeration of the inductive logic of statistics, objective rigor of mathematics and the skills of numerical analysis of computer science. On the other hand, it possesses the richness to handle the need for providing statistical inference to a wide and emerging arena of applied sciences. Directional data (DD) in general refer to multivariate observations on variables with possibly circular ones. Circular random variables are usually those which pertain to observations on directions, orientations, etc. Data on periodic occurrences can also be cast in the arena of DD. Analysis of such data sets differs markedly from those for linear ones due to the disparate topologies between the line and the circle. We overcome the aforementioned problem of modelling high volatility data by appealing to the area of probability distributions for directional data. First, methods of construction of probability distributions for such data are presented. This is a challenging problem leading to that of deriving distributions on smooth manifolds, such as those on the torus and the hypertorus. Then, it is shown how methods for DD can be exploited to provide solutions to obtaining crucial inference for high volatility distributions. The use of DDSTAP, the statistical package for DD, developed by the speaker is demonstrated for detection of change-point retrospectively. Online detection methods are then proposed for such distributions. While the modelling problem may be overcome by a judicious choice from the family of distributions enhanced for DD, non-trivial difficulties are encountered in deriving optimal decision rules with them. Once the change-point is detected, characteristics of the portfolio affected by it must be evaluated. The most prominent characteristic in terms of the risk measure certainly is Value at Risk (VaR). It refers to the question of how much a portfolio position can fall in value over a certain time period with a a priori chosen probability. VaR is the crucial measure in the financial sectors for determining market risk and mandatory capital reserves. The estimation of VaR is hence of substantial importance. We briefly discuss this aspect also. The above methods are exemplified through several real-life financial data sets. Finally, several interesting and important problems in this context for future research are exposed. 14 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

17 KN-3 Art, Science and the Secret Sauce - A recipe for building world class analytics capability Srikanth Velamakanni Fractal Analytics Inc. Analytics has become critical to better decision making for organizations around the world. While the concepts surrounding analytics have been around for 50+ years, recent developments in AI/Machine learning (science), understanding human behavior (art) and the organizational environment (secret sauce) have made it challenging for companies to create world class analytics capability to deliver innovation, insight and impact. The complexities of Big data, need for sophisticated techniques, lack of sufficient consumer insight and challenges in hiring/building a team make it hard for organizations to realize the promise of analytics to drive competitive advantage. S-028 Role of Inclusive Financial Services in Empowering the MSME sector for a Green Economy: An Indian Perspective Raka Banerji Army Institute of Management, Kolkata Sudipti Banerjea University of Calcutta, Kolkata T his research paper attempts to do an impact assessment of the role of financial services in entrepreneurship development within the MSME sector in India. Access to well-functioning and efficient financial services can empower the micro and small enterprises, allowing them to better integrate into the country s productive processes and contribute to the more resourceefficient and sustainable economic growth, thus, addressing the issues of economic and social equity. Financial inclusion in this particular sector can facilitate the up scaling of innovations for nurturing the energy-efficient technology necessary for sustaining the Green Economy. The study focuses on a strongly positive link between the total outstanding credit of all the scheduled commercial banks to the MSME sector and growth of the total product of the MSME sector during , using the Regression Analysis and Time Series model like NLS and Autoregressive Moving Average (ARMA) approach. The results highlight that the enhancement of financial assistance clearly generates a positive and statistically significant impact on the growth of the MSME sector which is capable of contributing in big way towards the self-sustaining economic growth in India. This study also highlights several related issues on which more exploratory research is needed in the context of channelizing financial assistance to the MSME sector for effectively taking the economy on the path of green growth. 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 15

18 S-043 Commodity Indices: Defining their Role in Indian Market- Understanding Dynamic Conditional Correlation with Stock Index in Multi-resolution Set-up Rahul Deora Indian Institute of Technology Kharagpur Brajesh Kumar O P Jindal Global University, Recently commodity products have been widely recognised as an important asset class. Financial investors regard commodity investing very effective and important as it helps in diversifying portfolio risk, improving the risk/return profile of the portfolio and works as hedging tool against inflation. In India, commodity future trading is relatively new and facing restrictions/oppositions in terms of less innovative products and limited participation. Commodity indices in India are not traded, however, exchanges and investors are advocating the need of commodity indices as important investment vehicle. Hence, this study proposes a wavelet-based multi-resolution DCC-GARCH model to investigate dynamic conditional correlation between Indian stock index and commodity indices. We consider NIFTY as equity index and for commodity indices, MCXCOMDEX, MCXAGRI, MCXENERGY, MCXMETAL of MCX are used. We decompose the daily data into different frequencies/resolutions (2, 4, 8, and 16 days) using wavelet analysis to understand the characteristics of conditional correlation structure between NIFTY and commodity indices. The data rages from 1st August 2005 to 5th January We find that direction and magnitude of conditional correlations significantly vary with their time scales. MCXMETAL is relatively less correlated (though very less on absolute basis) with NIFTY in shortest time horizon (2 and 4 days) than other indices, gives a signal to daily traders to accommodate MCXMETAL in their portfolio. However, in longest time horizon (8 and 16 days), MCXAGRI shows lower correlation giving similar signals to investors who trade on monthly or bi-monthly basis. S-018 Devising the Usp in Sporadic Markets - A Study Done on Wedding Planners in Tamilnadu P.Baba Gnanakumar Sri Krishna Arts and Science College, Coimbatore This research explores the unique selling proposition (USP) in wedding planner market and aim to position it at various service levels. We explored the mismatch between the customer expectations and wedding planner services, and discovered the common factor that discriminates both of them in the state of Tamilnadu. Based on the common factor, the service level leap for the wedding planners has been identified. This research identified the gap among customer expectation and wedding planners service level weights by extorting multivariate analysis; determine the USP by employing Box Ljung Statistic, and recursive positioning of USP with MDD analysis. We conclude that an integrated time-driven network is essential to satisfy the customers. The additional cost involved in the time-driven network is to be considered as an opportunity cost. Time-driven network can be implemented using MDD analysis. The research enables to identify a non-linear growth tools necessary while marketing to different types of customers following different cultures. Keywords: Service level leaps, Fragmented Marketing, Extreme Marketing 16 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

19 S-139 Applications of Bayesian Networks in Business Intelligence Heena Timani Ahmedabad University Bayesian network is a kind of probabilistic graphical model to represent the relationships A between variables. It provides an effective and natural way to represent causal relationships. Bayesian networks have the ability of capturing both qualitative knowledge through their network structure, and quantitative knowledge through their parameters. While expert knowledge from practitioners is mostly qualitative, it can be used directly for building the structure of a Bayesian network. In addition, data mining algorithms can encode both qualitative and quantitative knowledge and encode both forms simultaneously in a Bayesian network. As a result, Bayesian networks can bridge the gap between different types of knowledge and serve to unify all available knowledge into a single form of representation. Within many domains, the amount of data available is so large that learning directly on the data is intractable. In order to deal with this intractability, learning is applied to features extracted from the data. The method for extracting features is generally specific,. In this paper applications related to data mining in Electronic commerce are discussed using Bayesian Classifiers and Bayesian Networks techniques for extracting and encoding knowledge from data. Keywords: Bayesian Classifiers, Probabilistic graphical model, Electronic Commerce, Data mining S-181 Improvements to be introduced in the algorithms of CVRP and VRPB when solved over instances involving asymmetric distances and heterogeneous fleet. Kaviti Keshav Kumar, Sunil Agrawal PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur T his paper shows the modifications to be introduced in the models of Capacitated Vehicle Routing problem (CVRP) and Vehicle Routing Problem with backhauls (VRPB). In the paper Ubeda et al. (2011) CVRP and VRPB models have been proposed over instances involving symmetric distances between the nodes which follow the triangular inequality. The fleet has been considered to be homogeneous. Our work is based on instances in which the distances between the nodes are asymmetric and do not follow the triangle inequality and the fleet is considered to be heterogeneous. The CVRP and VRPB models given by Ubeda et al. (2011) are good enough to solve over the instances in our work and provide an optimal solution. However, in our work we have proposed two modifications in the constraints of the existing models and have shown with the help of a numerical example that these modifications lead to the improvement in the value of the objective function obtained. Three different cases have been considered to show the effects of these two modifications. Case I consists of the model with the first modification only which gives the flexibility to choose only those vehicles in the fleet that are good enough to satisfy the demand of all the customer nodes instead of using all the available vehicles. Case II consists of the model with the second modification which allows every node to be visited by more than one vehicle instead of restricting every node to be visited by a single vehicle. Case III consists of the model with both the modifications 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 17

20 considered simultaneously. In the numerical problem the results obtained by the application of the above mentioned cases in the respective models have been compared with the results obtained by the unmodified models of CVRP and VRPB (given by Ubeda et al. (2011)) when solved over the instances mentioned above. The results obtained in the former case were better compared to the latter and they have been explained in a detailed manner in the paper. S-081 Determinants of Lapsation of Policies: An Investigation in Indian Insurance Sector Sunita Mall School of Science, NMIMS Seshadev Sahoo IIM Lucknow In this Research paper, we study the impact of fourteen explanatory variables related to product and policy holder characteristics on lapsation of Indian Life Insurance Company. Our study has a distinguished contribution to the existing literature. The data is obtained from a large Indian life insurance company and includes product categories like Traditional and Unit-linked products which is a consumer database of 2967 contracts. The analyzed time period taken is from We extend the existing literature by considering some new explanatory variables related to product and policyholder characteristics like dependency, occupation, gender, education, marital status and outstanding premium. Lapse of a contract is defined as a binary event as the contract can either be valid or lapsed and we use logistic regression model to analyze the lapse rates with respect to the specific explanatory variables. The findings of the paper show that product characteristics like sum insure, product type, outstanding premium, mode of payment, policy duration and outstanding policy duration and policy holder characteristics like age of the policy holder, occupation, dependency, marital status are important drivers of lapsation. For policy duration, our result contradicted the existing literature. This paper displays a better picture of the lapse drivers and will surely help the Insurance Company to minimize the lapse. Keywords: Lapsation, Dependency, Outstanding premium, outstanding duration, Rider S-083 On Testing Exponentiality against NBAFR Alternatives Aditi Pal, Murari Mitra Bengal Engineering and Science University, Shibpur M.Z. Anis Indian Statistical Institute, Kolkata In this paper, we propose an interesting approach for testing exponentiality against NBAFR alternatives based on a technique involving density estimation. Thus our testing problem can be formulated as: H 0 : F is exponential vs. H 1 : F is NBAFR and not exponential A measure of deviation from exponentiality has been derived on the basis of an inequality which we have proved. A test procedure has been suggested and a test statistic has been constructed using density estimators. The asymptotic normality of the test statistic has been 18 3rd IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence