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This open access book investigates the inter-relationship between the mind and a potential opportunity to explore the psychology of entrepreneurship. Building on recent research, this book offers a broad scope investigation of the different aspects of what goes on in the mind of the (potential) entrepreneur as he or she considers the pursuit of a potential opportunity, the creation of a new organization, and/or the selection of an entrepreneurial career. This book focuses on individuals as the level of analysis and explores the impact of the organization and the environment only inasmuch as they impact the individual’s cognitions. Readers will learn why some individuals and managers are able to able to identify and successfully act upon opportunities in uncertain environments while others are not. This book applies a cognitive lens to understand individuals’ knowledge, motivation, attention, identity, and emotions in the entrepreneurial process. .

Business. --- Entrepreneurship. --- Cognitive psychology. --- Business and Management. --- Cognitive Psychology. --- Employee Health and Wellbeing. --- Psychology, Cognitive --- Cognitive science --- Psychology --- Entrepreneur --- Intrapreneur --- Capitalism --- Business incubators --- Trade --- Economics --- Management --- Commerce --- Industrial management --- Consciousness. --- Employee health promotion. --- Employee wellness programs --- Employees --- Health promotion in the workplace --- Occupational health promotion --- Workplace health promotion --- Worksite health promotion --- Health promotion --- Occupational health services --- Apperception --- Mind and body --- Perception --- Philosophy --- Spirit --- Self --- Entrepreneurship --- Cognitive Psychology --- Employee Health and Wellbeing --- Human Resource Management --- entrepreneurial mindset --- cognitive processes --- prior knowledge --- exploitation --- motivation --- financial motivation --- non-financial motivation --- entrepreneurial opportunities --- self-identity --- well-being --- work identity --- Cognition & cognitive psychology --- Personnel & human resources management

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Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.

deposit insurance --- implied volatility --- static arbitrage --- parameterization --- machine learning --- calibration --- dichotomous response --- predictive model --- tree boosting --- GLM --- validation --- generalised linear modelling --- zero-inflated poisson model --- telematics --- benchmark --- cross-validation --- prediction --- stock return volatility --- long-term forecasts --- overlapping returns --- autocorrelation --- chain ladder --- Bornhuetter–Ferguson --- maximum likelihood --- exponential families --- canonical parameters --- prior knowledge --- accelerated failure time model --- chain-ladder method --- local linear kernel estimation --- non-life reserving --- operational time --- zero-inflation --- overdispersion --- automobile insurance --- risk classification --- risk selection --- least-squares monte carlo method --- proxy modeling --- life insurance --- Solvency II --- claims prediction --- export credit insurance --- semiparametric modeling --- VaR estimation --- analyzing financial data --- n/a --- Bornhuetter-Ferguson