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Download or read book Managing the Transition to a Sustainable Enterprise written by Rob van Tulder and published by Routledge. This book was released on 2013-09-23 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: In combining practice and theory, this textbook provides a management perspective on the ‘business case’ for sustainability. Drawing on examples from 20 frontrunner companies located in the Netherlands, it builds upon a unique research project in which CEOs and middle-managers gave access not only to their decision-making process, but also revealed how their perceptions shaped the transition process. This book identifies four different archetypes of business cases and related business models that business students and managers can use to identify phases and related attitudes towards sustainability. The book provides in-depth analysis and insight into: • theoretical concepts and an overview of the relevant literature • the different business cases for sustainability • behavioural characteristics of each phase and the typical barriers between them • more than 70 tipping points • approaches to shaping stakeholder dialogue • effective engagement of stakeholders in each phase of transition • how companies move through the phases towards higher levels of sustainability • insights of employees of the 20 companies whether the business case was really achieved • summary of the interventions which have proved successful in these companies. This book offers students as well as managers of vocational and academic institutions at undergraduate and postgraduate level insight into real-life transition processes towards sustainability.

Download or read book Python for Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2014-12-11 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies

Download or read book jQuery Novice to Ninja written by Earle Castledine and published by SitePoint Pty Ltd. This book was released on 2012-02-16 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: jQuery: Novice to Ninja, 2nd Edition is the perfect book to jump-start your journey into jQuery. You’ll learn all the basics, so you’ll be able to truly appreciate the power of this JavaScript framework. Then you’ll move on to more advanced techniques, such as plugin development and the creation of almost every conceivable UI widget. A practical, hands-on guide to using jQuery Ready-to-use best practice solutions Includes complete working code Fully updated for jQuery 1.6

Download or read book Python for Finance Cookbook written by Eryk Lewinson and published by Packt Publishing Ltd. This book was released on 2020-01-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook Description Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach. What you will learnDownload and preprocess financial data from different sourcesBacktest the performance of automatic trading strategies in a real-world settingEstimate financial econometrics models in Python and interpret their resultsUse Monte Carlo simulations for a variety of tasks such as derivatives valuation and risk assessmentImprove the performance of financial models with the latest Python librariesApply machine learning and deep learning techniques to solve different financial problemsUnderstand the different approaches used to model financial time series dataWho this book is for This book is for financial analysts, data analysts, and Python developers who want to learn how to implement a broad range of tasks in the finance domain. Data scientists looking to devise intelligent financial strategies to perform efficient financial analysis will also find this book useful. Working knowledge of the Python programming language is mandatory to grasp the concepts covered in the book effectively.

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Download or read book Mastering Python for Finance written by James Ma Weiming and published by Packt Publishing Ltd. This book was released on 2015-04-29 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.