Download or read book Financial Data Analytics written by Sinem Derindere Köseoğlu and published by Springer Nature. This book was released on 2022-04-25 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.

Download or read book Financial Statistics and Data Analytics written by Shuangzhe Li and published by MDPI. This book was released on 2021-03-02 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.

Download or read book An Introduction to Analysis of Financial Data with R written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2014-08-21 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including: Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques. An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.

Download or read book Data Analysis for Corporate Finance written by Mariano F. Scandizzo CFA CQF and published by Fulton Books, Inc.. This book was released on 2021-12-07 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you ever tried to learn to code or to use advanced visualization tools? If so, I am sure you know how daunting it is to learn by yourself. Generally, tools and books follow an encyclopedism approach, i.e., books attempt to teach every feature about a coding language or tool. This implies hundreds, if not thousands of pages simply to tackle a single topic, whether SQL, Python, MS Excel, MS PowerBI, you name it. The journey from zero to hero to become proficient using numerical and visualization tools to take your career to the next level becomes an ordeal that requires years and thousands of pages just to begin putting the pieces of the puzzle together. However, the reality is that you do not need to learn absolutely every available feature to use those tools and deliver a superior project. Rather than teaching you about the forest, I will discuss specific trees. Why? Because once you become familiar and confident nurturing a few trees, growing a forest becomes a simple process of planting new trees. This book provides the fundamental blocks so that you can learn about financial data science and take these tools and start using them tomorrow. The scope of the selected tools will empower you to see a considerable improvement in your financial modeling skills. The book is designed to provide corporate finance professionals the ability to start immediately using advance tools for concrete real-world tasks. Therefore, this book is all about functionalism. It is about providing you with tools that will put you to work and dramatically change the way you analyze data. Once you see the benefits, it will become natural to keep expanding your domain knowledge, leveraging today's endless available educational resources.

Download or read book Statistical Analysis of Financial Data written by James Gentle and published by CRC Press. This book was released on 2020-03-12 with total page 666 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets, describing the market operations and using exploratory data analysis to illustrate the nature of financial data. The software used to obtain the data for the examples in the first chapter and for all computations and to produce the graphs is R. However discussion of R is deferred to an appendix to the first chapter, where the basics of R, especially those most relevant in financial applications, are presented and illustrated. The appendix also describes how to use R to obtain current financial data from the internet. Chapter 2 describes the methods of exploratory data analysis, especially graphical methods, and illustrates them on real financial data. Chapter 3 covers probability distributions useful in financial analysis, especially heavy-tailed distributions, and describes methods of computer simulation of financial data. Chapter 4 covers basic methods of statistical inference, especially the use of linear models in analysis, and Chapter 5 describes methods of time series with special emphasis on models and methods applicable to analysis of financial data. Features * Covers statistical methods for analyzing models appropriate for financial data, especially models with outliers or heavy-tailed distributions. * Describes both the basics of R and advanced techniques useful in financial data analysis. * Driven by real, current financial data, not just stale data deposited on some static website. * Includes a large number of exercises, many requiring the use of open-source software to acquire real financial data from the internet and to analyze it.

Download or read book Statistics and Data Analysis for Financial Engineering written by David Ruppert and published by Springer. This book was released on 2015-04-21 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Download or read book Data Analysis for Business Economics and Policy written by Gábor Békés and published by Cambridge University Press. This book was released on 2021-05-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Download or read book Analytical Corporate Finance written by Angelo Corelli and published by Springer Nature. This book was released on 2023-10-31 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book draws readers’ attention to the financial aspects of daily life at a corporation by combining a robust mathematical setting and the explanation and derivation of the most popular models of the firm. Intended for third-year undergraduate students of business finance, quantitative finance, and financial mathematics, as well as first-year postgraduate students, it is based on the twin pillars of theory and analytics, which merge in a way that makes it easy for students to understand the exact meaning of the concepts and their representation and applicability in real-world contexts. Examples are given throughout the chapters in order to clarify the most intricate aspects; where needed, there are appendices at the end of chapters, offering additional mathematical insights into specific topics. Due to the recent growth in knowledge demand in the private sector, practitioners can also profit from the book as a bridge-builder between university and industry. Lastly, the book provides useful information for managers who want to deepen their understanding of risk management and come to recognize what may have been lacking in their own systems.

Download or read book Big Data Science in Finance written by Irene Aldridge and published by John Wiley & Sons. This book was released on 2021-01-08 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Download or read book Corporate Financial Reporting and Analysis written by S. David Young and published by John Wiley & Sons. This book was released on 2018-11-28 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate Financial Reporting Analysis combines comprehensive coverage and a rigorous approach to modern financial reporting with a readable and accessible style. Merging traditional principles of corporate finance and accepted reporting practices with current models enable the reader to develop essential interpretation and analysis skills, while the emphasis on real-world practicality and methodology provides seamless coverage of both GAAP and IFRS requirements for enhanced global relevance. Two decades of classroom testing among INSEAD MBA students has honed this text to provide the clearest, most comprehensive model for financial statement interpretation and analysis; a concise, logically organized pedagogical framework includes problems, discussion questions, and real-world case studies that illustrate applications and current practices, and in-depth examination of key topics clarifies complex concepts and builds professional intuition. With insightful coverage of revenue recognition, inventory accounting, receivables, long-term assets, M&A, income taxes, and other principle topics, this book provides both education and ongoing reference for MBA students.

Download or read book Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Download or read book Analyzing Financial Data and Implementing Financial Models Using R written by Clifford S. Ang and published by Springer Nature. This book was released on 2021-06-23 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.

Download or read book Corporate Financial Analysis with Microsoft Excel written by Francis J. Clauss and published by McGraw Hill Professional. This book was released on 2009-08-23 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate Financial Analysis with Microsoft® Excel® visualizes spreadsheets as an effective management tool both for financial analysis and for coordinating its results and actions with marketing, sales, production and service operations, quality control, and other business functions. Taking an integrative view that promotes teamwork across corporate functions and responsibilities, the book contains dozens of charts, diagrams, and actual Excel® screenshots to reinforce the practical applications of every topic it covers. The first two sections—Financial Statements and Cash Budgeting—explain how to use spreadsheets for: Preparing income statements, balance sheets, and cash flow statements Performing vertical and horizontal analyses of financial statements Determining financial ratios and analyzing their trends and significance Combining quantitative and judgmental techniques to improve forecasts of sales revenues and customer demands Calculating and applying the time value of money Managing inventories, safety stocks, and the allocation of resources The third and final section—Capital Budgeting—covers capital structure, the cost of capital, and leverage; the basics of capital budgeting, including taxes and depreciation; applications, such as new facilities, equipment replacement, process improvement, leasing versus buying, and nonresidential real estate; and risk analysis of capital budgets and the potential impacts of unforeseen events. Corporate Financial Analysis with Microsoft® Excel® takes a broad view of financial functions and responsibilities in relation to those of other functional parts of modern corporations, and it demonstrates how to use spreadsheets to integrate and coordinate them. It provides many insightful examples and case studies of real corporations, including Wal- Mart, Sun Microsystems, Nike, H. J. Heinz, Dell, Microsoft, Apple Computer, and IBM. Corporate Financial Analysis with Microsoft® Excel® is the ideal tool for managing your firm’s short-term operations and long-term capital investments.

Download or read book Applied Corporate Finance written by Aswath Damodaran and published by John Wiley & Sons. This book was released on 2014-10-27 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aswath Damodaran, distinguished author, Professor of Finance, and David Margolis, Teaching Fellow at the NYU Stern School of Business, have delivered the newest edition of Applied Corporate Finance. This readable text provides the practical advice students and practitioners need rather than a sole concentration on debate theory, assumptions, or models. Like no other text of its kind, Applied Corporate Finance, 4th Edition applies corporate finance to real companies. It now contains six real-world core companies to study and follow. Business decisions are classified for students into three groups: investment, financing, and dividend decisions.

Download or read book Financial Planning Analysis and Performance Management written by Jack Alexander and published by John Wiley & Sons. This book was released on 2018-06-13 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Critical insights for savvy financial analysts Financial Planning & Analysis and Performance Management is the essential desk reference for CFOs, FP&A professionals, investment banking professionals, and equity research analysts. With thought-provoking discussion and refreshing perspective, this book provides insightful reference for critical areas that directly impact an organization’s effectiveness. From budgeting and forecasting, analysis, and performance management, to financial communication, metrics, and benchmarking, these insights delve into the cornerstones of business and value drivers. Dashboards, graphs, and other visual aids illustrate complex concepts and provide reference at a glance, while the author’s experience as a CFO, educator, and general manager leads to comprehensive and practical analytical techniques for real world application. Financial analysts are under constant pressure to perform at higher and higher levels within the realm of this consistently challenging function. Though areas ripe for improvement abound, true resources are scarce—until now. This book provides real-world guidance for analysts ready to: Assess performance of FP&A function and develop improvement program Improve planning and forecasting with new and provocative thinking Step up your game with leading edge analytical tools and practical solutions Plan, analyze and improve critical business and value drivers Build analytical capability and effective presentation of financial information Effectively evaluate capital investments in uncertain times The most effective analysts are those who are constantly striving for improvement, always seeking new solutions, and forever in pursuit of enlightening resources with real, useful information. Packed with examples, practical solutions, models, and novel approaches, Financial Planning & Analysis and Performance Management is an invaluable addition to the analyst’s professional library. Access to a website with many of the tools introduced are included with the purchase of the book.

Download or read book Analyzing Data with Power BI and Power Pivot for Excel written by Alberto Ferrari and published by Microsoft Press. This book was released on 2017-04-28 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness. How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one! By reading this book, you will: • Gain an understanding of the basics of data modeling, including tables, relationships, and keys • Familiarize yourself with star schemas, snowflakes, and common modeling techniques • Learn the importance of granularity • Discover how to use multiple fact tables, like sales and purchases, in a complex data model • Manage calendar-related calculations by using date tables • Track historical attributes, like previous addresses of customers or manager assignments • Use snapshots to compute quantity on hand • Work with multiple currencies in the most efficient way • Analyze events that have durations, including overlapping durations • Learn what data model you need to answer your specific business questions About This Book • For Excel and Power BI users who want to exploit the full power of their favorite tools • For BI professionals seeking new ideas for modeling data

Download or read book Private Real Estate Investment written by Roger J. Brown and published by Elsevier. This book was released on 2005-03-29 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fiduciary responsibilities and related court-imposed liabilities have forced investors to assess market conditions beyond gut level, resulting in the development of sophisticated decision-making tools. Roger Brown's use of historical real estate data enables him to develop tools for gauging the impact of circumstances on relative risk. His application of higher level statistical modeling to various aspects of real estate makes this book an essential partner in real estate research. Offering tools to enhance decision-making for consumers and researchers in market economies of any country interested in land use and real estate investment, his book will improve real estate market efficiency. With property the world's biggest asset class, timely data on housing prices just got easier to find and use. Excellent mixture of theory and application Data and database analysis techniques are the first of their kind