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 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 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 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 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 Statistical Analysis of Financial Data in R written by René Carmona and published by Springer Science & Business Media. This book was released on 2013-12-13 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns of risk management are addressed by the study of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Principal component analysis (PCA), smoothing, and regression techniques are applied to the construction of yield and forward curves. Time series analysis is applied to the study of temperature options and nonparametric estimation. Nonlinear filtering is applied to Monte Carlo simulations, option pricing and earnings prediction. This textbook is intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. It is sprinkled with practical examples using market data, and each chapter ends with exercises. Practical examples are solved in the R computing environment. They illustrate problems occurring in the commodity, energy and weather markets, as well as the fixed income, equity and credit markets. The examples, experiments and problem sets are based on the library Rsafd developed for the purpose of the text. The book should help quantitative analysts learn and implement advanced statistical concepts. Also, it will be valuable for researchers wishing to gain experience with financial data, implement and test mathematical theories, and address practical issues that are often ignored or underestimated in academic curricula. This is the new, fully-revised edition to the book Statistical Analysis of Financial Data in S-Plus. René Carmona is the Paul M. Wythes '55 Professor of Engineering and Finance at Princeton University in the department of Operations Research and Financial Engineering, and Director of Graduate Studies of the Bendheim Center for Finance. His publications include over one hundred articles and eight books in probability and statistics. He was elected Fellow of the Institute of Mathematical Statistics in 1984, and of the Society for Industrial and Applied Mathematics in 2010. He is on the editorial board of several peer-reviewed journals and book series. Professor Carmona has developed computer programs for teaching statistics and research in signal analysis and financial engineering. He has worked for many years on energy, the commodity markets and more recently in environmental economics, and he is recognized as a leading researcher and expert in these areas.

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 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, has 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 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

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 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 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 Quantitative Corporate Finance written by John B. Guerard Jr. and published by Springer Nature. This book was released on 2020-11-21 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds. Now in its second edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance. New to the second edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.

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 439 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 Corporate Finance written by Pierre Vernimmen and published by John Wiley & Sons. This book was released on 2014-10-09 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt: Merging theory and practice into a comprehensive, highly-anticipated text Corporate Finance continues its legacy as one of the most popular financial textbooks, with well-established content from a diverse and highly respected author team. Unique in its features, this valuable text blends theory and practice with a direct, succinct style and commonsense presentation. Readers will be introduced to concepts in a situational framework, followed by a detailed discussion of techniques and tools. This latest edition includes new information on venture finance and debt structuring, and has been updated throughout with the most recent statistical tables. The companion website provides statistics, graphs, charts, articles, computer models, and classroom tools, and the free monthly newsletter keeps readers up to date on the latest happenings in the field. The authors have generously made themselves available for questions, promising an answer in seventy-two hours. Emphasizing how key concepts relate to real-world situations is what makes Corporate Finance a valuable reference with real relevance to the professional and student alike. Readers will gain insight into the methods and tools that shape the industry, allowing them to: Analyze investments with regard to hurdle rates, cash flows, side costs, and more Delve into the financing process and learn the tools and techniques of valuation Understand cash dividends and buybacks, spinoffs, and divestitures Explore the link between valuation and corporate finance As the global economy begins to recover, access to the most current information and statistics will be required. To remain relevant in the evolving financial environment, practitioners will need a deep understanding of the mechanisms at work. Corporate Finance provides the expert guidance and detailed explanations for those requiring a strong foundational knowledge, as well as more advanced corporate finance professionals.