Microsoft Excel 97 Developer S Handbook
Download Microsoft Excel 97 Developer S Handbook PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Microsoft Excel 97 Developer S Handbook book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Handbook of Quantitative Finance and Risk Management
Author: Cheng-Few Lee
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-06-14
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.
Handbook Of Investment Analysis, Portfolio Management, And Financial Derivatives (In 4 Volumes)
This four-volume handbook covers important topics in the fields of investment analysis, portfolio management, and financial derivatives. Investment analysis papers cover technical analysis, fundamental analysis, contrarian analysis, and dynamic asset allocation. Portfolio analysis papers include optimization, minimization, and other methods which will be used to obtain the optimal weights of portfolio and their applications. Mutual fund and hedge fund papers are also included as one of the applications of portfolio analysis in this handbook.The topic of financial derivatives, which includes futures, options, swaps, and risk management, is very important for both academicians and partitioners. Papers of financial derivatives in this handbook include (i) valuation of future contracts and hedge ratio determination, (ii) options valuation, hedging, and their application in investment analysis and portfolio management, and (iii) theories and applications of risk management.Led by worldwide known Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues of investment analysis, portfolio management, and financial derivatives based on his years of academic and industry experience.
Essentials of Excel VBA, Python, and R
This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry. This second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the first volume for dedicated content on financial statistics, and portfolio analysis.