Download or read book MARKET MODELS A GUIDE TO FINANCIAL DATA ANALYSIS With CD written by Carol Alexander and published by . This book was released on 2009-01-01 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market_Desc: Primarily this book has been written for financial institutions (investment banks, asset management companies, investment analysis personnel, corporate treasuries, insurance companies, pension funds, risk management companies/consultants and regulatory bodies.) Special Features: "The author uses an applications-based approach."Includes the latest developments in VaR. About The Book: Models play a crucial role in today's financial markets and an understanding and appreciation of how to model financial data is key to any finance practitioner's skill set. Model developers are faced with many decisions, about the data, methodology, model specification and testing, prior to the final model implementation. This is costly and how many media reports in recent years have highlighted the mismanagement of such resources! It is crucial to make the right choices at every stage of model development. But this is as much an 'art' as a 'science'. The talented interpretation of results is just as critical for success as the mathematical foundation. This new book is the first of its kind. As well as providing numerous real world examples to illustrate concepts in an accessible manner, the accompanying CD will allow the reader to implement the examples themselves and adapt them for their own purposes. Professor Carol Alexander, Chair of Risk Management at the ISMA Centre and one of the best known names in financial data analysis, provides an authoritative and up-to-date treatment of model development. She brings many new insights to the practicalities of volatility and correlation analysis, modelling the market risk of portfolios and statistical models. New models that are based on cointegration, principal component analysis, normal mixture densities, GARCH and many other areas are elegantly and rigorously explained, with an emphasis on concepts that makes this text accessible to a very wide audience. The book is also designed to be self contained, with many technical appendices. Market Models is the ideal reference for all those involved in model selection and development

Download or read book Market Models written by Carol Alexander and published by John Wiley & Sons. This book was released on 2001-12-04 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: In part 1, Carol Alexander brings many new insights to the pricing and hedging of options with her understanding of volatility and correlation, and the uncertainty which surrounds these key determinants of option portfolio risk. Modelling the market risk of portfolios is covered in part 2 where the main focus is on a linear algebraic approach; the covariance matrix and principal component analysis are developed as key tools for the analysis of financial systems. The traditional time series econometric approach is explained in part 3, with coverage ranging from the application cointegration to long-short equity hedge funds, to high-frequency data prediction using neural networks and nearest neighbour algorithms . Throughout this text the emphasis is on understanding concepts and implementing solutions. It has been designed to be accessible to a very wide audience: the coverage is comprehensive and complete and the technical appendix makes the book largely self-contained.

Download or read book Strategic Analysis Of Financial Markets The In 2 Volumes written by Steven D Moffitt and published by World Scientific Publishing Company. This book was released on 2017-03-24 with total page 1119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 1 of 'The Strategic Analysis of Financial Markets,' — Framework, is premised on the belief that markets can be understood only by dropping the assumptions of rationality and efficient markets in their extreme forms, and showing that markets still have an inherent order and inherent logic. But that order results primarily from the 'predictable irrationality' of investors, as well as from people's uncoordinated attempts to profit. The market patterns that result do not rely on rationality or efficiency.A framework is developed for understanding financial markets using a combination of psychology, statistics, game and gambling analysis, market history and the author's experience. It expresses analytically how professional investors and traders think about markets — as games in which other participants employ inferior, partially predictable strategies. Those strategies' interactions can be toxic and lead to booms, bubbles, busts and crashes, or can be less dramatic, leading to various patterns that are mistakenly called 'market inefficiencies' and 'stylized facts.'A logical case is constructed, starting from two foundations, the psychology of human decision making and the 'Fundamental Laws of Gambling.' Applying the Fundamental Laws to trading leads to the idea of 'gambling rationality' (grationality), replacing the efficient market's concept of 'rationality.' By classifying things that are likely to have semi-predictable price impacts (price 'distorters'), one can identify, explore through data analysis, and create winning trading ideas and systems. A structured way of doing all this is proposed: the six-step 'Strategic Analysis of Market Method.' Examples are given in this and Volume 2.Volume 2 of 'The Strategic Analysis of Financial Markets' — Trading System Analytics, continues the development of Volume 1 by introducing tools and techniques for developing trading systems and by illustrating them using real markets. The difference between these two Volumes and the rest of the literature is its rigor. It describes trading as a form of gambling that when properly executed, is quite logical, and is well known to professional gamblers and analytical traders.But even those elites might be surprised at the extent to which quantitative methods have been justified and applied, including a life cycle theory of trading systems. Apart from a few sections that develop background material, Volume 2 creates from scratch a trading system for Eurodollar futures using principles of the Strategic Analysis of Markets Method (SAMM), a principled, step-by-step approach to developing profitable trading systems. It has an entire Chapter on mechanical methods for testing and improvement of trading systems, which transcends the rather unstructured and unsatisfactory 'backtesting' literature. It presents a breakout trend following system developed using factor models. It also presents a specific pairs trading system, and discusses its life cycle from an early, highly profitable period to its eventual demise. Recent developments in momentum trading and suggestions on improvements are also discussed.

Download or read book Financial Modeling and Valuation written by Paul Pignataro and published by John Wiley & Sons. This book was released on 2013-07-10 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by the Founder and CEO of the prestigious New York School of Finance, this book schools you in the fundamental tools for accurately assessing the soundness of a stock investment. Built around a full-length case study of Wal-Mart, it shows you how to perform an in-depth analysis of that company's financial standing, walking you through all the steps of developing a sophisticated financial model as done by professional Wall Street analysts. You will construct a full scale financial model and valuation step-by-step as you page through the book. When we ran this analysis in January of 2012, we estimated the stock was undervalued. Since the first run of the analysis, the stock has increased 35 percent. Re-evaluating Wal-Mart 9months later, we will step through the techniques utilized by Wall Street analysts to build models on and properly value business entities. Step-by-step financial modeling - taught using downloadable Wall Street models, you will construct the model step by step as you page through the book. Hot keys and explicit Excel instructions aid even the novice excel modeler. Model built complete with Income Statement, Cash Flow Statement, Balance Sheet, Balance Sheet Balancing Techniques, Depreciation Schedule (complete with accelerating depreciation and deferring taxes), working capital schedule, debt schedule, handling circular references, and automatic debt pay downs. Illustrative concepts including detailing model flows help aid in conceptual understanding. Concepts are reiterated and honed, perfect for a novice yet detailed enough for a professional. Model built direct from Wal-Mart public filings, searching through notes, performing research, and illustrating techniques to formulate projections. Includes in-depth coverage of valuation techniques commonly used by Wall Street professionals. Illustrative comparable company analyses - built the right way, direct from historical financials, calculating LTM (Last Twelve Month) data, calendarization, and properly smoothing EBITDA and Net Income. Precedent transactions analysis - detailing how to extract proper metrics from relevant proxy statements Discounted cash flow analysis - simplifying and illustrating how a DCF is utilized, how unlevered free cash flow is derived, and the meaning of weighted average cost of capital (WACC) Step-by-step we will come up with a valuation on Wal-Mart Chapter end questions, practice models, additional case studies and common interview questions (found in the companion website) help solidify the techniques honed in the book; ideal for universities or business students looking to break into the investment banking field.

Download or read book Market Data Explained written by Marc Alvarez and published by Elsevier. This book was released on 2011-04-01 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market Data Explained is intended to provide a guide to the universe of data content produced by the global capital markets on a daily basis. Commonly referred to as "market data, the universe of content is very wide and the type of information correspondingly diverse. Jargon and acronyms are very common. As a result, users of marker data typically face difficulty in applying the content in analysis and business applications. This guide provides an independent framework for understanding this diversity and streamlining the process of referring to content and how it relates to today's business environment. The book achieves this goal by providing a consistent frame of reference for users of market data. As such, it is built around the concept of a data model – a single, coherent view of the capital markets independent of any one source, such as an exchange. In particular it delineates clearly between the actual data content and how it is delivered (i.e., realtime data streams versus reference data). It shows how the data relates across the universe of securities (i.e., stocks, bonds, derivatives etc.). In this way it provides a logical framework for understanding how new content can be added over time as the business develops. Special features: 1. Uniqueness – this is the first comprehensive catalog and taxonomy to be made available for a business audience 2. Industry Acceptance – the framework described in this book is implemented as a relational data model in the industry today and used by blue chip multinational firms 3. Comprehensiveness – there are no arbitrary distinctions made based on asset class or data type (the legacy approach). The model presented in this book is fully cross asset and makes no distinction between data types (i.e., realtime versus historical/reference data) or sources 4. Independence – the framework is an independent, objective overview of how the data content integrates to provide a coherent view of the data produced by the global capital markets on a daily and intra-day basis. It provides a logical framework for referring to the content and entities that are so intrinsic to this industry - First and only single, comprehensive desk reference to market data produced by the global capital markets on a daily basis - Provides a comprehensive catalog of the market data and a common structure for navigating the complex content and interrelationships - Provides a common taxonomy and naming conventions that handles the highly varied, geographically and language dependent nature of the content

Download or read book Futures Otc World written by and published by . This book was released on 2002 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Derivatives Analytics with Python written by Yves Hilpisch and published by John Wiley & Sons. This book was released on 2015-08-03 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge options analytics and hedging using the power of Python Derivatives Analytics with Python shows you how to implement market-consistent valuation and hedging approaches using advanced financial models, efficient numerical techniques, and the powerful capabilities of the Python programming language. This unique guide offers detailed explanations of all theory, methods, and processes, giving you the background and tools necessary to value stock index options from a sound foundation. You'll find and use self-contained Python scripts and modules and learn how to apply Python to advanced data and derivatives analytics as you benefit from the 5,000+ lines of code that are provided to help you reproduce the results and graphics presented. Coverage includes market data analysis, risk-neutral valuation, Monte Carlo simulation, model calibration, valuation, and dynamic hedging, with models that exhibit stochastic volatility, jump components, stochastic short rates, and more. The companion website features all code and IPython Notebooks for immediate execution and automation. Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. This book is the finance professional's guide to exploiting Python's capabilities for efficient and performing derivatives analytics. Reproduce major stylized facts of equity and options markets yourself Apply Fourier transform techniques and advanced Monte Carlo pricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamically hedge options Recent developments in the Python ecosystem enable analysts to implement analytics tasks as performing as with C or C++, but using only about one-tenth of the code or even less. Derivatives Analytics with Python — Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts.

Download or read book Building Financial Models with Microsoft Excel written by K. Scott Proctor and published by John Wiley and Sons. This book was released on 2009-11-25 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: A proven guide to building financial models from scratch The Second Edition of Building Financial Models with Microsoft Excel + CD-ROM provides beginning and intermediate level computer users with step-by-step instructions on building financial models using Microsoft Excel 2007-the most popular spreadsheet program available. The accompanying CD-ROM contains Excel worksheets that track the course of the book and allow you to build your own financial models. This comprehensive resource also covers important topics such as the concepts of valuation, sensitivity analysis, and contribution margin. Offers accessible guidance on building financial models using Excel 2007 Illustrates how to integrate financial statements such as the balance sheet, income statement, and statement of cash flows Covers the basics of building and using a Capitalization Table Discusses how to best present a financial model Incorporating financial models into business decisions has become an essential element of good business practice, and this book will show you how to excel at this endeavor.

Download or read book Financial Analytics with R written by Mark J. Bennett and published by Cambridge University Press. This book was released on 2016-10-06 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

Download or read book Risk written by and published by . This book was released on 2001-07 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Excel for Business Analysis written by Danielle Stein Fairhurst and published by John Wiley & Sons. This book was released on 2015-05-18 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a guide to building financial models for business proposals, to evaluate opportunities, or to craft financial reports. It covers the principles and best practices of financial modelling, including the Excel tools, formulas, and functions to master, and the techniques and strategies necessary to eliminate errors.

Download or read book Market Risk Analysis Practical Financial Econometrics written by Carol Alexander and published by John Wiley & Sons. This book was released on 2008-05-27 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one-semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM. Empirical examples and case studies specific to this volume include: Factor analysis with orthogonal regressions and using principal component factors; Estimation of symmetric and asymmetric, normal and Student t GARCH and E-GARCH parameters; Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization; Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management; Simulation of normal mixture and Markov switching GARCH returns; Cointegration based index tracking and pairs trading, with error correction and impulse response modelling; Markov switching regression models (Eviews code); GARCH term structure forecasting with volatility targeting; Non-linear quantile regressions with applications to hedging.

Download or read book Python for Finance written by Yves J. Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout 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.

Download or read book Financial Statement Analysis written by Martin S. Fridson and published by John Wiley & Sons. This book was released on 2002-10-01 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Financial Statement Analysis A Practitioner's Guide Third Edition "This is an illuminating and insightful tour of financial statements, how they can be used to inform, how they can be used to mislead, and how they can be used to analyze the financial health of a company." -Professor Jay O. Light Harvard Business School "Financial Statement Analysis should be required reading for anyone who puts a dime to work in the securities markets or recommends that others do the same." -Jack L. Rivkin Executive Vice President (retired) Citigroup Investments "Fridson and Alvarez provide a valuable practical guide for understanding, interpreting, and critically assessing financial reports put out by firms. Their discussion of profits-'quality of earnings'-is particularly insightful given the recent spate of reporting problems encountered by firms. I highly recommend their book to anyone interested in getting behind the numbers as a means of predicting future profits and stock prices." -Paul Brown Chair-Department of Accounting Leonard N. Stern School of Business, NYU "Let this book assist in financial awareness and transparency and higher standards of reporting, and accountability to all stakeholders." -Patricia A. Small Treasurer Emeritus, University of California Partner, KCM Investment Advisors "This book is a polished gem covering the analysis of financial statements. It is thorough, skeptical and extremely practical in its review." -Daniel J. Fuss Vice Chairman Loomis, Sayles & Company, LP

Download or read book An Introduction to High Frequency Finance written by Ramazan Gençay and published by Elsevier. This book was released on 2001-05-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data.This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.

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 Advanced Modelling in Finance using Excel and VBA written by Mary Jackson and published by John Wiley & Sons. This book was released on 2006-08-30 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new and unique book demonstrates that Excel and VBA can play an important role in the explanation and implementation of numerical methods across finance. Advanced Modelling in Finance provides a comprehensive look at equities, options on equities and options on bonds from the early 1950s to the late 1990s. The book adopts a step-by-step approach to understanding the more sophisticated aspects of Excel macros and VBA programming, showing how these programming techniques can be used to model and manipulate financial data, as applied to equities, bonds and options. The book is essential for financial practitioners who need to develop their financial modelling skill sets as there is an increase in the need to analyse and develop ever more complex 'what if' scenarios. Specifically applies Excel and VBA to the financial markets Packaged with a CD containing the software from the examples throughout the book Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.