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

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.

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.

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.

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.

Quantitative portfolio management has become a highly specialized discipline. Computing power and software improvements have advanced the field to a level that would not have been thinkable when Harry Markowitz began the modern era of quantitative portfolio management in 1952. In addition to raw computing power, major advances in financial economics and econometrics have shaped academia and the financial industry over the last 60 years. While the idea of a general theory of finance is still only a distant hope, asset managers now have tools in the financial engineering kit that address specific problems in their industry. The Oxford Handbook of Quantitative Asset Management consists of seven sections that explore major themes in current theoretical and practical use. These themes span all aspects of a modern quantitative investment organization. Contributions from academics and practitioners working in leading investment management organizations bring together the key theoretical and practical aspects of the field to provide a comprehensive overview of the major developments in the area.

In Volatility Trading, Sinclair offers you a quantitative model for measuring volatility in order to gain an edge in your everyday option trading endeavors. With an accessible, straightforward approach. He guides traders through the basics of option pricing, volatility measurement, hedging, money management, and trade evaluation. In addition, Sinclair explains the often-overlooked psychological aspects of trading, revealing both how behavioral psychology can create market conditions traders can take advantage of-and how it can lead them astray. Psychological biases, he asserts, are probably the drivers behind most sources of edge available to a volatility trader. Your goal, Sinclair explains, must be clearly defined and easily expressed-if you cannot explain it in one sentence, you probably aren't completely clear about what it is. The same applies to your statistical edge. If you do not know exactly what your edge is, you shouldn't trade. He shows how, in addition to the numerical evaluation of a potential trade, you should be able to identify and evaluate the reason why implied volatility is priced where it is, that is, why an edge exists. This means it is also necessary to be on top of recent news stories, sector trends, and behavioral psychology. Finally, Sinclair underscores why trades need to be sized correctly, which means that each trade is evaluated according to its projected return and risk in the overall context of your goals. As the author concludes, while we also need to pay attention to seemingly mundane things like having good execution software, a comfortable office, and getting enough sleep, it is knowledge that is the ultimate source of edge. So, all else being equal, the trader with the greater knowledge will be the more successful. This book, and its companion CD-ROM, will provide that knowledge. The CD-ROM includes spreadsheets designed to help you forecast volatility and evaluate trades together with simulation engines.