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Yang provides a solid foundation to address the question of how to trade derivatives. He offers a systematic way of determining the optimal trading size under a given market price.
This book addresses selected practical applications and recent developments in the areas of quantitative financial modeling in derivatives instruments, some of which are from the authors' own research and practice. It is written from the viewpoint of financial engineers or practitioners, and, as such, it puts more emphasis on the practical applications of financial mathematics in the real market than the mathematics itself with precise (and tedious) technical conditions. It attempts to combine economic insights with mathematics and modeling so as to help the reader to develop intuitions.Among the modeling and the numerical techniques presented are the practical applications of the martingale theories, such as martingale model factory and martingale resampling and interpolation. In addition, the book addresses the counterparty credit risk modeling, pricing, and arbitraging strategies from the perspective of a front office functionality and a revenue center (rather than merely a risk management functionality), which are relatively recent developments and are of increasing importance. It also discusses various trading structuring strategies and touches upon some popular credit/IR/FX hybrid products, such as PRDC, TARN, Snowballs, Snowbears, CCDS, and credit extinguishers.While the primary scope of this book is the fixed-income market (with further focus on the interest rate market), many of the methodologies presented also apply to other financial markets, such as the credit, equity, foreign exchange, and commodity markets.
Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner’s hands-on experience. The focus on empirical modeling and practical know-how makes this book a valuable resource for students and professionals. The book starts with the often overlooked context of why and how we trade via a detailed introduction to market structure and quantitative microstructure models. The authors then present the necessary quantitative toolbox including more advanced machine learning models needed to successfully operate in the field. They next discuss the subject of quantitative trading, alpha generation, active portfolio management and more recent topics like news and sentiment analytics. The last main topic of execution algorithms is covered in detail with emphasis on the state of the field and critical topics including the elusive concept of market impact. The book concludes with a discussion on the technology infrastructure necessary to implement algorithmic strategies in large-scale production settings. A git-hub repository includes data-sets and explanatory/exercise Jupyter notebooks. The exercises involve adding the correct code to solve the particular analysis/problem.
This book provides a manual on quantitative financial analysis. Focusing on advanced methods for modelling financial markets in the context of practical financial applications, it will cover data, software and techniques that will enable the reader to implement and interpret quantitative methodologies, specifically for trading and investment. Includes contributions from an international team of academics and quantitative asset managers from Morgan Stanley, Barclays Global Investors, ABN AMRO and Credit Suisse First Boston. Fills the gap for a book on applied quantitative investment & trading models Provides details of how to combine various models to manage and trade a portfolio
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.
Alpha, higher-than-expected returns generated by an investment strategy, is the holy grail of the investment world. Achieve alpha, and you've beaten the market on a risk-adjusted basis. Quantitative Strategies for Achieving Alpha was borne from equity analyst Richard Tortoriello's efforts to create a series of quantitative stock selection models for his company, Standard & Poor's, and produce a “road map” of the market from a quantitative point of view. With this practical guide, you will gain an effective instrument that can be used to improve your investment process, whether you invest qualitatively, quantitatively, or seek to combine both. Each alpha-achieving strategy has been extensively back-tested using Standard & Poor's Compustat Point in Time database and has proven to deliver alpha over the long term. Quantitative Strategies for Achieving Alpha presents a wide variety of individual and combined investment strategies that consistently predict above-market returns. The result is a comprehensive investment mosaic that illustrates clearly those qualities and characteristics that make an investment attractive or unattractive. This valuable work contains: A wide variety of investment strategies built around the seven basics that drive future stock market returns: profitability, valuation, cash flow generation, growth, capital allocation, price momentum, and red flags (risk) A building-block approach to quantitative analysis based on 42 single-factor and nearly 70 two- and three-factor backtests, which show the investor how to effectively combine individual factors into robust investment screens and models More than 20 proven investment screens for generating winning investment ideas Suggestions for using quantitative strategies to manage risk and for structuring your own quantitative portfolios Advice on using quantitative principles to do qualitative investment research, including sample spreadsheets This powerful, data intensive book will help you clearly see what empirically drives the market, while providing the tools to make more profitable investment decisions based on that knowledge--through both bull and bear markets.
The first in-depth analysis of pairs trading Pairs trading is a market-neutral strategy in its most simple form. The strategy involves being long (or bullish) one asset and short (or bearish) another. If properly performed, the investor will gain if the market rises or falls. Pairs Trading reveals the secrets of this rigorous quantitative analysis program to provide individuals and investment houses with the tools they need to successfully implement and profit from this proven trading methodology. Pairs Trading contains specific and tested formulas for identifying and investing in pairs, and answers important questions such as what ratio should be used to construct the pairs properly. Ganapathy Vidyamurthy (Stamford, CT) is currently a quantitative software analyst and developer at a major New York City hedge fund.
A comprehensive look at the tools and techniques used in quantitative equity management Some books attempt to extend portfolio theory, but the real issue today relates to the practical implementation of the theory introduced by Harry Markowitz and others who followed. The purpose of this book is to close the implementation gap by presenting state-of-the art quantitative techniques and strategies for managing equity portfolios. Throughout these pages, Frank Fabozzi, Sergio Focardi, and Petter Kolm address the essential elements of this discipline, including financial model building, financial engineering, static and dynamic factor models, asset allocation, portfolio models, transaction costs, trading strategies, and much more. They also provide ample illustrations and thorough discussions of implementation issues facing those in the investment management business and include the necessary background material in probability, statistics, and econometrics to make the book self-contained. Written by a solid author team who has extensive financial experience in this area Presents state-of-the art quantitative strategies for managing equity portfolios Focuses on the implementation of quantitative equity asset management Outlines effective analysis, optimization methods, and risk models In today's financial environment, you have to have the skills to analyze, optimize and manage the risk of your quantitative equity investments. This guide offers you the best information available to achieve this goal.
The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.
With the immediacy of today’s NASDAQ close and the timeless power of a Greek tragedy, The Quants is at once a masterpiece of explanatory journalism, a gripping tale of ambition and hubris, and an ominous warning about Wall Street’s future. In March of 2006, four of the world’s richest men sipped champagne in an opulent New York hotel. They were preparing to compete in a poker tournament with million-dollar stakes, but those numbers meant nothing to them. They were accustomed to risking billions. On that night, these four men and their cohorts were the new kings of Wall Street. Muller, Griffin, Asness, and Weinstein were among the best and brightest of a new breed, the quants. Over the prior twenty years, this species of math whiz--technocrats who make billions not with gut calls or fundamental analysis but with formulas and high-speed computers--had usurped the testosterone-fueled, kill-or-be-killed risk-takers who’d long been the alpha males the world’s largest casino. The quants helped create a digitized money-trading machine that could shift billions around the globe with the click of a mouse. Few realized, though, that in creating this unprecedented machine, men like Muller, Griffin, Asness and Weinstein had sowed the seeds for history’s greatest financial disaster. Drawing on unprecedented access to these four number-crunching titans, The Quants tells the inside story of what they thought and felt in the days and weeks when they helplessly watched much of their net worth vaporize--and wondered just how their mind-bending formulas and genius-level IQ’s had led them so wrong, so fast.