Download or read book Decision Making with Quantitative Financial Market Data written by Alain Ruttiens and published by Springer Nature. This book was released on 2021-03-01 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use of quantitative data, especially in financial markets, may provide rapid results due to the ease-of-use and availability of fast computational software, but this book advises caution and helps to understand and avoid potential pitfalls. It deals with often underestimated issues related to the use of financial quantitative data, such as non-stationarity issues, accuracy issues and modeling issues. It provides practical remedies or ways to develop new calculation methodologies to avoid pitfalls in using data, as well as solutions for risk management issues in financial market. The book is intended to help professionals in financial industry to use quantitative data in a safer way.
Download or read book Decision Making with Quantitative Financial Market Data written by Alain Ruttiens and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use of quantitative data, especially in financial markets, may provide rapid results due to the ease-of-use and availability of fast computational software, but this book advises caution and helps to understand and avoid potential pitfalls. It deals with often underestimated issues related to the use of financial quantitative data, such as non-stationarity issues, accuracy issues and modeling issues. It provides practical remedies or ways to develop new calculation methodologies to avoid pitfalls in using data, as well as solutions for risk management issues in financial market. The book is intended to help professionals in financial industry to use quantitative data in a safer way.
Download or read book An Introduction to Financial Markets written by Paolo Brandimarte and published by John Wiley & Sons. This book was released on 2018-02-22 with total page 893 pages. Available in PDF, EPUB and Kindle. Book excerpt: COVERS THE FUNDAMENTAL TOPICS IN MATHEMATICS, STATISTICS, AND FINANCIAL MANAGEMENT THAT ARE REQUIRED FOR A THOROUGH STUDY OF FINANCIAL MARKETS This comprehensive yet accessible book introduces students to financial markets and delves into more advanced material at a steady pace while providing motivating examples, poignant remarks, counterexamples, ideological clashes, and intuitive traps throughout. Tempered by real-life cases and actual market structures, An Introduction to Financial Markets: A Quantitative Approach accentuates theory through quantitative modeling whenever and wherever necessary. It focuses on the lessons learned from timely subject matter such as the impact of the recent subprime mortgage storm, the collapse of LTCM, and the harsh criticism on risk management and innovative finance. The book also provides the necessary foundations in stochastic calculus and optimization, alongside financial modeling concepts that are illustrated with relevant and hands-on examples. An Introduction to Financial Markets: A Quantitative Approach starts with a complete overview of the subject matter. It then moves on to sections covering fixed income assets, equity portfolios, derivatives, and advanced optimization models. This book’s balanced and broad view of the state-of-the-art in financial decision-making helps provide readers with all the background and modeling tools needed to make “honest money” and, in the process, to become a sound professional. Stresses that gut feelings are not always sufficient and that “critical thinking” and real world applications are appropriate when dealing with complex social systems involving multiple players with conflicting incentives Features a related website that contains a solution manual for end-of-chapter problems Written in a modular style for tailored classroom use Bridges a gap for business and engineering students who are familiar with the problems involved, but are less familiar with the methodologies needed to make smart decisions An Introduction to Financial Markets: A Quantitative Approach offers a balance between the need to illustrate mathematics in action and the need to understand the real life context. It is an ideal text for a first course in financial markets or investments for business, economic, statistics, engineering, decision science, and management science students.
Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Download or read book The Quants written by Scott Patterson and published by Currency. This book was released on 2011-01-25 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of the Fundamentals of Financial Decision Making written by Leonard C. MacLean and published by World Scientific. This book was released on 2013 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook in two parts covers key topics of the theory of financial decision making. Some of the papers discuss real applications or case studies as well. There are a number of new papers that have never been published before especially in Part II.Part I is concerned with Decision Making Under Uncertainty. This includes subsections on Arbitrage, Utility Theory, Risk Aversion and Static Portfolio Theory, and Stochastic Dominance. Part II is concerned with Dynamic Modeling that is the transition for static decision making to multiperiod decision making. The analysis starts with Risk Measures and then discusses Dynamic Portfolio Theory, Tactical Asset Allocation and Asset-Liability Management Using Utility and Goal Based Consumption-Investment Decision Models.A comprehensive set of problems both computational and review and mind expanding with many unsolved problems are in an accompanying problems book. The handbook plus the book of problems form a very strong set of materials for PhD and Masters courses both as the main or as supplementary text in finance theory, financial decision making and portfolio theory. For researchers, it is a valuable resource being an up to date treatment of topics in the classic books on these topics by Johnathan Ingersoll in 1988, and William Ziemba and Raymond Vickson in 1975 (updated 2 nd edition published in 2006).
Download or read book Financial Decision Making Using Computational Intelligence written by Michael Doumpos and published by Springer Science & Business Media. This book was released on 2012-07-23 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.
Download or read book The Financial Mathematics of Market Liquidity written by Olivier Gueant and published by CRC Press. This book was released on 2016-03-30 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is among the first to present the mathematical models most commonly used to solve optimal execution problems and market making problems in finance. The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making presents a general modeling framework for optimal execution problems-inspired from the Almgren-Chriss app
Download or read book Quantitative Analysis in Financial Markets written by Marco Avellaneda and published by World Scientific. This book was released on 1999 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains lectures presented at the Courant Institute's Mathematical Finance Seminar.
Download or read book The Quant Trader s Handbook written by Josh Luberisse and published by Fortis Novum Mundum. This book was released on with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: In "The Quant Trader's Handbook," Josh masterfully navigates the intricate world of algorithmic trading, shedding light on its various complexities and revealing the secrets that drive the success of some of the most prominent quantitative hedge funds and traders. Through a blend of captivating storytelling and rigorous analysis, this guide offers readers an unparalleled opportunity to delve into the mechanics of quantitative trading, exploring the strategies, technologies, and practices that have transformed the financial landscape. As modern markets continue to be shaped by the silent precision of algorithms, it becomes essential for traders and investors to understand the underlying mechanics that drive these systems. This book promises to immerse its readers in the rich tapestry of the algorithmic trading realm, stretching from its nascent beginnings in the 1970s to the AI-integrated strategies of the 21st century. Inside, you'll embark on a chronological journey starting with the pioneering days of electronic stock markets and culminating in the sophisticated high-frequency trading systems of today. Alongside this, Josh takes you through the ins and outs of popular quantitative trading strategies, illustrated with intuitive pseudocode examples, like the Moving Average Crossover and the Pair Trading Strategy, ensuring even those new to the domain can grasp the nuances. But this isn't just a book about code and numbers. The Quant Trader's Handbook paints the bigger picture. With detailed network diagrams, you'll gain insights into the architectural complexity and beauty of modern trading systems, understanding how various components seamlessly intertwine to make real-time decisions in the blink of an eye. As you embark on this journey with Josh, you'll discover the foundational concepts of algorithmic trading, unravel the mysteries of quantitative analysis and modeling, and gain valuable insights into the inner workings of execution and order management. From the depths of data mining techniques to the heights of infrastructure and technology, each chapter is meticulously crafted to provide a thorough understanding of the various aspects that contribute to a successful algorithmic trading business. In addition to its wealth of practical knowledge, "The Quant Trader's Handbook" also delves into the regulatory and compliance considerations that are essential for navigating today's financial markets. With a keen eye for detail and a remarkable ability to contextualize even the most technical topics, Josh brings to life the fascinating stories of industry giants like Renaissance Technologies, DE Shaw, and Two Sigma, painting a vivid picture of the rise of quantitative finance. Whether you're an aspiring quant looking to make your mark in the world of finance, an investor trying to demystify the black box of algorithmic trading, or merely a curious soul eager to understand how bits and bytes are silently shaping the financial world, "The Quant Trader's Handbook" is an indispensable resource that will captivate, inform, and inspire you. Join Josh as he unravels the secrets of the world's most successful traders and embark on a journey that may just change the way you see the markets forever.
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 Applications of Computational Intelligence in Data Driven Trading written by Cris Doloc and published by John Wiley & Sons. This book was released on 2019-11-05 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.
Download or read book Statistical Models and Methods for Financial Markets written by Tze Leung Lai and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.
Download or read book Advanced Quantitative Finance written by William Johnson and published by HiTeX Press. This book was released on 2024-10-18 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Advanced Quantitative Finance: Trading, Risk, and Portfolio Optimization" unfolds as an essential guide for anyone eager to delve into the sophisticated world of modern finance. This comprehensive text blends theoretical underpinnings with practical insights, offering a robust exploration of the quantitative techniques driving today's markets. Each chapter systematically demystifies complex subjects—from risk management and derivatives pricing to algorithmic trading and asset pricing models—empowering readers to grasp the nuances of financial analysis with clarity and precision. Structured for both novices and seasoned professionals, the book navigates the latest advancements in machine learning, big data analytics, and behavioral finance, presenting them as indispensable tools for the contemporary financial landscape. With a focus on actionable knowledge and strategic applications, readers will gain the proficiency needed to enhance their decision-making, optimize investment portfolios, and effectively manage risk in an ever-evolving economic environment. This book is your invitation to not only understand quantitative finance but to excel in it, unlocking new levels of insight and innovation in your financial pursuits.
Download or read book Financial Market History Reflections on the Past for Investors Today written by David Chambers and published by CFA Institute Research Foundation. This book was released on with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the 2008 financial crisis, a resurgence of interest in economic and financial history has occurred among investment professionals. This book discusses some of the lessons drawn from the past that may help practitioners when thinking about their portfolios. The book’s editors, David Chambers and Elroy Dimson, are the academic leaders of the Newton Centre for Endowment Asset Management at the University of Cambridge in the United Kingdom.
Download or read book Managing Downside Risk in Financial Markets written by Frank A. Sortino and published by Butterworth-Heinemann. This book was released on 2001-10-02 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative methods have revolutionized the area of trading, regulation, risk management, portfolio construction, asset pricing and treasury activities, and governmental activity such as central banking to name but some of the applications. Downside-risk, as a quantitative method, is an accurate measurement of investment risk, because it captures the risk of not accomplishing the investor's goal. 'Downside Risk in Financial Markets' demonstrates how downside-risk can produce better results in performance measurement and asset allocation than variance modelling. Theory, as well as the practical issues involved in its implementation, is covered and the arguments put forward emphatically show the superiority of downside risk models to variance models in terms of risk measurement and decision making. Variance considers all uncertainty to be risky. Downside-risk only considers returns below that needed to accomplish the investor's goal, to be risky. Risk is one of the biggest issues facing the financial markets today. 'Downside Risk in Financial Markets' outlines the major issues for Investment Managers and focuses on "downside-risk" as a key activity in managing risk in investment/portfolio management. Managing risk is now THE paramount topic within the financial sector and recurring losses through the 1990s has shocked financial institutions into placing much greater emphasis on risk management and control. Free Software Enclosed To help you implement the knowledge you will gain from reading this book, a CD is enclosed that contains free software programs that were previously only available to institutional investors under special licensing agreement to The pension Research Institute. This is our contribution to the advancement of professionalism in portfolio management. The Forsey-Sortino model is an executable program that: 1. Runs on any PC without the need of any additional software. 2. Uses the bootstrap procedure developed by Dr. Bradley Effron at Stanford University to uncover what could have happened, instead of relying only on what did happen in the past. This is the best procedure we know of for describing the nature of uncertainty in financial markets. 3. Fits a three parameter lognormal distribution to the bootstrapped data to allow downside risk to be calculated from a continuous distribution. This improves the efficacy of the downside risk estimates. 4. Calculates upside potential and downside risk from monthly returns on any portfolio manager. 5. Calculates upside potential and downside risk from any user defined distribution. Forsey-Sortino Source Code: 1. The source code, written in Visual Basic 5.0, is provided for institutional investors who want to add these calculations to their existing financial services. 2. No royalties are required for this source code, providing institutions inform clients of the source of these calculations. A growing number of services are now calculating downside risk in a manner that we are not comfortable with. Therefore, we want investors to know when downside risk and upside potential are calculated in accordance with the methodology described in this book. Riddles Spreadsheet: 1. Neil Riddles, former Senior Vice President and Director of Performance Analysis at Templeton Global Advisors, now COO at Hansberger Global Advisors Inc., offers a free spreadsheet in excel format. 2. The spreadsheet calculates downside risk and upside potential relative to the returns on an index Brings together a range of relevant material, not currently available in a single volume source. Provides practical information on how financial organisations can use downside risk techniques and technological developments to effectively manage risk in their portfolio management. Provides a rigorous theoretical underpinning for the use of downside risk techniques. This is important for the long-run acceptance of the methodology, since such arguments justify consultant's recommendations to pension funds and other plan sponsors.
Download or read book Investor Decision Making and the Role of the Financial Advisor written by Caterina Cruciani and published by Springer. This book was released on 2017-11-13 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book looks at financial advisory from a behavioural perspective, and focuses on how the nature of the relationship between advisors and clients may affect the ability of the advisor to perform its functions. Broken into three key parts, the book looks at the client, the advisor, and the relationship between the two. Chapters review relevant theories of decision-making under risk to understand the nature of clients’ decisions. The literature on advisors’ functions and the normative landscape regulating financial advisory are also addressed. Finally, this book reviews how behavioural finance has traditionally addressed portfolio selection and explains how trust can be seen as a viable avenue to maximize advisors’ effectiveness and pursue clients’ needs. This book will be of interest to both behavioural finance scholars and practitioners interested in understanding what the future of financial advisory may have in stock.
