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Johnson W: Quantitative Finance

Quantitative Finance

Mastering Mathematical Models for Market Success

Wiley Finance

PRAISE FOR FINANCIAL DATA ANALYTICS "Really interesting, and an impressive masterpiece! Financial Data Analytics contains a rich amount of material, with original research findings in almost every chapter; many parts of the book will even be directly helpful for my own teaching in business school. In view of its dedication towards data-driven analytical tools genuinely needed in financial problems, I believe that it is the very book that defines the scope of financial data analytics." -Alain Bensoussan, Fellow of AMS, IEEE, and SIAM; President of INRIA (1984-1996); President of CNES (Centre National d'Etudes Spatiales) (1996-2003); Chairman of ESA Council (European Space Agency) (1999-2002); Former Member of Advisory Board, Mathematical Finance; Lars Magnus Ericsson Chair Professor of Management, Naveen Jindal School of Management, University of Texas at Dallas "Financial Data Analytics is an exceptional book that integrates mathematics, practical examples, and real-life scenarios. With its focus on real datasets and practical programming codes in Python and R, the book offers a comprehensive exploration of various topics. It presents novel research findings and provides valuable insights for researchers, practitioners, and actuarial students. The book strikes a balance between foundational concepts and advanced techniques, making it an invaluable reference for professionals in the field ... By redefining the landscape of financial data analytics in FinTech and InsurTech, this book establishes itself as a trusted guide in the industry." - Simon Lam, Fellow of SOA, CFA, FRM; President of The Actuarial Society of Hong Kong (2018, 2023); Deputy CEO &amp; General Manager, Munich Re (Hong Kong) "The book will certainly play an impactful role in the advancement of financial analytics and should be on the bookshelf of every serious student of the topic." - Wai Keung Li, Fellow of Am. Stat. Assoc. and Inst. Math. Stat.; Emeritus Professor, The University of Hong Kong; Dean, Faculty of Liberal Arts and Social Sciences, The Education University of Hong Kong "... The dual focus on theory and applications, together with the discussion on recent advancements of the fields, makes the book one of a kind, even field-defining, among books on similar topics, and an ideal resource for anyone interested in understanding and implementing statistical models in this era of big data, as well as for students preparing for professional examinations on data analytics, such as the SRM, PA and ATPA exams of the Society of Actuaries." - Ambrose Lo, Fellow of SOA, Chartered Enterprise Risk Analyst; Author of ACTEX Study Manual for SOA Exam SRM, ACTEX Study Manual for SOA Exam PA, and ACTEX Study Manual for SOA Exam ATPA "... Financial Data Analytics is one comprehensive biblical handbook for academic researchers, financial practitioners, and graduate students for both methodologies and applications. The book also lays a systematic framework for future extension and enrichment for financial data analytics." - Nai-pan Tang, Former Chief Risk Officer and Member of Executive Committee, Hang Seng Bank; Former Deputy CEO and Chief Risk Officer, Shanghai Commercial Bank Ltd.; Former Director of the Board, Deputy CEO, Alternative CEO, Chief Risk Officer, and Vice Chairman of Asset Management, China CITIC Bank International; Director, The Hong Kong Institute of Bankers (2019-2021); Professor of Practice, Department of Finance, Chinese University of Hong Kong

Financial Data Analytics with Machine Learning, Optimization and Statistics

Dieses Lehrbuch stellt die wesentlichen Methoden und Anwendungsgebiete der Künstlichen Intelligenz und der Analyse großer Datenmengen bei Finanzintermediären und Industrieunternehmen im Bereich der Finanzwirtschaft dar. Es&nbsp;vermittelt die Grundlagen und fortgeschrittene Methoden der KI und ihrer Anwendungen in der Finanzwirtschaft und&nbsp;unterstützt bei der Vorbereitung auf das Berufsleben im quantitativen Asset- und Risikomanagement. Das Buch kann begleitend zu universitären Lehrveranstaltungen im Bereich Financial Data Analytics, Risiko- und Investmentmanagement benutzt werden.

Daten, Methoden und Anwendungen

Künstliche Intelligenz in der Finanzwirtschaft

Springer Nature Proceedings excluding Computer Science

&lt;p&gt;This book focuses on selected aspects of the current and upcoming trends in transportation, logistics, and decision-making. In detail, the included transportation management, optimization and management of logistics system, big data technology and method, financial engineering and risk management, investment decision and risk management, data-driven process management decision, scheduling optimization and combination decision, theory and method of forecasting and decision-making, data mining and knowledge management, operation and green&amp;nbsp; supply chain management, industrial engineering and operation management, information system and business intelligence, Internet + green manufacturing, strategic emerging industries and industrial finance, big data, and smart city. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium “The Eleventh International Forum on Decision Sciences,” which took place in Qingdao, Shandong Province, China.&amp;nbsp;&lt;br&gt;&lt;/p&gt;

Xiang Li

Xiaofeng Xu

Proceedings of the Eleventh International Forum on Decision Sciences

Derivatives: Mathematical Foundations for Finance Students is written for students of finance and actuarial science who want to understand derivatives not just as formulas but as ideas that make sense. The goal is to build the mathematical foundations up step by step - starting from the familiar territory of first-year undergraduate probability and statistics and moving all the way to stochastic calculus and the principles of risk-neutral pricing, which form the heart of modern financial mathematics.This text will enable the reader to:¿ understand models of asset price behavior and apply stochastic calculus ¿ use stochastic simulations in R to investigate processes and price options ¿ price options with the binomial model ¿ derive solutions to the Black-Scholes equation using risk-neutral pricing ¿ price interest-rate derivatives using Black's model, short-rate models and the Heath-Jarrow-Morton (HJM) framework ¿ tackle quantitative finance exam questions.It incorporates a range of learning features to aid student understanding, including boxed examples, end-of-chapter summaries, selected questions from Society of Actuaries (US) Quantitative Finance examinations and further reading suggestions. The book is also supported by a suite of digital learning resources, including PowerPoint slides, multiple choice questions, instructor manual/advice document for lecturers and a test bank.This book will appeal to both undergraduate and postgraduate students who wish to understand the principles of stochastic calculus and option pricing.

Mathematical Foundations for Finance Students

Derivatives

Studienarbeit aus dem Jahr 2020 im Fachbereich BWL - Rechnungswesen, Bilanzierung, Steuern, Note: 1,0, Ernst-Moritz-Arndt-Universität Greifswald (Rechts- und Staatswissenschaftlichen Fakultät), Veranstaltung: Seminar zu Portofolio- und Risikomanagement, Sprache: Deutsch, Abstract: Im Rahmen des modernen Risikomanagements ist die Verarbeitung vieler korrelierender Einzelrisiken von Bedeutung. Die Copula-Theorie beschäftigt sich mit diesem Problem und ist Hauptgegenstand der vorliegenden Arbeit. Zunächst werden in Kapitel 2 mathematische Grundannahmen und Definitionen aufgezeigt, die auf den Arbeiten von Sklar und Fréchet-Hoeffding basieren. Im darauffolgenden Kapitel 3 werden die fundamentalen Copulas beschrieben, welche die verschiedenen Abhängigkeitsstrukturen modellieren. Kapitel 4 behandelt die Tail-Abhängigkeiten, bei denen die Verhaltensweisen der Copula-Funktionen an den äußeren Rändern definiert werden. Kapitel 5 betrachtet besonders wichtige Copula-Funktionen und ordnet diese der elliptischen und archimedischen Klasse zu. Dabei werden die in den vorherigen Kapiteln definierten Regeln und Eigenschaften auf spezielle Fälle angewendet. Abschließend werden die Erkenntnisse der Arbeit im Fazit zusammengefasst, wobei auch Kritik an Copula-Modellen angeführt wird. Hauptziel dieser Arbeit ist es, ein generelles Verständnis über die Copula-Theorie zu erlangen.

Copula-Theorie und Tail-Dependence im modernen Risikomanagement. Grundlagen, Typen und Anwendungen

"Written by a veteran Wall Street Journal reporter, this is a fascinating deep dive into the world of billion-dollar traders and high-stakes crisis predictors who strive to turn extreme events into financial windfalls. There's no doubt that our world has gotten more extreme. Pandemics, climate change, superpower rivalries, cyberattacks, political radicalization--virtually, everywhere we look there is mayhem bearing down on us, putting trillions of assets at risk." --

How Wall Street Traders Make Billions in the New Age of Crisis

Chaos Kings

This book is a short monograph on using mathematics in a basic financial model: cash flows. With cash flows, this book covers financial literacy topics including time value of money, interest rates, NPV and IRR, calculation of rate of return, and utility theory. The rest of the book covers financial engineering topics, including Asset-Back Securities, Mortgage-Back Securities, NPV and IRR for uncertain cash flows, valuation of financial instruments based on cash flows, hedging strategies for derivatives pricing, and optimization involving cash flows. Primarily suitable for self-learners, especially those with a strong quantitative background, to get into the finance field, this book includes all suggested solutions to problems, mainly arising from the practical area of finance.

Mathematics of Cash Flows

Professional and Applied Computing (R0)

Paramjit Parmar

A Practical Guide to Solving Analytical Problems

Functional Programming in Financial Markets

Mathematics and Statistics (R0)

Syouji Nakamura

Katsushige Sawaki

Toshio Nakagawa

Including Applications to Reliability Models

Probability and Statistical Models in Operations Research, Computer and Management Sciences

As seen on Steven Bartlett's THE DIARY OF A CEO

The Making of a Permabear

Studienarbeit aus dem Jahr 2024 im Fachbereich BWL - Investition und Finanzierung, Note: 2,0, FernUniversität Hagen (Lehrstuhl für Betriebswirtschaftslehre, insbesondere Bank- und Finanzwirtschaft), Veranstaltung: Financial Engineering, Sprache: Deutsch, Abstract: Die Arbeit befasst sich mit Bonus-Zertifikaten, die mit einem Markvolumen von etwa 1,3 Milliarden Euro im Bereich der strukturierten Wertpapiere vertreten sind. Für Bonus-Zertifikate gibt es keine allgemeinen Bewertungsformeln, da diese häufig aus einem Zero-Strike-Call und einer Down-and-out-Put-Option gebildet werden. Demnach reicht es aus, diese einzelnen Elemente zu bewerten, um den Gesamtwert zu erhalten. Aus diesem Grund werden die Barrier-Optionen, welche unabdingbar für die Bewertung von Bonus-Zertifikaten sind, dargestellt, um anschließend  unter anderem anhand des Black-Scholes-Modells und der Monte-Carlo-Simulation die Bewertung eines fiktiven Bonus-Zertifikats vorzunehmen.

Ziel dieser Arbeit ist es demnach, das Finanzprodukt "Bonus-Zertifikat" und dessen Bewertung zu beschreiben und anhand einer Sensitivitätsanalyse zu erklären.

Florian Betz

Bewertung von Bonus-Zertifikaten. Monte-Carlo Simulation und Reiner-Rubinstein-Formeln

The work carried out in many financial institutions has demonstrated that successful trading operations can be built using functional programming. However, there remains an entry barrier due to the lack of practical knowledge required to apply these techniques effectively. This book lowers that barrier by offering accessible insights that are enriched with real-world expertise.
While functional programming has been around for many decades, its benefits have become increasingly apparent in more recent years. This is due to a variety of factors, including advancements in processing speeds, the growth in the use of distributed computing, and the availability of functional programming languages on platforms which are popular in finance - particularly .NET and JVM.
The opening chapters introduce the fundamental concepts in functional programming and illustrate how these concepts are used in solving problems in the fixed income markets. As your understanding deepens, later chapters explore increasingly complex examples in areas such as valuation, risk analysis, hedging, and deal automation. The concluding chapters examine common programming patterns that arise across the solutions, including those influenced by category theory, such as functors, semigroups, monoids, and monads. At each stage, the book presents carefully selected algorithms to reinforce the practical understanding of the solutions.
In the end, this book provides an accessible introduction to the use of functional programming in the financial markets by bridging the gap between the theory of functional programming and its practical application in areas of finance.

What You Will Learn 

Develop functions for performing common financial market operations, such as valuing financial assets, calculating risks, hedging those risks, and automating buy/sell decisions.

Use functional programming to extract business insights from large datasets using numerical and statistical techniques. 

Effectively apply various functional programming features, such as recursion, higher-order functions, and list processing, in creating these solutions




Who This Book Is For
Aspiring professionals entering the financial markets; professional software engineers seeking a deeper understanding of how functional programming is utilized in modern capital markets; and finance professionals (including traders, risk managers, and other business users) who want to grasp the implementation details behind the "black box" tools they rely on in their day to day lives.

Quantitative Finance

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