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Financial Modeling, Actuarial Valuation and Solvency in Insurance
by Mario V. Wüthrich Michael MerzRisk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there are many new developments in this area in the financial and insurance industry (Basel III and Solvency II), but none of these developments provides a fully consistent and comprehensive framework for the analysis of solvency questions. Merz and Wüthrich combine ideas from financial mathematics (no-arbitrage theory, equivalent martingale measure), actuarial sciences (insurance claims modeling, cash flow valuation) and economic theory (risk aversion, probability distortion) to provide a fully consistent framework. Within this framework they then study solvency questions in incomplete markets, analyze hedging risks, and study asset-and-liability management questions, as well as issues like the limited liability options, dividend to shareholder questions, the role of re-insurance, etc. This work embeds the solvency discussion (and long-term liabilities) into a scientific framework and is intended for researchers as well as practitioners in the financial and actuarial industry, especially those in charge of internal risk management systems. Readers should have a good background in probability theory and statistics, and should be familiar with popular distributions, stochastic processes, martingales, etc.
Financial Modelling with Jump Processes (Chapman and Hall/CRC Financial Mathematics Series)
by Rama Cont Peter TankovWINNER of a Riskbook.com Best of 2004 Book Award!During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematic
Financial Models in Production (SpringerBriefs in Finance)
by Adil Reghai Othmane KettaniThis book provides a hands-on guide to how financial models are actually implemented and used in practice, on a daily basis, for pricing and risk-management purposes. It shows how to put these models into use in production while minimizing the cost of implementation and maximizing robustness and control. Addressing some of the most important and cutting-edge issues, it describes how to build the necessary models in order to risk manage all the costs involved in options fabrication within the world of equity derivatives and hybrids. This is achieved by extending classical models and improving them in order to account for complex features. The book is primarily aimed at market practitioners (traders, risk managers, risk control, top managers), as well as Masters students in Quantitative/Mathematical Finance. It will also be useful for instructors hoping to enrich their courses with practical examples. The prerequisites are basic stochastic calculus and a general knowledge of financial markets and financial derivatives.
Financial Numeracy in Mathematics Education: Research and Practice (Mathematics Education in the Digital Era #15)
by Annie Savard Alexandre CavalcanteThis book presents the important role of mathematics in the teaching of financial education. Through a conceptualization of financial numeracy as a social practice, it focuses on the teaching practices, resources, and needs of secondary mathematics teachers (grades 7-12) to incorporate financial concepts in their classes. The editors and authors bring forth a novel perspective regarding mathematics education in the digital era. By focusing on financial numeracy, a key component of skills required in the digital era, they discuss important issues related to the teaching and learning of mathematics and finance. In contrary to most research in the field of financial education coming from scholars in areas such as business, accounting, management and economics, this book introduces the contribution of researchers from the field of education to the debate. The book appeals to an international audience composed of researchers, stakeholders, policymakers, teachers, and teacher educators.
Financial Risk Management and Modeling (Risk, Systems and Decisions)
by Constantin Zopounidis Ramzi Benkraiem Iordanis KalaitzoglouRisk is the main source of uncertainty for investors, debtholders, corporate managers and other stakeholders. For all these actors, it is vital to focus on identifying and managing risk before making decisions. The success of their businesses depends on the relevance of their decisions and consequently, on their ability to manage and deal with the different types of risk. Accordingly, the main objective of this book is to promote scientific research in the different areas of risk management, aiming at being transversal and dealing with different aspects of risk management related to corporate finance as well as market finance. Thus, this book should provide useful insights for academics as well as professionals to better understand and assess the different types of risk.
Financial Risk Management for Cryptocurrencies (SpringerBriefs in Finance)
by Wim Schoutens Lucia Alessi Eline Van der Auwera Marco Petracco GiudiciThis book explores the emerging field of risk management and risk analysis of cryptocurrencies, an area that has been generating considerable research. It begins by providing an introduction to digital finance and the concept of cryptocurrencies and blockchain technologies. It then describes in detail the intrinsic risks involved in cryptocurrencies, an area that, to date, has not been fully documented or investigated. Lastly, it discusses the various types of risk, with a focus on design, operational, market and quantitative risks.Providing insights into the analysis and management of cryptocurrencies, and serving as a starting point for a more in-depth risk analysis, this book will appeal to professionals and researchers interested in familiarizing themselves with the risks in cryptocurrencies, including academics, portfolio managers, risk-managers, quants, financial professionals, regulators, economists, asset managers and traders.
Financial Risk Modelling and Portfolio Optimization with R
by Bernhard PfaffIntroduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book.Financial Risk Modelling and Portfolio Optimization with R:Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field.Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies.Explores portfolio risk concepts and optimization with risk constraints.Enables the reader to replicate the results in the book using R code.Is accompanied by a supporting website featuring examples and case studies in R.Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Financial Risk Modelling and Portfolio Optimization with R (Statistics in Practice)
by Bernhard PfaffIntroduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Enables the reader to replicate the results in the book using R code. Is accompanied by a supporting website featuring examples and case studies in R. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Financial Software Engineering (Undergraduate Topics in Computer Science)
by Kevin Lano Howard HaughtonIn this textbook the authors introduce the important concepts of the financial software domain, and motivate the use of an agile software engineering approach for the development of financial software. They describe the role of software in defining financial models and in computing results from these models. Practical examples from bond pricing, yield curve estimation, share price analysis and valuation of derivative securities are given to illustrate the process of financial software engineering.Financial Software Engineering also includes a number of case studies based on typical financial engineering problems:*Internal rate of return calculation for bonds* Macaulay duration calculation for bonds* Bootstrapping of interest rates* Estimation of share price volatility* Technical analysis of share prices* Re-engineering Matlab to C#* Yield curve estimation* Derivative security pricing* Risk analysis of CDOs The book is suitable for undergraduate and postgraduate study, and for practitioners who wish to extend their knowledge of software engineering techniques for financial applications
Financial Statements-Based Bank Risk Aggregation (Innovation in Risk Analysis)
by Jianping Li Lu Wei Xiaoqian ZhuThis book proposes a bank risk aggregation framework based on financial statements. Specifically, bank risk aggregation is of great importance to maintain stable operation of banking industry and prevent financial crisis. A major obstacle to bank risk management is the problem of data shortage, which makes many quantitative risk aggregation approaches typically fail. Recently, to overcome the problem of inaccurate total risk results caused by the shortage of risk data, some researchers have proposed a series of financial statements-based bank risk aggregation approaches. However, the existing studies have drawbacks of low frequency and time lag of financial statements data and usually ignore off-balance sheet business risk in bank risk aggregation. Thus, by reviewing the research progress in bank risk aggregation based on financial statements and improving the drawbacks of existing methods, this book proposes a bank risk aggregation framework based on financial statements. It makes full use of information recorded in financial statements, including income statement, on- and off-balance sheet assets, and textual risk disclosures, which solves the problem of data shortage in bank risk aggregation to some extent and improves the reliability and rationality of bank risk aggregation results. This book not only improves the theoretical studies of bank risk aggregation, but also provides an important support for the capital allocation of the banking industry in practice. Thus, this book has theoretical and practical importance for bank managers and researchers of bank risk management.
Financial Statistics and Mathematical Finance: Methods, Models and Applications
by Ansgar StelandMathematical finance has grown into a huge area of research which requires a lot of care and a large number of sophisticated mathematical tools. Mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, it considers various aspects of the application of statistical methods in finance and illustrates some of the many ways that statistical tools are used in financial applications.Financial Statistics and Mathematical Finance:Provides an introduction to the basics of financial statistics and mathematical finance.Explains the use and importance of statistical methods in econometrics and financial engineering.Illustrates the importance of derivatives and calculus to aid understanding in methods and results.Looks at advanced topics such as martingale theory, stochastic processes and stochastic integration.Features examples throughout to illustrate applications in mathematical and statistical finance.Is supported by an accompanying website featuring R code and data sets.Financial Statistics and Mathematical Finance introduces the financial methodology and the relevant mathematical tools in a style that is both mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, both graduate students and researchers in statistics, finance, econometrics and business administration will benefit from this book.
Financial Technology: 5th International Conference, ICFT 2024, Singapore, September 23–25, 2024, Proceedings (Communications in Computer and Information Science #2437)
by Qi Cao Ruidan Su Ke-Wei HuangThis book constitutes the proceedings of the 5th International Conference on Financial Technology, ICFT 2024, held in Singapore during September 23–25, 2024. The 17 full papers presented in this volume were carefully reviewed and selected from 35 submissions. These papers focus on the current research in Blockchain technology, Financial technology and the application of Artificial Intelligence in these areas.
Financial Technology: Proceedings of The International Conference on Business and Technology (ICBT 2021) (Lecture Notes in Networks and Systems #486)
by Allam Hamdan Bahaaeddin AlareeniThis book constitutes the refereed proceedings of the International Conference on Business and Technology (ICBT2021) organized by EuroMid Academy of Business & Technology (EMABT), held in Istanbul, between 06–07 November 2021. In response to the call for papers for ICBT2021, 485 papers were submitted for presentation and inclusion in the proceedings of the conference. After a careful blind refereeing process, 292 papers were selected for inclusion in the conference proceedings from forty countries. Each of these chapters was evaluated through an editorial board, and each chapter was passed through a double-blind peer-review process.The book highlights a range of topics in the fields of technology, entrepreneurship, business administration, accounting, and economics that can contribute to business development in countries, such as learning machines, artificial intelligence, big data, deep learning, game-based learning, management information system, accounting information system, knowledge management, entrepreneurship, and social enterprise, corporate social responsibility and sustainability, business policy and strategic management, international management and organizations, organizational behavior and HRM, operations management and logistics research, controversial issues in management and organizations, turnaround, corporate entrepreneurship, innovation, legal issues, business ethics, and firm governance, managerial accounting and firm financial affairs, non-traditional research, and creative methodologies.These proceedings are reflecting quality research contributing theoretical and practical implications, for those who are wise to apply the technology within any business sector. It is our hope that the contribution of this book proceedings will be of the academic level which even decision-makers in the various economic and executive-level will get to appreciate.
Financial and Actuarial Statistics: An Introduction, Second Edition
by Dale S. Borowiak Arnold F. ShapiroUnderstand Up-to-Date Statistical Techniques for Financial and Actuarial ApplicationsSince the first edition was published, statistical techniques, such as reliability measurement, simulation, regression, and Markov chain modeling, have become more prominent in the financial and actuarial industries. Consequently, practitioners and students must ac
Financial and Insurance Formulas
by Tomas CipraThis survey contains more than 3,000 formulas and methods from the field of finance and insurance mathematics (as well as related formulas in mathematics, probability theory, statistics, econometrics, index numbers, demography, stochastic processes and time series). The formulas are mostly applicable in financial and actuarial practice. Their mathematical level ranges from simple ones based on arithmetic to very sophisticated matters of higher mathematics (e. g. stochastic calculus), but they are usually presented in the form most frequently used in applications. Explanations and references to related parts of the survey are given so that one can easily browse and look them up in the text; the detailed Index is also helpful for this purpose. The survey will be of benefit for students, researchers and practitioners in finance and insurance.
Financial and Managerial Accounting (Seventeenth Edition)
by Jan Williams Joseph Carcello Mark Bettner Susan HakaWith the seventeenth edition of Financial and Managerial Accounting: The Basis for Business Decisions, the Williams author team continues to be a solid foundation for students who are learning basic accounting concepts. Hallmarks of the text - including the solid Accounting Cycle Presentation, relevant pedagogy, and high quality, end-of-chapter material--have been updated throughout the book.
Finanzierung und Finanzmanagement: Lehr- Und Übungsbuch Für Das Master-studium
by Thomas Schuster Margarita UskovaDas Buch bietet eine sehr praxisorientierte und vertiefte Darstellung eines Unternehmens. Nach einem kurzen Überblick über die Grundlagen des Finanzmanagements lernt der Leser die Einzelheiten der Beteiligungs-, Fremd- und Innenfinanzierung kennen. Außerdem werden Finanzderivate wie zum Beispiel Optionen und Forward Rate Agreements dargestellt. Ein Kapitel über alternative Finanzierungsinstrumente, beispielsweise Factoring oder Leasing, runden das Lehrbuch ab. In jedem Kapitel führt ein Fallbeispiel in das Wissensgebiet ein. Die einzelnen Themen werden anschaulich durch viele Praxisbeispiele illustriert. Lernkontrollaufgaben dienen der Absicherung, dass der Leser den gelernten Stoff gut verstanden hat. Es handelt sich um ein sehr modernes Lehrbuch mit der konsequenten Verbindung von Theorie, Praxisbeispielen und vertiefenden Übungsaufgaben. Studierende finden zusätzliche Übungsaufgaben und Lösungen auf der Internetseite des Verlags. Für Lehrende werden weitere Materialien – bespielsweise PowerPoint-Folien und Klausuren – auf der Springer-Seite DozentenPLUS bereitgestellt. Das Buch wendet sich an Master-Studierende mit wirtschaftswissenschaftlichem Schwerpunkt, MBA-Studierende sowie an Praktiker in Finanzabteilungen von Unternehmen.
Finanzmathematik in diskreter Zeit
by Ulrich Rieder Nicole BäuerleDieses Lehrbuch bietet eine leicht verständliche Einführung in die moderne Finanzmathematik und erläutert grundlegende mathematische Konzepte der Optionsbewertung, der Portfolio-Optimierung und des Risikomanagements. Hierzu gehören die Preisbestimmung durch Arbitrageüberlegungen, die Preisbestimmung von amerikanischen Optionen über die Lösung optimaler Stopp-Probleme, die Bestimmung von optimalen Konsum- und Investitionsstrategien und Erwartungswert-Varianz Portfolios. Aktuelle Konzepte der Risikomessung wie Value at Risk und Expected Shortfall werden ebenso vorgestellt.Grundlagen in Stochastik und Optimierung reichen für das Verständnis der Inhalte aus und zahlreiche Übungsaufgaben mit ausführlichen Lösungen sowie drei Anhänge erleichtern das Selbststudium.
Finanzmathematik: Eine Einführung für Mathematik, Wirtschaftswissenschaften und Praxis
by Christian Weiß Thomas Skill Dennis HeitmannBei der Anwendung finanzmathematischer Modelle im beruflichen Alltag ist es ein entscheidender Erfolgsfaktor, die Verknüpfung von Theorie und Praxis zu verstehen. Dieses Buch verbindet daher die Präsentation der Theorie hinter den zentralen Themen der Finanzmathematik durchgehend mit vielen Beispielen aus einem konkreten Anwendungsfeld. Dabei bringen die Autoren fortwährend ihre langjährigen Erfahrungen als Berufstätige in der Finanzbranche und als Wissenschaftler ein. In besonderer Weise richtet sich dieses Buch dadurch an Studierende der Mathematik, der Betriebs- und der Volkswirtschaftslehre, die sich für einen Schwerpunkt in Finanzmärkten und Anlagestrategien interessieren. Ergänzt wird die klare und verständliche Darstellung durch mehr als 60 Aufgaben inklusive Lösungen, die auch als Onlineressourcen in Excel umgesetzt und verfügbar sind. Damit keine weitere Literatur zu erforderlichen Vorkenntnissen herangezogen werden muss, sind in einem Anhang die notwendigen Grundlagen aus der Wirtschaftsmathematik und Statistik in kompakter und übersichtlicher Form zusammengefasst, sodass das vorliegende Buch auch für das Selbststudium hervorragend genutzt werden kann. Dadurch ist es ebenfalls im hohen Maße für Berufstätige aus der Praxis geeignet, die einen Hintergrund in den Wirtschaftswissenschaften oder der Mathematik mitbringen und auf der Suche nach einer anschaulichen und praxisorientierten Einführung sind oder ihr Wissen auffrischen möchten.
Finanzmathematik: Zins-, Renten- und Tilgungsrechnung verstehen (Studienbücher Wirtschaftsmathematik Ser.)
by Bernd KuppingerDie Finanzmathematik ist unter Wirtschaftswissenschaftlern nicht immer beliebt. Sie gilt als kompliziert und recht lernintensiv. Bernd Kuppinger will Ihnen in diesem Buch zeigen, dass das nicht so sein muss. Er erklärt Ihnen so verständlich wie möglich, was Sie über Zins-, Renten- und Tilgungsrechnung wissen müssen. Er gibt eine Einführung in die Investitionsrechnung und bringt Ihnen in einem eigenen Teil auch noch das mathematische Handwerkszeug näher, das Sie brauchen, um in der Finanzmathematik zu bestehen. Viele Beispiele helfen Ihnen, den Bezug zur Praxis herzustellen, und mit den zahlreichen Übungsaufgaben können Sie Ihr Wissen festigen und testen.
Finding Communities in Social Networks Using Graph Embeddings (Lecture Notes in Social Networks)
by David B. Skillicorn Mosab AlfaqeehCommunity detection in social networks is an important but challenging problem. This book develops a new technique for finding communities that uses both structural similarity and attribute similarity simultaneously, weighting them in a principled way. The results outperform existing techniques across a wide range of measures, and so advance the state of the art in community detection. Many existing community detection techniques base similarity on either the structural connections among social-network users, or on the overlap among the attributes of each user. Either way loses useful information. There have been some attempts to use both structure and attribute similarity but success has been limited. We first build a large real-world dataset by crawling Instagram, producing a large set of user profiles. We then compute the similarity between pairs of users based on four qualitatively different profile properties: similarity of language used in posts, similarity of hashtags used (which requires extraction of content from them), similarity of images displayed (which requires extraction of what each image is 'about'), and the explicit connections when one user follows another. These single modality similarities are converted into graphs. These graphs have a common node set (the users) but different sets a weighted edges. These graphs are then connected into a single larger graph by connecting the multiple nodes representing the same user by a clique, with edge weights derived from a lazy random walk view of the single graphs. This larger graph can then be embedded in a geometry using spectral techniques. In the embedding, distance corresponds to dissimilarity so geometric clustering techniques can be used to find communities. The resulting communities are evaluated using the entire range of current techniques, outperforming all of them. Topic modelling is also applied to clusters to show that they genuinely represent users with similar interests. This can form the basis for applications such as online marketing, or key influence selection.
Finding Fibonacci: The Quest to Rediscover the Forgotten Mathematical Genius Who Changed the World
by Keith DevlinIn 2000, Keith Devlin set out to research the life and legacy of the medieval mathematician Leonardo of Pisa, popularly known as Fibonacci, whose book Liber abbaci has quite literally affected the lives of everyone alive today. Although he is most famous for the Fibonacci numbers—which, it so happens, he didn't invent—Fibonacci's greatest contribution was as an expositor of mathematical ideas at a level ordinary people could understand. In 1202, Liber abbaci—the "Book of Calculation"—introduced modern arithmetic to the Western world. Yet Fibonacci was long forgotten after his death, and it was not until the 1960s that his true achievements were finally recognized.Finding Fibonacci is Devlin's compelling firsthand account of his ten-year quest to tell Fibonacci's story. Devlin, a math expositor himself, kept a diary of the undertaking, which he draws on here to describe the project's highs and lows, its false starts and disappointments, the tragedies and unexpected turns, some hilarious episodes, and the occasional lucky breaks. You will also meet the unique individuals Devlin encountered along the way, people who, each for their own reasons, became fascinated by Fibonacci, from the Yale professor who traced modern finance back to Fibonacci to the Italian historian who made the crucial archival discovery that brought together all the threads of Fibonacci's astonishing story.Fibonacci helped to revive the West as the cradle of science, technology, and commerce, yet he vanished from the pages of history. This is Devlin's search to find him.
Finding Fractals
by Amy TaoHave you ever seen a fractal? You probably have, and just didn’t know it! These repeating shapes can happen anywhere, whether in nature or in math—it’s easy to make one out of a series of lines and triangles! Follow along and make a fractal of your own in a fun craft.
Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python
by Kevin FeaselDiscover key information buried in the noise of data by learning a variety of anomaly detection techniques and using the Python programming language to build a robust service for anomaly detection against a variety of data types. The book starts with an overview of what anomalies and outliers are and uses the Gestalt school of psychology to explain just why it is that humans are naturally great at detecting anomalies. From there, you will move into technical definitions of anomalies, moving beyond "I know it when I see it" to defining things in a way that computers can understand.The core of the book involves building a robust, deployable anomaly detection service in Python. You will start with a simple anomaly detection service, which will expand over the course of the book to include a variety of valuable anomaly detection techniques, covering descriptive statistics, clustering, and time series scenarios. Finally, you will compare your anomaly detection service head-to-head with a publicly available cloud offering and see how they perform.The anomaly detection techniques and examples in this book combine psychology, statistics, mathematics, and Python programming in a way that is easily accessible to software developers. They give you an understanding of what anomalies are and why you are naturally a gifted anomaly detector. Then, they help you to translate your human techniques into algorithms that can be used to program computers to automate the process. You’ll develop your own anomaly detection service, extend it using a variety of techniques such as including clustering techniques for multivariate analysis and time series techniques for observing data over time, and compare your service head-on against a commercial service.What You Will LearnUnderstand the intuition behind anomaliesConvert your intuition into technical descriptions of anomalous dataDetect anomalies using statistical tools, such as distributions, variance and standard deviation, robust statistics, and interquartile rangeApply state-of-the-art anomaly detection techniques in the realms of clustering and time series analysisWork with common Python packages for outlier detection and time series analysis, such as scikit-learn, PyOD, and tslearnDevelop a project from the ground up which finds anomalies in data, starting with simple arrays of numeric data and expanding to include multivariate inputs and even time series dataWho This Book Is ForFor software developers with at least some familiarity with the Python programming language, and who would like to understand the science and some of the statistics behind anomaly detection techniques. Readers are not required to have any formal knowledge of statistics as the book introduces relevant concepts along the way.
Finding Zero: A Mathematician's Odyssey to Uncover the Origins of Numbers
by Amir D. Aczel“A captivating story, not just an intellectual quest but a personal one . . . gripping [and] filled with the passion and wonder of numbers.” —The New York TimesVirtually everything in our lives is digital, numerical, or quantified. But the story of how and where we got these numerals, which we so depend on, has for thousands of years been shrouded in mystery. Finding Zero is the saga of Amir Aczel’s lifelong obsession: to find the original sources of our numerals, perhaps the greatest abstraction the human mind has ever created.Aczel has doggedly crisscrossed the ancient world, scouring dusty, moldy texts, cross-examining so-called scholars who offered wildly differing sets of facts, and ultimately penetrating deep into a Cambodian jungle to find a definitive proof. Here, he takes the reader along for the ride.The history begins with Babylonian cuneiform numbers, followed by Greek and Roman letter numerals. Then Aczel asks: Where do the numbers we use today, the so-called Hindu-Arabic numerals, come from? It is this search that leads him to explore uncharted territory on a grand quest into India, Thailand, Laos, Vietnam, and ultimately into the wilds of Cambodia. There he is blown away to find the earliest zero—the keystone of our entire system of numbers—on a crumbling, vine-covered wall of a seventh-century temple adorned with eaten-away erotic sculptures.While on this odyssey, Aczel meets a host of fascinating characters: academics in search of truth, jungle trekkers looking for adventure, surprisingly honest politicians, shameless smugglers, and treacherous archaeological thieves—who finally reveal where our numbers come from.“A historical adventure that doubles as a surprisingly engaging math lesson . . . rip-roaring exploits and escapades.” —Publishers Weekly