Book picks similar to
Stochastic Calculus Models for Finance II: Continuous Time Models (Springer Finance) by Steven E. Shreve
finance
mathematics
quant
textbooks
The Analysis and Use of Financial Statements
Gerald I. White - 1993
* An increased international focus with more coverage of IASC and non-US GAAPs and more non-US examples.
The Strategy of Conflict
Thomas C. Schelling - 1960
It proposes enlightening similarities between, for instance, maneuvering in limited war and in a traffic jam; deterring the Russians and one's own children; the modern strategy of terror and the ancient institution of hostages.
Linear Algebra
Kenneth M. Hoffman - 1971
Linear Equations; Vector Spaces; Linear Transformations; Polynomials; Determinants; Elementary canonical Forms; Rational and Jordan Forms; Inner Product Spaces; Operators on Inner Product Spaces; Bilinear Forms For all readers interested in linear algebra.
Probability, Random Variables and Stochastic Processes with Errata Sheet
Athanasios Papoulis - 2001
Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.
Bond Markets, Analysis, and Strategies
Frank J. Fabozzi - 1988
Fabozzi's "Bond Markets" is the most applied book on the market. It prepares students to analyze the bond market and manage bond portfolios without getting bogged down in the theory. The author's extensive experience in the field is reflected in this uniquely applied approach. This seventh edition has been painstakingly updated. The author conducted numerous conversations and discussions with analysts and portfolio managers to make sure that this text reflects the field today. Pricing of Bonds; Measuring Yield; Bond Price Volatility; Factors Affecting Bond Yields and the Term Structure of Interest Rates; Treasury and Agency Securities; Corporate Debt Instruments; Municipal Securities; Non-U.S. Bonds; Residential Mortgage Loans; Agency Mortgage Pass-through Securities; Agency Collateralized Mortgage Obligations and Stripped Mortgage-Backed Securities; Prime and Subprime Mortgage-Backed Securities; Commercial Loans and Commercial Mortgage-Backed Securities; Asset-Backed Securities; Cash Collateralized Debt Obligations; Interest Rate Models; Analysis of Bonds with Embedded Options; Analysis of Mortgage-Backed Securities; Analysis of Convertible Bonds; Corporate Bond Credit Analysis; Credit Risk Modeling; Active Bond Portfolio Management Strategies; Indexing; Liability Driven Strategies; Bond Performance Measurement and Evaluation; Interest Rate Futures; Interest Rate Options; Interest-Rate Swaps, Caps, and Floors; Credit Derivatives and Synthetic CDOs The latest edition of Fabozzi's "Bond Markets "helps make sense of bond markets and mortgage financing. The 2008 financial crisis is explained as part of the newly added chapter on prime and subprime loans.
Inefficient Markets: An Introduction to Behavioral Finance
Andrei Shleifer - 2000
It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies. This bookdescribes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In actualfinancial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents models of such markets. These models explain the available financial data more accurately than the efficient marketshypothesis, and generate new predictions about security prices. By summarizing and expanding the research in behavioral finance, the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets.
Mathematics: Its Content, Methods and Meaning
A.D. Aleksandrov - 1963
. . Nothing less than a major contribution to the scientific culture of this world." — The New York Times Book ReviewThis major survey of mathematics, featuring the work of 18 outstanding Russian mathematicians and including material on both elementary and advanced levels, encompasses 20 prime subject areas in mathematics in terms of their simple origins and their subsequent sophisticated developement. As Professor Morris Kline of New York University noted, "This unique work presents the amazing panorama of mathematics proper. It is the best answer in print to what mathematics contains both on the elementary and advanced levels."Beginning with an overview and analysis of mathematics, the first of three major divisions of the book progresses to an exploration of analytic geometry, algebra, and ordinary differential equations. The second part introduces partial differential equations, along with theories of curves and surfaces, the calculus of variations, and functions of a complex variable. It furthur examines prime numbers, the theory of probability, approximations, and the role of computers in mathematics. The theory of functions of a real variable opens the final section, followed by discussions of linear algebra and nonEuclidian geometry, topology, functional analysis, and groups and other algebraic systems.Thorough, coherent explanations of each topic are further augumented by numerous illustrative figures, and every chapter concludes with a suggested reading list. Formerly issued as a three-volume set, this mathematical masterpiece is now available in a convenient and modestly priced one-volume edition, perfect for study or reference."This is a masterful English translation of a stupendous and formidable mathematical masterpiece . . ." — Social Science
Mathematical Methods for Physicists
George B. Arfken - 1970
This work includes differential forms and the elegant forms of Maxwell's equations, and a chapter on probability and statistics. It also illustrates and proves mathematical relations.
Reinforcement Learning: An Introduction
Richard S. Sutton - 1998
Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.
Judgment Under Uncertainty: Heuristics and Biases
Daniel Kahneman - 1982
Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, multistage inference, social perception, medical diagnosis, risk perception, and methods for correcting and improving judgments under uncertainty. About half of the chapters are edited versions of classic articles; the remaining chapters are newly written for this book. Most review multiple studies or entire subareas of research and application rather than describing single experimental studies. This book will be useful to a wide range of students and researchers, as well as to decision makers seeking to gain insight into their judgments and to improve them.
Elements of Information Theory
Thomas M. Cover - 1991
Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.
Probability And Statistics For Engineers And Scientists
Ronald E. Walpole - 1978
Offers extensively updated coverage, new problem sets, and chapter-ending material to enhance the book’s relevance to today’s engineers and scientists. Includes new problem sets demonstrating updated applications to engineering as well as biological, physical, and computer science. Emphasizes key ideas as well as the risks and hazards associated with practical application of the material. Includes new material on topics including: difference between discrete and continuous measurements; binary data; quartiles; importance of experimental design; “dummy” variables; rules for expectations and variances of linear functions; Poisson distribution; Weibull and lognormal distributions; central limit theorem, and data plotting. Introduces Bayesian statistics, including its applications to many fields. For those interested in learning more about probability and statistics.
Schaum's Outline of Linear Algebra
Seymour Lipschutz - 1968
This guide provides explanations of eigenvalues, eigenvectors, linear transformations, linear equations, vectors, and matrices.
The Book of Why: The New Science of Cause and Effect
Judea Pearl - 2018
Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.