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• 0. ALGEBRAIC CONCEPTS. Sets. The Real Numbers. Integral Exponents. Radicals and Rational Exponents. Operations with Algebraic Expressions. Factoring. Algebraic Fractions.
• 1. LINEAR EQUATIONS AND FUNCTIONS. Solutions of Linear Equations and Inequalities in One Variable. Functions. Linear Functions. Graphs and Graphing Utilities. Solutions of Systems of Linear Equations. Applications of Functions in Business and Economics.
• 2. QUADRATIC AND OTHER SPECIAL FUNCTIONS. Quadratic Equations. Quadratic Functions: Parabolas. Business Applications Using Quadratics. Special Functions and Their Graphs. Modeling-- Fitting Curves to Data with Graphing Utilities (optional).
• 3. MATRICES. Matrices. Multiplication of Matrices. Gauss-Jordan Elimination: Solving Systems of Equations. Inverse of a Square Matrix-- Matrix Equations. Applications of Matrices: Leontief Input-Output Models.
• 4. INEQUALITIES AND LINEAR PROGRAMMING. Linear Inequalities in Two Variables. Linear Programming: Graphical Methods. The Simplex Method: Maximization. The Simplex Method: Duality and Minimization. The Simplex Method with Mixed Constraints.
• 5. EXPONENTIAL AND LOGARITHMIC FUNCTIONS. Exponential Functions. Logarithmic Functions and Their Properties. Equations and Applications with Exponential and Logarithmic Functions.
• 6. MATHEMATICS OF FINANCE. Simple Interest-- Sequences. Compound Interest-- Geometric Sequences. Future Values of Annuities. Present Values of Annuities. Loans and Amortization.
• 7. INTRODUCTION TO PROBABILITY. Probability-- Odds. Unions and Intersections of Events: One-Trial Experiments. Conditional Probability: The Product Rule. Probability Trees and Bayes'' Formula. Counting: Permutations and Combinations. Permutations, Combinations, and Probability. Markov Chains.
• 8. FURTHER TOPICS IN PROBABILITY-- DATA DESCRIPTION. Binomial Probability Experiments. Data Description. Discrete Probability Distributions-- The Binomial Distribution. Normal Probability Distribution. The Normal Curve Approximation to the Binomial Distribution.
• 9. DERIVATIVES. Limits. Continuous Functions-- Limits at Infinity. Rates of Change and Derivatives. Derivative Formulas. The Product Rule and the Quotient Rule. The Chain Rule and the Power Rule. Using Derivative Formulas. Higher-Order Derivatives. Applications: Marginals and Derivatives.
• 10. APPLICATIONS AND DERIVATIVES. Relative Maxima and Minima: Curve Sketching. Concavity: Points of Inflection. Optimization in Business and Economics. Applications of Maxima and Minima. Rational Functions: More Curve Sketching.
• 11. DERIVATIVES CONTINUED. Derivatives of Logarithmic Functions. Derivatives of Exponential Functions. Implicit Differentiation. Related Rates. Applications in Business and Economics.
• 12. INDEFINITE INTEGRALS. Indefinite Integrals. The Power Rule. Integrals Involving Exponential and Logarithmic Functions. Applications of the Indefinite Integral in Business and Economics. Differential Equations.
• 13. DEFINITE INTEGRALS: TECHNIQUES OF INTEGRATION. Area Under a Curve. The Definite Integral: The Fundamental Theorem of Calculus. Area Between Two Curves. Applications of Definite Integrals in Business and Economics. Using Tables of Integrals. Integration by Parts. Improper Integrals and Their Applications. Numerical Integration Methods: The Trapezoidal Rule and Simpson''s Rule.
• 14. FUNCTIONS OF TWO OR MORE VARIABLES. Functions of Two or More Variables. Partial Differentiation. Applications of Functions of Two Variables in Business and Economics. Maxima and Minima. Maxima and Minima of Functions Subject to Constraints: Lagrange Multipliers. APPENDICES. A. Graphing Calculator Guide. B. Excel Guide. C. Areas Under the Standard Normal Curve.
• (source: Nielsen Book Data)

MATHEMATICAL APPLICATIONS FOR THE MANAGEMENT, LIFE, AND SOCIAL SCIENCES, 12th Edition, helps students succeed in finite mathematics and applied calculus courses by tying the concepts to real-life applications using real, meaningful data. Designed for students majoring in business, economics, life sciences and social sciences, the book offers a brief review of algebra to prepare students with different backgrounds for the material in later chapters. Chapter Warm-ups review the prerequisite topics for each chapter, and Checkpoints ask questions and pose problems within each section's discussion--allowing you to check your understanding of skills and concepts before moving to the next chapter. Use of technology is integrated into the text, and optional modeling problems are discussed. Student resources include a Student Solutions Manual and online homework with WebAssign.
(source: Nielsen Book Data)

• PART I: MATHEMATICAL APPLICATIONS
• 1. Revision Mathematics
• 2. Keeping up with Change: Index Numbers PART II: COLLECTING AND INTERPRETING DATA
• 3. Collecting Data: Surveys and Samples
• 4. Finding Patterns in Data: Charts and Tables
• 5. Making Sense of Data: Averages and Measures of Spread PART III: PROBABILITY& STATISTICS
• 6. Taking a Chance: Probability
• 7. The Shape of Data: Probability Distributions
• 8. Interpreting with Confidence: Analysis of Sample Data
• 9. Checking Ideas: Testing a Hypothesis
• 10. Cause and Effect: Correlation and Regression PART IV: DECISION MAKING TECHNIQUES
• 11. How to make Good Decisions
• 12. Choosing wisely: Investment Appraisal
• 13. Forecasting: Time Series Analysis
• 14. Making the Most of Things: Linear Programming
• 15. Planning Large Projects: Network Analysis
• 16. Managing Stock Levels: Materials Management and Inventory Control.
• (source: Nielsen Book Data)

The new edition of this accessible textbook provides ideal introductory coverage of quantitative methods. It offers real world business examples and case studies to illustrate problem-solving in empirical situations. Student learning is comprehensively supported by extensive online resources.
(source: Nielsen Book Data)

• Theory of Interest Rate of Return and Present Value Compound Interest Annuities Loans Measuring Rate of Return Continuous Time Interest Theory Bonds Bond Valuation More on Bonds Term Structure of Interest Rates Discrete Probability for Finance Sample Spaces and Probability Measures Random Variables and Distributions Discrete Expectation Conditional Probability Independence and Dependence Estimation and Simulation Portfolio Theory Stocks Portfolios of Risky Assets Optimal Portfolio Selection Valuation of Derivatives Basic Terminology and Ideas Single-Period Options Multiple-Period Options Valuation of Exotic Options and Simulation Appendix: Answers to Selected Exercises Bibliography Index.
• (source: Nielsen Book Data)

Introduction to Financial Mathematics is ideal for an introductory undergraduate course. Unlike most textbooks aimed at more advanced courses, the text motivates students through a discussion of personal finances and portfolio management. The author then goes on to cover valuation of financial derivatives in discrete time, using all of closed form, recursive, and simulation methods. The text covers nearly all of the syllabus topics of the Financial Mathematics Actuarial examination, providing students with the foundation they require for future studies and throughout their careers. It begins by covering standard material on the mathematics of interest, including compound interest, present value, annuities, loans, several versions of the rate of return on an investment, and interest in continuous time. The text explains how to value bonds at their issue dates, at coupon times, between coupon times, and in cases where the bonds are terminated early. Next, it supplies a rapid-fire overview of the main ideas and techniques of discrete probability, including sample spaces and probability measures, random variables and distributions, expectation, conditional probability, and independence. The author introduces the basic terminology of stocks and stock trading. He also explains how to derive the rate of return on a portfolio and how to use the idea of risk aversion to model the investor tradeoff between risk and return. The text also discusses the estimation of parameters of asset models from real data. The text closes with a detailed discussion of how to value financial derivatives using anti-arbitrage assumptions. The one-step and multi-step cases are covered, and exotic options such as barrier options are also introduced, to which simulation methods are applied. Many of the examples in the book involve numerical solution of complicated non-linear equations; others ask students to produce algorithms which beg to be implemented as programs. For maximum flexibility, the author has produced the text without adhering to any particular computational platform. A digital version of this text is also available in the form of Mathematica notebooks that contain additional content.
(source: Nielsen Book Data)

• Chapter 1: Principles of Modern Analytics
• 1
• Chapter 2: Business 3.0 Is Here
• 15
• Chapter 3: Why You Need a Unique Analytics Roadmap
• 19
• Chapter 4: Analytics Can Supercharge Your Business Strategy
• 25
• Chapter 5: Building Your Analytics Roadmap
• 61
• Chapter 6: Analytic Applications
• 87
• Chapter 7: Analytic Use Cases
• 103
• Chapter 8: Predictive Analytics Methodology
• 119
• Chapter 9: Predictive Analytics Techniques
• 147
• Chapter 10: End User Analytics
• 193
• Chapter 11: Analytic Platforms
• 223
• Chapter 12: Attracting and Retaining Analytics Talent
• 257
• Chapter 13: Organizing Analytics Teams
• 283
• Chapter 14: What Are You Waiting For? Go Get Started!
• 293 Appendix A: Unsupervised Learning: Unsupervised Neural Networks
• 297 Index 313.
• (source: Nielsen Book Data)

Advanced Analytics Methodologies is today's definitive guide to analytics implementation for MBA and university-level business students and sophisticated practitioners. Its expanded, cutting-edge coverage helps readers systematically "jump the gap" between their organization's current analytical capabilities and where they need to be. Step by step, Michele Chambers and Thomas Dinsmore help readers customize a complete roadmap for implementing analytics that supports unique corporate strategies, aligns with specific corporate cultures, and serves unique customer and stakeholder communities. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore provide advanced applications and examples not available elsewhere, describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. They show how to: * Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy * Link key business objectives with core characteristics of your organization, value chain, and stakeholders * Take advantage of game changing opportunities before competitors do * Effectively integrate the managerial and operational aspects of analytics * Measure performance with dashboards, scorecards, visualization, simulation, and more * Prioritize and score prospective analytics projects * Identify "Quick Wins" you can implement while you're planning for the long-term * Build an effective Analytic Program Office to make your roadmap persistent * Update and revise your roadmap for new needs and technologies This advanced text will serve the needs of students and faculty studying cutting-edge analytics techniques, as well as experienced analytics leaders and professionals including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and many line-of-business executives.
(source: Nielsen Book Data)

• Acknowledgements About the author Conventions Overview Warranty and disclaimer
• 1 Introduction Overview Common Excel errors Systematic design method Auditing Summary
• 2 Basic financial arithmetic Simple interest Compound interest Nominal and effective rates Continuous discounting Conversions and comparisons Exercise Summary
• 3 Cash flows Net present value Internal rate of return XNPV and XIRR XNPV periodic example Modified internal rate of return Exercise Summary
• 4 Bonds calculations Description Cash flows Zero coupons Yield Yield to call Price and yield relationship Yield curve pricing Other yield measures Yield measures Exercise Summary
• 5 Bonds risks Risks Duration Convexity Comparison Exercise Summary
• 6 Floating rate securities Floating rates Characteristics of interest rate securities Yield evaluation Coupon stripping Exercise Summary
• 7 Amortization and depreciation Amortization Full amortization Delayed payments Sum of digits Straight line and declining balance depreciation UK declining balance method Double declining balance depreciation French depreciation Exercise Summary
• 8 Swaps Definitions How swaps save money Advantages of swaps Terminating interest rate swaps Implicit credit risk Worked single currency swap Valuation Cross currency swap Worked example Swaptions Exercise Summary
• 9 Forward interest rates Definitions Example forward rates Hedging principles Forward rate agreement Yield curves Exercise Summary
• 10 Futures Futures market Terminology Benefits Clearinghouse operation Bond futures Hedging mechanisms Hedging example one Hedging example two Exercise Summary
• 11 Foreign exchange Risk Spot rates Longer dates Equivalence Comparisons and arbitrage Exercise Summary
• 12 Options Description Terminology Underlying asset Call options Put options Example Covered call Insurance using a stock and a long put Pricing models Black Scholes model Call put parity Greeks Binomial models Comparison to Black Scholes Exercise Summary
• 13 Real options Real options Black Scholes model Binomial model Exercise Summary
• 14 Valuation Valuation methods Assets Market methods Multi-period dividend discount models Free cash flow valuation Adjusted present value Economic profit Exercise Summary
• 15 Leasing Economics of leasing Interest rates Classification Amortization Accounting Settlements Lessor evaluation Lessee evaluation Exercise Summary
• 16 Basic statistics Methods Descriptive statistics Probability distributions Sampling/Central Limit Theorem Hypothesis testing Correlation and regression LINEST function Exercise Summary Appendices
• 1 Exercise answers, functions list, software installation and licence
• 2 Microsoft(R) Office Menus Index.
• (source: Nielsen Book Data)

Fully updated and compliant with Excel 2013, this clearly explains the basic calculations for mathematical finance, backed up with simple templates for further use and development, and a workbook with exercises and solutions at the end of each chapter. The examples used are relevant to both managers and students in the UK and overseas. New to this edition * Updated glossary of key terms * Functions list in English and Euro languages * Continuity check on all formats, layouts and charts * More worked examples * Additional exercises at the end of each chapter to help build models * Templates and models available online.
(source: Nielsen Book Data)

• Will I have to wear a suit? rethinking life after graduate school
• Getting your head ready
• Should I finish my dissertation?
• How to use your grad school years wisely
• So what am I going to do?
• Myths about post-academic careers
• Questions about graduate school and your future
• Your eclectic mix
• Post-academic profile: Abby Markoe, A.B.D. history of medicine, executive, director
• Squashwise
• How do I figure out what else to do? soul-searching before job searching
• Take inventory
• Break it down
• Looking backward: seven stories
• Guilty pleasures
• "This is your brain on graduate school"
• No need for a #2 pencil
• Where are all those PhDs anyway?
• Create your own possibilities
• Post-academic profile: Samantha Sutton, PhD in biology, life coach
• Asking the big questions: how to figure out if you want them and if they want you
• Asking the big questions
• Answering the big questions: three strategies
• Transitional tales
• So what's next?
• Post-academic profile: Xiuwen Tu, PhD in physics, Sun Power Corporation, device and characterization engineer
• This might hurt a bit: turning a CV into a résumé
• Getting ready to write a résumé
• Writing a résumé: the first draft
• A few more words of advice
• After you've drafted a résumé
• Case studies and sample résumés
• Cover letters that will get you hired
• Post-academic profile: Alyssa Picard, PhD in history, staff representative for the Michigan Affiliate of the American Federation of Teachers
• Sweaty palms, warm heart: how to turn an interview into a job
• Before the interview
• During the interview
• After the interview
• What if the interview doesn't go well?
• The job offer (or lack thereof)
• Negotiation
• Adjusting to your new job
• Post-academic profile: Scott Keeter, PhD in political science, director of Survey Research, Pew Research Center for the People & the Press
• Conclusion.

Graduate schools churn out tens of thousands of PhDs and MAs every year. Yet more than half of all college courses are taught by adjunct faculty, which means that the chances of an academic landing a tenure-track job seem only to shrink as student loan and credit card debts grow. What's a frustrated would-be scholar to do? Can she really leave academia? Can a job outside the academy really be rewarding? And could anyone want to hire a grad-school refugee? In this third edition of "So What Are You Going to Do with That?", thoroughly revised with new advice for students in the sciences, Susan Basalla and Maggie Debelius-PhDs themselves - answer all those questions with a resounding "Yes!" A witty, accessible guide full of concrete advice for anyone contemplating the jump from scholarship to the outside world, "So What Are You Going to Do with That?" covers topics ranging from career counseling to interview etiquette to how to translate skills learned in the academy into terms an employer can understand and appreciate. Packed with examples and stories from real people who have successfully made this daunting - but potentially rewarding-transition, and written with a deep understanding of both the joys and difficulties of the academic life, this fully updated guide will be indispensable for any graduate student or professor who has ever glanced at his or her CV, flipped through the want ads, and wondered, "What if?".
(source: Nielsen Book Data)

• 1 Introduction to Business Mathematics and Statistics
• Part 1. Data and their presentation
• 2. Sampling and Data Collection
• 3. Data and their Accuracy
• 4. Frequency Distributions and Charts
• 5. General Charts and Graphs Examination questions
• Part 2. Statistical measures
• 6. Arithmetic Mean
• 7. Median
• 8. Mode and Other Measures of Location
• 9. Measures of Dispersion and Skewness
• 10. Standard Deviation
• 11. Quantiles and the Quartile Deviation Examination example and questions
• Part 3. Regression and correlation
• 12. Linear Functions and Graphs
• 13. Regression Techniques
• 14. Correlation Techniques Examination examples and questions
• Part 4. Time series analysis
• 15. Time Series Model
• 16. Time Series Trend
• 17. Seasonal Variation and Forecasting Examination example and questions
• Part 5 Index numbers
• 18. Index Relatives
• 19. Composite Index Numbers
• 20. Special Published Indices Examination questions
• Part 6. Compounding, discounting and annuities
• 21. Interest and Depreciation
• 22. Present Value and Investment Appraisal
• 23. Annuities Examination examples and questions
• Part 7 Business equations and graphs
• 24. Functions and Graphs
• 25. Linear Equations
• 26. Quadratic and Cubic Equations
• 27. Differentiation and Integration
• 28. Cost, Revenue and Profit Functions Examination examples and questions
• Part 8 Probability
• 29. Set Theory and Enumeration
• 30. Introduction to Probability
• 31. Conditional Probability and Expectation Examination examples and questions
• Part 9. Further probability
• 32. Combinations and Permutations
• 33. Binomial and Poisson Distributions
• 34. Normal Distribution Examination example and questions
• Part 10 Specialised business applications
• 35. Linear Inequalities
• 36. Matrices
• 37. Inventory Control
• 38. Network Planning and Analysis Examination example and questions.
• (source: Nielsen Book Data)

This seventh edition of Business Mathematics and Statistics provides a thorough grounding in basic mathematical and statistical techniques, helping students to learn how to make decisions when presented with incomplete information. Comprehensive coverage of statistical methods, management mathematics and probability and extensive examples and questions make this essential reading for students on business and accounting courses and also students studying economics.
(source: Nielsen Book Data)

An updated and expanded version of the time-honored classic text on financial math, this book provides, in one place, a complete and practical treatment of the four primary venues for finance: commercial lending, financial formulas, mortgage lending, and resource allocation or capital budgeting techniques. With an emphasis on understanding the principles involved rather than blind reliance on formulas, the book provides rigorous and thorough explanations of the mathematical calculations used in determining the time value of money, valuation of loans by commercial banks, valuation of mortgages, and the cost of capital and capital budgeting techniques for single as well as mutually exclusive projects. This new edition devotes an entire chapter to a method of evaluating mutually exclusive projects without resorting to any imposed conditions. Two chapters not found in the previous edition address special topics in finance, including a novel and innovative way to approach amortization tables and the time value of money for cash flows when they increase geometrically or arithmetically. This new edition also features helpful how-to sections on Excel applications at the end of each appropriate chapter.
(source: Nielsen Book Data)

• INTRODUCTION TO PRICING AND MANAGEMENT OF FINANCIAL SECURITIES Mathematics of Compounding Primer on Pricing Risky Securities Portfolio Management Primer on Derivative Securities
• DISCRETE-TIME MODELING Single-Period Arrow-Debreu Models Introduction to Discrete-Time Stochastic Calculus Replication and Pricing in the Binomial Tree Model General Multi-Asset Multi-Period Model
• CONTINUOUS-TIME MODELING Essentials of General Probability Theory One-Dimensional Brownian Motion and Related Processes Introduction to Continuous-Time Stochastic Calculus Risk-Neutral Pricing in the (B, S) Economy: One Underlying Stock Risk-Neutral Pricing in a Multi-Asset Economy American Options Alternative Models of Asset Price Dynamics Interest-Rate Modeling and Derivative Pricing COMPUTATIONAL TECHNIQUES Introduction to Monte Carlo and Simulation Methods Numerical Applications to Derivative Pricing Appendix: Some Useful Integral Identities and Symmetry Properties of Normal Random Variables Glossary of Symbols and Abbreviations References Index.
• (source: Nielsen Book Data)

Versatile for Several Interrelated Courses at the Undergraduate and Graduate Levels Financial Mathematics: A Comprehensive Treatment provides a unified, self-contained account of the main theory and application of methods behind modern-day financial mathematics. Tested and refined through years of the authors' teaching experiences, the book encompasses a breadth of topics, from introductory to more advanced ones. Accessible to undergraduate students in mathematics, finance, actuarial science, economics, and related quantitative areas, much of the text covers essential material for core curriculum courses on financial mathematics. Some of the more advanced topics, such as formal derivative pricing theory, stochastic calculus, Monte Carlo simulation, and numerical methods, can be used in courses at the graduate level. Researchers and practitioners in quantitative finance will also benefit from the combination of analytical and numerical methods for solving various derivative pricing problems. With an abundance of examples, problems, and fully worked out solutions, the text introduces the financial theory and relevant mathematical methods in a mathematically rigorous yet engaging way. Unlike similar texts in the field, this one presents multiple problem-solving approaches, linking related comprehensive techniques for pricing different types of financial derivatives. The book provides complete coverage of both discrete- and continuous-time financial models that form the cornerstones of financial derivative pricing theory. It also presents a self-contained introduction to stochastic calculus and martingale theory, which are key fundamental elements in quantitative finance.
(source: Nielsen Book Data)

• Preface--
• 1. Probability space--
• 2. Probability distributions and random variables--
• 3. Product measure and independence--
• 4. Conditional expectation--
• 5. Sequences of random variables-- Index.
• (source: Nielsen Book Data)

Students and instructors alike will benefit from this rigorous, unfussy text, which keeps a clear focus on the basic probabilistic concepts required for an understanding of financial market models, including independence and conditioning. Assuming only some calculus and linear algebra, the text develops key results of measure and integration, which are applied to probability spaces and random variables, culminating in central limit theory. Consequently it provides essential prerequisites to graduate-level study of modern finance and, more generally, to the study of stochastic processes. Results are proved carefully and the key concepts are motivated by concrete examples drawn from financial market models. Students can test their understanding through the large number of exercises and worked examples that are integral to the text.
(source: Nielsen Book Data)

• 1. Introduction
• 2. The Basis of Everything is Water: Understanding Risk in Markets
• 3. Harvesting Olives: Alpha and Beta Strategies
• 4. The Code of Hammurabi: Reducing Risk
• 5. Not What They Care About: Having Targets Other Than Returns
• 6. Predicting the Eclipse: Searching for a Black Swan and Windows of Doom
• 7. In the Stars: Lateral Thinking to Understand Markets
• 8. The Silk Road and its Secrets: Is There Really a Secret Sauce in Trading?
• 9. The Father of History: This Time is Sometimes Different in Markets
• 10. A Last Word to Conclude.
• (source: Nielsen Book Data)

What can the ancient world teach us about modern money markets? How can we use examples from the ancient world, philosophers and writers to better understand the markets? Just as historians such as Herodotus living in ancient Greece examined the past, can traders look to their past to learn something new? In this exciting new book, Saeed Amen looks to the ancient world to help us better understand modern money markets, demonstrating what ancient philosophers can teach us about trading markets today, and showing readers how to maximize their returns. Based on the rationale that if your primary objective is purely to make money from trading quickly, you can make decisions that perversely increase the likelihood of losing; this book demonstrates how successful trading can actually be achieved as a byproduct of good trading. Relating concepts from the ancient world, such as water and risk, diversified knowledge, Herodotus and historical bias to the modern world money markets, Amen demonstrates that by focusing on goals that go beyond making money, lateral thinking, targeting risk adjusted returns, and keeping drawdowns in check, investors will indirectly make more money in the long run. Investors might be fooled by randomness on occasion, but luck can never be derided as an important factor, which helps investors succeed. Instead repeated success in investing capital over an extended period seems to be less a product of randomness, but instead a product of a profound understanding of markets.
(source: Nielsen Book Data)

• Table of Contents:* Money and markets * Fair games * Set theory * Measurable functions * Probability spaces * Expected values * Continuity and integrability * Conditional expectation * Lebesgue measure * Martingales * The Black-Scholes formula * Stochastic integration * Solutions * Bibliography * Index.
• (source: Nielsen Book Data)

The use of the Black-Scholes model and formula is pervasive in financial markets. There are very few undergraduate textbooks available on the subject and, until now, almost none written by mathematicians. Based on a course given by the author, the goal of this book is to introduce advanced undergraduates and beginning graduate students studying the mathematics of finance to the Black-Scholes formula. The author uses a first-principles approach, developing only the minimum background necessary to justify mathematical concepts and placing mathematical developments in context. The book skillfully draws the reader toward the art of thinking mathematically and then proceeds to lay the foundations in analysis and probability theory underlying modern financial mathematics. It rigorously reveals the mathematical secrets of topics such as abstract measure theory, conditional expectations, martingales, Wiener processes, the Ito calculus, and other ingredients of the Black-Scholes formula. In explaining these topics, the author uses examples drawn from the universe of finance. The book also contains many exercises, some included to clarify simple points of exposition, others to introduce new ideas and techniques, and a few containing relatively deep mathematical results. The second edition contains numerous revisions and additional material designed to enhance the book's usability as a classroom text. These changes include insights gleaned by the author after teaching from the text, as well as comments and suggestions made by others who used the book. Whereas the revised edition maintains the original approach, format, and list of topics, most chapters are modified to some extent; in addition, the rearrangement of material resulted in a new chapter (Chapter 9). With the modest prerequisite of a first course in calculus, the book is suitable for undergraduates and graduate students in mathematics, finance, and economics and can be read, using appropriate selections, at a number of levels.
(source: Nielsen Book Data)

• Introduction and User Guide Introduction and concept Contents How to use this book? Further literature Acknowledgements Generating Random Numbers Introduction Examples of random number generators Testing and analyzing RNGs Generating random numbers with general distributions Selected distributions Multivariate random variables Quasi random sequences as a substitute for random sequences Parallelization techniques The Monte Carlo Method: Basic Principles and Improvements Introduction The strong law of large numbers and the Monte Carlo method Improving the speed of convergence of the Monte Carlo method: Variance reduction methods Further aspects of variance reduction methods Simulating Continuous-Time Stochastic Processes with Continuous Paths Introduction Stochastic processes and their paths: Basic definitions The Monte Carlo method for stochastic processes Brownian motion and the Brownian bridge Basics of Ito calculus Stochastic differential equations Simulating solutions of stochastic differential equations Which simulation methods for SDE should be chosen? Simulating Financial Models and Pricing of Derivatives: Continuous Paths Introduction Basics of stock price modeling A Black-Scholes type stock price framework Basic facts of options An introduction to option pricing Option pricing and the Monte Carlo method in the Black-Scholes setting Weaknesses of the Black-Scholes model Local volatility models and the CEV model An excursion: Calibrating a model Option pricing in incomplete markets: Some aspects Stochastic volatility and option pricing in the Heston model Variance reduction principles in non-Black-Scholes models Stochastic local volatility models Monte Carlo option pricing: American and Bermudan options Monte Carlo calculation of option price sensitivities Basics of interest rate modeling The short rate approach to interest rate modeling The forward rate approach to interest rate modeling LIBOR market models Simulating Continuous-Time Stochastic Processes: Discontinuous Paths Introduction Poisson processes and Poisson random measures: Definition and simulation Jump diffusions: Basics, properties, and simulation Levy processes: Definition, properties, and examples Simulation of Levy processes Simulating Financial Models: Discontinuous Paths Introduction Merton's jump diffusion model and stochastic volatility models with jumps Special Levy models and their simulation Simulating Actuarial Models Introduction Premium principles and risk measures Some applications of Monte Carlo methods in life insurance Simulating dependent risks with copulas Non-life insurance Markov chain Monte Carlo and Bayesian estimation Asset-liability management and Solvency II References Index.
• (source: Nielsen Book Data)

Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of stochastic processes with continuous and discontinuous paths. It also covers a wide selection of popular models in finance and insurance, from Black-Scholes to stochastic volatility to interest rate to dynamic mortality. Through its many numerical and graphical illustrations and simple, insightful examples, this book provides a deep understanding of the scope of Monte Carlo methods and their use in various financial situations. The intuitive presentation encourages readers to implement and further develop the simulation methods.
(source: Nielsen Book Data)

• The lovely but lonely Vickrey auction / Lawrence M. Ausubel and Paul Milgrom
• Iterative combinatorial auctions / David C. Parkes
• Ascending proxy auctions / Lawrence M. Ausubel and Paul Milgrom
• Simultaneous ascending auctions / Peter Cramton
• The clock-proxy auction : a practical combinatorial auction design / Lawrence M. Ausubel, Peter Cramton, and Paul Milgrom
• PAUSE : a computationally tractable combinatorial auction / Ailsa Land, Susan Powell, and Richard Steinberg
• Pseudonymous bidding in combinatorial auctions / Makato Yokoo
• From the assignment model to combinatorial auctions / Sushil Bikhchandani and Joseph M. Ostroy
• Bidding languages for combinatorial auctions / Noam Nisan
• Preference elicitation in combinatorial auctions / Tuomas Sandholm and Craig Boutilier
• The communication requirements of combinatorial allocation problems / Ilya Segal
• The winner determination problem / Daniel Lehmann, Rudolf Müller, and Tuomas Sandholm
• Tractable cases of the winner determination problem / Rudolf Müller
• Optimal winner determination algorithms / Tuomas Sandholm
• Incentive compatibility in computationally feasible combinatorial auctions / Amir Ronen
• Noncomputational approaches to mitigating computational problems in combinatorial auctions / Aleksandar Pekeč and Michael H. Rothkopf
• Observations and near-direct implementations of the ascending proxy auction / Karla Hoffman ... [ et al.]
• A test suite for combinatorial auctions / Kevin Leyton-Brown and Yoav Shoham
• Empirical hardness models for combinatorial auctions / Kevin Leyton-Brown, Eugene Nudelman, and Yoav Shoham
• Auctions for the safe, efficient, and equitable allocation of airspace system resources / Michael O. Ball, George L. Donahue, and Karla Hoffman
• Combinatorial auctions for truckload transportation / Chris Caplice and Yossi Sheffi
• Auctioning bus routes : the London experience / Estelle Cantillon and Martin Pesendorfer
• Industrial procurement auctions / Martin Bichler ... [et al.].

A synthesis of theoretical and practical research on combinatorial auctions from the perspectives of economics, operations research, and computer science. The study of combinatorial auctions - auctions in which bidders can bid on combinations of items or packages - draws on the disciplines of economics, operations research, and computer science. This landmark collection integrates these three perspectives, offering a state-of-the art survey of developments in combinatorial auction theory and practice by leaders in the field. Combinatorial auctions (CAs), by allowing bidders to express their preferences more fully, can lead to improved economic efficiency and greater auction revenues. However, challenges arise in both design and implementation. Combinatorial Auctions addresses each of these challenges. After describing and analysing various CA mechanisms, the book addresses bidding languages and questions of efficiency. Possible strategies for solving the computationally intractable problem of how to compute the objective-maximising allocation (known as the winner determination problem) are considered, as are questions of how to test alternative algorithms. The book discusses five important applications of CAs: spectrum auctions, airport takeoff and landing slots, procurement of freight transportation services, the London bus routes market, and industrial procurement. This unique collection makes recent work in CAs available to a broad audience of researchers and practitioners. The integration of work from the three disciplines underlying CAs, using a common language throughout, serves to advance the field in theory and practice.
(source: Nielsen Book Data)

• Section 1. Key skills in career planning and decision-making.
• 1. The ten commandments of career satisfaction and success
• 2. Seven rules for a more successful career
• 3. Knowing what you do best
• 4. How motivated are your skills?
• 5. What do you like to do? the power of interests
• 6. A second look at your interests
• 7. 25 work-related values
• 8. Personality type
• 9. Working conditions
• 10. Some things you need to know about career testing
• 11. Choosing the right test
• 12. Brainstorming for job ideas
• 13. Researching the job market through informational interviewing
• 14. Questions to ask in informational interviews
• 15. Informational interviewing worksheet
• 16. Tapping into the Internet for occupational information
• Section 2. Resumes and cover letters.
• 17. Building blocks of a good (chronological) resume
• 18. Your resume in action : verb(alizing) your accomplishments
• 19. One size does not fit all : choosing the best resume format
• 20. The brave new world of electronic resumes
• 21. From good to great : making your resume stand out
• 22. Putting your education to work
• 23. Sample profiles
• 24. Keywords are winning words
• 25. What can you do for us? The power of accomplishments
• 26. Sample resumes
• 27. Resume planner
• 28. Cover letters : why you need them
• 29. How to wreck a cover letter
• 30. Rules of the cover letter writing road
• 31. Cover letter greatness
• 32. Cover letter worksheet
• 33. Sample cover letters
• 34. Cover letter template
• Section 3. A-job-hunting we will go.
• 35. Testing your readiness IQ
• 36. Job hunting while still employed
• 37. Seven job search myths
• 38. Company research
• 39. How to recover from involuntary terminations
• 40. The Psychological challenge
• 41. Where the jobs are
• 42. Help wanted
• 43. Is anybody home?
• 44. Taking advantage of career fairs
• 45. The recruiter connection
• 46. Recruiter worksheet
• 47. Can an employment agency help you?
• 48. Employment agency worksheet
• 49. More job search myths
• 50. Networking strategies for success
• 51. Network in action
• 52. 8 ways to manage the reference process
• 53. Job search insanity
• 54. Do you need a career counselor?
• 55. What career counselors do
• 56. Finding the right counselor for you
• 57. Long-distance job hunting
• 58. Working globally
• 59. Managing your finances during a job search
• 60. Time management for job hunters
• 61. Job search checklist
• 62. Secrets of a successful job search
• Section 4. The interview.
• 63. Interviewing : what employers look for
• 64. The art and skill of preparation
• 65. Body English
• 66. Interview do's and don'ts
• 67. Listening skills 101
• 68. Expecting the unexpected
• 69. "Food, glorious food" and other challenges of mealtime interviews
• 70. Typical questions
• 71. "Tell me about yourself."
• 72. "Where do you want to be five years from now?"
• 73. The 25 most popular behavioral questions
• 74. Strategies for dealing with behavioral questions
• 75. The consultative selling approach to interviewing
• 76. Problem-solving questions
• 77. "What are your weaknesses?"
• 78. Red flags : dealing with employer objections
• 79. Overcoming objections --

• Money and markets Fair games Set theory Measurable functions Probability spaces Expected values Continuity and integrability Conditional expectation Martingales The Black-Scholes formula Stochastic integration Solutions Bibliography Index.
• (source: Nielsen Book Data)

The use of the Black-Scholes model and formula is pervasive in financial markets. There are very few undergraduate textbooks available on the subject and, until now, almost none written by mathematicians. Based on a course given by the author, the goal of this book is to introduce advanced undergraduates and beginning graduate students studying the mathematics of finance to the Black-Scholes formula. The author uses a first-principles approach, developing only the minimum background necessary to justify mathematical concepts and placing mathematical developments in context.The book skillfully draws the reader toward the art of thinking mathematically and then proceeds to lay the foundations in analysis and probability theory underlying modern financial mathematics. It rigorously reveals the mathematical secrets of topics such as abstract measure theory, conditional expectations, martingales, Wiener processes, the Ito calculus, and other ingredients of the Black-Scholes formula. In explaining these topics, the author uses examples drawn from the universe of finance. The book also contains many exercises, some included to clarify simple points of exposition, others to introduce new ideas and techniques, and a few containing relatively deep mathematical results. With the modest prerequisite of a first course in calculus, the book is suitable for undergraduates and graduate students in mathematics, finance, and economics and can be read, using appropriate selections, at a number of levels.
(source: Nielsen Book Data)

• Credit barrier models in a discrete framework by C. Albanese and O. X. Chen Optimal derivatives design under dynamic risk measures by P. Barrieu and N. El Karoui On pricing of forward and futures contracts on zero-coupon bonds in the Cox-Ingersoll-Ross model by J. Bialkowski and J. Jakubowski Pricing and hedging of credit risk: Replication and mean-variance approaches (I) by T. R. Bielecki, M. Jeanblanc, and M. Rutkowski Pricing and Hedging of credit risk: Replication and mean-variance approaches (II) by T. R. Bielecki, M. Jeanblanc, and M. Rutkowski Spot convenience yield models for the energy markets by R. Carmona and M. Ludkovski Optimal portfolio management with consumption by N. Castaneda-Leyva and D. Hernandez-Hernandez Some processes associated with a fractional Brownian motion by T. E. Duncan Pricing claims on non tradable assets by R. J. Elliott and J. van der Hoek Some optimal investment, production and consumption models by W. H. Fleming Asian options under multiscale stochastic volatility by J.-P. Fouque and C.-H. Han A regime switching model: Statistical estimation, empirical evidence, and change point detection by X. Guo Multinomial maximum likelihood estimation of market parameters for stock jump-diffusion models by F. B. Hanson, J. J. Westman, and Z. Zhu Optimal terminal wealth under partial information for HMM stock returns by U. G. Haussmann and J. Sass Computing optimal selling rules for stocks using linear programming by K. Helmes Optimization of consumption and portfolio and minimization of volatility by Y. Hu Options: To buy or not to buy? by M. Jonsson and R. Sircar Risk sensitive optimal investment: Solutions of the dynamical programming equation by H. Kaise and S. J. Sheu Hedging default risk in an incomplete market by A. E. B. Lim Mean-variance portfolio choice with discontinuous asset prices and nonnegative wealth processes by A. E. B. Lim and X. Y. Zhou Indifference prices of early exercise claims by M. Musiela and T. Zariphopoulou Random walk around some problems in identification and stochastic adaptive control with applications to finance by B. Pasik-Duncan Pricing and Hedging for incomplete jump diffusion benchmark models by E. Platen Why is the effect of proportional transaction costs $O(\delta^{2/3})$? by L. C. G. Rogers Estimation via stochastic filtering in financial market models by W. J. Runggaldier Stochastic optimal control modeling of debt crises by J. L. Stein Duality and risk sensitive portfolio optimization by L. Stettner Characterizing option prices by linear programs by R. H. Stockbridge Pricing defaultable bond with regime switching by J. W. Wang and Q. Zhang Affine regime-switching models for interest rate term structure by S. Wu and Y. Zeng Stochastic approximation methods for some finance problems by G. Yin and Q. Zhang.
• (source: Nielsen Book Data)

The mathematics of finance involves a wide spectrum of techniques that go beyond traditional applied mathematics. The field has witnessed a tremendous amount of progress in recent years, which has inspired communication and networking among researchers in finance, economics, engineering, and industry. This volume contains papers based on talks given at the first AMS-IMS-SIAM Joint Summer Research Conference on Mathematics of Finance held at Snowbird (UT). Topics covered here include modeling, estimation, optimization, control, risk assessment and management, contingent claim pricing, dynamic hedging, and financial derivative design. The book is suitable for graduate students and research mathematicians interested in mathematical finance.
(source: Nielsen Book Data)

• A Brownian Motion of Financial Markets.- Contingent Claim Valuation in a Complete Market.- Single-Agent Consumption and Investment.- Equilibrium in a Complete Market.- Contingent Claims in Incomplete Markets.- Constrained Consumption and Investment.
• (source: Nielsen Book Data)

This book is the sequel to "Brownian Motion and Stochastic Calculus" by the same authors. Within the context of Brownian-motion-driven asset prices, it develops contingent claim pricing and optimal consumption/investment in both complete and incomplete markets. The latter topic is extended to a study of equilibrium, providing conditions for existence and uniqueness of market prices which support trading by several heterogeneous agents.Although much of the incomplete-market material is available in research papers, these topics are treated for the first time in a unified manner. The book contains an extensive set of references and notes describing the field, including topics not treated in the book. This book will be of interest to researchers wishing to see advanced mathematics applied to finance. The material on optimal consumption and investment, leading to equilibrium, is addressed to the theoretical finance community. The chapters on contingent claim valuation presents techniques of practical importance, especially for pricing exotic options.
(source: Nielsen Book Data)