Covering a variety of Excel simulations, from gambling to genetics, this introduction is for people interested in modeling future events, without the cost of an expensive textbook. The simulations covered offer a fun alternative to the usual Excel topics and include situations such as roulette, password cracking, sex determination, population growth, and traffic patterns, among many others.

Covering a variety of Excel simulations, from gambling to genetics, this introduction is for people interested in modeling future events, without the cost of an expensive textbook. The simulations covered offer a fun alternative to the usual Excel topics and include situations such as roulette, password cracking, sex determination, population growth, and traffic patterns, among many others.

Teach Your Students How to Become Successful Working Quants Quantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techniques of financial mathematics, but it also helps them gain significant intuition about what the techniques mean, how they work, and what happens when they stop working. After introducing risk, return, decision making under uncertainty, and traditional discounted cash flow project analysis, the book covers mortgages, bonds, and annuities using a blend of Excel simulation and difference equation or algebraic formalism. It then looks at how interest rate markets work and how to model bond prices before addressing mean variance portfolio optimization, the capital asset pricing model, options, and value at risk (VaR). The author next focuses on binomial model tools for pricing options and the analysis of discrete random walks. He also introduces stochastic calculus in a nonrigorous way and explains how to simulate geometric Brownian motion. The text proceeds to thoroughly discuss options pricing, mostly in continuous time. It concludes with chapters on stochastic models of the yield curve and incomplete markets using simple discrete models. Accessible to students with a relatively modest level of mathematical background, this book will guide your students in becoming successful quants. It uses both hand calculations and Excel spreadsheets to analyze plenty of examples from simple bond portfolios. The spreadsheets are available on the book’s CRC Press web page.

The use of simulation techniques has increased in importance in recent history, and simulation activities are an important resource for advanced preparation for the organization and execution of events. When formal mathematics is not enough, simulation may be the only option capable of approximating solutions. Simulation and Statistics with Excel: An Introduction to Business Students offers a non-rigorous and practical tour of the simulation procedure on computers, using a versatile and accessible resource, the Microsoft Excel spreadsheet. This book covers the concepts essential to understanding the basic principles and approaches of statistical simulation, allowing for the study of complex systems. Aimed at students in business and operational research beginning to use simulation as an instrument for understanding existing or proposed processes, this book will lay solid foundations in understanding simulation experimentation. Key Features: Provides a basis to understand the approaches and principles of simulator experiments. Uses a universal and easily accessible resource. Introduces simple examples to teach the fundamentals of simulation.

This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.

Covering a variety of Excel simulations by using Visual Basic (VBA), from gambling to genetics, this introduction is for people interested in modeling future events, without the cost of an expensive textbook. The simulations covered offer a fun alternative to the usual Excel topics and include situations such as roulette, password cracking, sex determination, population growth, and traffic patterns, among many others.

Praise for Financial Modeling with Crystal Ball(r) and Excel(r) "Professor Charnes's book drives clarity into applied Monte Carlo analysis using examples and tools relevant to real-world finance. The book will prove useful for analysts of all levels and as a supplement to academic courses in multiple disciplines." -Mark Odermann, Senior Financial Analyst, Microsoft "Think you really know financial modeling? This is a must-have for power Excel users. Professor Charnes shows how to make more realistic models that result in fewer surprises. Every analyst needs this credibility booster." -James Franklin, CEO, Decisioneering, Inc. "This book packs a first-year MBA's worth of financial and business modeling education into a few dozen easy-to-understand examples. Crystal Ball software does the housekeeping, so readers can concentrate on the business decision. A careful reader who works the examples on a computer will master the best general-purpose technology available for working with uncertainty." -Aaron Brown, Executive Director, Morgan Stanley, author of The Poker Face of Wall Street "Using Crystal Ball and Excel, John Charnes takes you step by step, demonstrating a conceptual framework that turns static Excel data and financial models into true risk models. I am astonished by the clarity of the text and the hands-on, step-by-step examples using Crystal Ball and Excel; Professor Charnes is a masterful teacher, and this is an absolute gem of a book for the new generation of analyst." -Brian Watt, Chief Operating Officer, GECC, Inc. "Financial Modeling with Crystal Ball and Excel is a comprehensive, well-written guide to one of the most useful analysis tools available to professional risk managers and quantitative analysts. This is a must-have book for anyone using Crystal Ball, and anyone wanting an overview of basic risk management concepts." -Paul Dietz, Manager, Quantitative Analysis, Westar Energy "John Charnes presents an insightful exploration of techniques for analysis and understanding of risk and uncertainty in business cases. By application of real options theory and Monte Carlo simulation to planning, doors are opened to analysis of what used to be impossible, such as modeling the value today of future project choices." -Bruce Wallace, Nortel

This book develops techniques for simulating digital logic circuits in Microsoft’s Excel that provide a useful tool to both the student and the practicing engineer. It introduces the subject by showing how logic devices, taken from the standard 7400 family, can be modeled and stored in a library. These functions can then be combined by the user as building blocks to design more complex circuits, both combinatorial and sequential. The simulations not only allow the designs to be verified to ensure they provide expected outputs and states, but can also perform detailed timing analysis. Worst case timing conditions can be imposed to stress the circuits so that the resultant behavior can be observed. Methods showing how the user can add additional devices to the simulation library are also covered.

The complete guide to the principles and practice of risk quantification for business applications. The assessment and quantification of risk provide an indispensable part of robust decision-making; to be effective, many professionals need a firm grasp of both the fundamental concepts and of the tools of the trade. Business Risk and Simulation Modelling in Practice is a comprehensive, in–depth, and practical guide that aims to help business risk managers, modelling analysts and general management to understand, conduct and use quantitative risk assessment and uncertainty modelling in their own situations. Key content areas include: Detailed descriptions of risk assessment processes, their objectives and uses, possible approaches to risk quantification, and their associated decision-benefits and organisational challenges. Principles and techniques in the design of risk models, including the similarities and differences with traditional financial models, and the enhancements that risk modelling can provide. In depth coverage of the principles and concepts in simulation methods, the statistical measurement of risk, the use and selection of probability distributions, the creation of dependency relationships, the alignment of risk modelling activities with general risk assessment processes, and a range of Excel modelling techniques. The implementation of simulation techniques using both Excel/VBA macros and the @RISK Excel add-in. Each platform may be appropriate depending on the context, whereas the core modelling concepts and risk assessment contexts are largely the same in each case. Some additional features and key benefits of using @RISK are also covered. Business Risk and Simulation Modelling in Practice reflects the author′s many years in training and consultancy in these areas. It provides clear and complete guidance, enhanced with an expert perspective. It uses approximately one hundred practical and real-life models to demonstrate all key concepts and techniques; these are accessible on the companion website.

Finance is Excel! This book takes you straight into the fascinating world of Excel, the powerful tool for number crunching. In a clear cut language it amalgamates financial theory with Excel providing you with the skills you need to build financial models for private or professional use. A comprehensive knowledge of modeling in Excel is becoming increasingly important in a competitive labour market. The chapters in part one start with the most basic Excel topics such as cell addresses, workbooks, basic formulas, etc. These chapters get more advanced through part one, and takes you in the end to topics such as array formulas, data tables, pivot tables, etc. The other parts of the book discusses a variety of subjects such as net present value, internal rate of return, risk, portfolio theory, CAPM, VaR, project valuation, asset valuation, firm valuation, loan, leasing, stocks, bonds, options, simulation, sensitivity analysis, etc.