Probabilities

Praise for the First Edition “If there is anything you want to know, or remind yourself, about probabilities, then look no further than this comprehensive, yet wittily written and enjoyable, compendium of how to apply probability calculations in real-world situations.” – Keith Devlin, Stanford University, National Public Radio’s “Math Guy” and author of The Math Gene and The Unfinished Game From probable improbabilities to regular irregularities, Probabilities: The Little Numbers That Rule Our Lives, Second Edition investigates the often surprising effects of risk and chance in our lives. Featuring a timely update, the Second Edition continues to be the go-to guidebook for an entertaining presentation on the mathematics of chance and uncertainty. The new edition develops the fundamental mathematics of probability in a unique, clear, and informal way so readers with various levels of experience with probability can understand the little numbers found in everyday life. Illustrating the concepts of probability through relevant and engaging real-world applications, the Second Edition features numerous examples on weather forecasts, DNA evidence, games and gambling, and medical testing. The revised edition also includes: The application of probability in finance, such as option pricing The introduction of branching processes and the extinction of family names An extended discussion on opinion polls and Nate Silver’s election predictions Probabilities: The Little Numbers That Rule Our Lives, Second Edition is an ideal reference for anyone who would like to obtain a better understanding of the mathematics of chance, as well as a useful supplementary textbook for students in any course dealing with probability.

While most books on trading deal with general concepts and shy away from specifics, Forex Patterns and Probabilities provides you with real-world strategies and a rare sense of clarity about the specific mechanics of currency trading. Leading trading educator Ed Ponsi will explain the driving forces in the currency markets and will provide strategies to enter, exit, and manage successful trades. Dozens of chart examples and explanations will guide you each step of the way and allow the reader to «look over the shoulder» of a professional trader hard at work at his craft. This book provides traders with step-by-step methodologies that are based on real market tendencies. The strategies in this book are presented clearly and in detail, so that anyone who wishes to can learn how to trade like a professional. It is written in a style that is easy to understand, so that the reader can quickly learn and use the techniques provided.

Select and execute the best trades—and reduce risk Rather than teaching options from a financial perspective, How to Price and Trade Options: Identify, Analyze, and Execute the Best Trade Probabilities goes back to the Nobel Prize-winning Black-Scholes model. Written by well-known options expert Al Sherbin, it looks at the basis for probability theory in option trading and explains how to put the odds in your favor when trading options. Inside, you'll discover how anyone can «operate their own casino» if they know how through proper option strategies. Plus, a supplemental website includes videos that walk you through various probability scenarios, pre-formatted spreadsheets, and code. All investors should have a portion of their portfolio set aside for option trades. Not only do options provide great opportunities for leveraged plays, they can also help you earn larger profits with a smaller amount of cash outlay. With the help of this book, traders, active investors, and self-directed investors of all stripes will learn how simple it can be to deploy probability-based trading strategies. Teaches both defined and undefined risk strategies Utilizes simple cost basis reduction strategies to enhance investment returns Draws on unique research studies Discusses volatility to include both historical (realized) and implied volatility: the interplay between the two is a key piece of information overlooked by option traders If you're a trader of any level and want to make the best trades possible, this book has you covered.

Foundations of Risk Analysis presents the issues core to risk analysis – understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes: An up to date presentation of how to understand, define and describe risk based on research carried out in recent years. A new definition of the concept of vulnerability consistent with the understanding of risk. Reflections on the need for seeing beyond probabilities to measure/describe uncertainties. A presentation and discussion of a method for assessing the importance of assumptions (uncertainty factors) in the background knowledge that the subjective probabilities are based on A brief introduction to approaches that produce interval (imprecise) probabilities instead of exact probabilities. In addition the new version provides a number of other improvements, for example, concerning the use of cost-benefit analyses and the As Low As Reasonably Practicable (ALARP) principle. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.

Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.

This book arrives at just the right time to facilitate understanding of performance-based fire risk assessment in buildings – an integral part of the global shift in policy away from traditional prescriptive codes. Yung, an internationally recognised expert on the subject of fire risk assessment, introduces the basic principles and techniques that help the reader to understand the various methodologies that are currently in place or being proposed by different organisations. Through his illustration of basic principles and techniques he enables the reader to conduct their own fire risk assessments. He demonstrates how the probabilities of fire scenarios are assessed based on the probabilities of success and failure of fire protection measures that are in place. He also shows how the consequences of fire scenarios are assessed based on the intensity and speed of fire and smoke spread, the probability and speed of occupant response and evacuation, and the effectiveness and speed of fire department response and rescue efforts. Yung’s clear and practical approach to this highly topical subject enables the reader to integrate the various tools available into a quantitative framework that can be used for decision making. He brings an invaluable resource to all those involved in fire engineering and risk assessment, including students, academics, building designers, fire protection engineers, structural engineers, regulators and risk analysts.

Derivatives Models on Models takes a theoretical and practical look at some of the latest and most important ideas behind derivatives pricing models. In each chapter the author highlights the latest thinking and trends in the area. A wide range of topics are covered, including valuation methods on stocks paying discrete dividend, Asian options, American barrier options, Complex barrier options, reset options, and electricity derivatives. The book also discusses the latest ideas surrounding finance like the robustness of dynamic delta hedging, option hedging, negative probabilities and space-time finance. The accompanying CD-ROM with additional Excel sheets includes the mathematical models covered in the book. The book also includes interviews with some of the world’s top names in the industry, and an insight into the history behind some of the greatest discoveries in quantitative finance. Interviewees include: Clive Granger, Nobel Prize winner in Economics 2003, on Cointegration Nassim Taleb on Black Swans Stephen Ross on Arbitrage Pricing Theory Emanuel Derman the Wall Street Quant Edward Thorp on Gambling and Trading Peter Carr the Wall Street Wizard of Option Symmetry and Volatility Aaron Brown on Gambling, Poker and Trading David Bates on Crash and Jumps Andrei Khrennikov on Negative Probabilities Elie Ayache on Option Trading and Modeling Peter Jaeckel on Monte Carlo Simulation Alan Lewis on Stochastic Volatility and Jumps Paul Wilmott on Paul Wilmott Knut Aase on Catastrophes and Financial Economics Eduardo Schwartz the Yoga Master of Quantitative Finance Bruno Dupire on Local and Stochastic Volatility Models

Evidence-Based Statistics: An Introduction to the Evidential Approach – from Likelihood Principle to Statistical Practice  provides readers with a comprehensive and thorough guide to the evidential approach in statistics. The approach uses likelihood ratios, rather than the probabilities used by other statistical inference approaches. The evidential approach is conceptually easier to grasp, and the calculations more straightforward to perform. This book explains how to express data in terms of the strength of statistical evidence for competing hypotheses.  The evidential approach is currently underused, despite its mathematical precision and statistical validity.  Evidence-Based Statistics  is an accessible and practical text filled with examples, illustrations and exercises. Additionally, the companion website complements and expands on the information contained in the book.  While the evidential approach is unlikely to replace probability-based methods of statistical inference, it provides a useful addition to any statistician’s “bag of tricks.” In this book:  It explains how to calculate statistical evidence for commonly used analyses, in a step-by-step fashion Analyses include: t tests, ANOVA (one-way, factorial, between- and within-participants, mixed), categorical analyses (binomial, Poisson, McNemar, rate ratio, odds ratio, data that’s ‘too good to be true’, multi-way tables), correlation, regression and nonparametric analyses (one sample, related samples, independent samples, multiple independent samples, permutation and bootstraps) Equations are given for all analyses, and R statistical code provided for many of the analyses Sample size calculations for evidential probabilities of misleading and weak evidence are explained Useful techniques, like Matthews’s critical prior interval, Goodman’s Bayes factor, and Armitage’s stopping rule are described Recommended for undergraduate and graduate students in any field that relies heavily on statistical analysis, as well as active researchers and professionals in those fields,  Evidence-Based Statistics: An Introduction to the Evidential Approach – from Likelihood Principle to Statistical Practice  belongs on the bookshelf of anyone who wants to amplify and empower their approach to statistical analysis.

Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics.  The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.

Risk Analysis, Second Edition Terje Aven, University of Stavanger, Norway A practical guide to the varied challenges presented in the ever-growing field of risk analysis. Risk Analysis presents an accessible and concise guide to performing risk analysis, in a wide variety of field, with minimal prior knowledge required. Forming an ideal companion volume to Aven's previous Wiley text Foundations of Risk Analysis, it provides clear recommendations and guidance in the planning, execution anduse of risk analysis. This new edition presents recent developments related to risk conceptualization, focusing on related issues on risk assessment and their application. New examples are also featured to clarify the reader's understanding in the application of risk analysis and the risk analysis process. Key features: Fully updated to include recent developments related to risk conceptualization and related issues on risk assessments and their applications. Emphasizes the decision making context of risk analysis rather than just computing probabilities Demonstrates how to carry out predictive risk analysis using a variety of case studies and examples. Written by an experienced expert in the field, in a style suitable for both industrial and academic audiences. This book is ideal for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and physical sciences. Managers facing decision making problems involving risk and uncertainty will also benefit from this book.