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The present book contains much more materials than the author's previous book The Science of Financial Market Trading. Spectrum analysis is again emphasized for the characterization of technical indicators employed by traders and investors. New indicators are created. Mathematical analysis is applied to evaluate the trading methodologies practiced by traders to execute a trade transaction. In addition, probability theory is employed to appraise the utility of money management techniques.The book: identifies the faultiness of some of the indicators used by traders and accentuates the potential of wavelets as a trading tool; describes the scientific evidences that the market is non-random, and that the non-randomness can vary with respect to time; demonstrates the validity of the claim by some traders that, with good money management techniques, the market is still profitable even if it were random; and analyzes why a popular trading tactic has a good probability of success and how it can be improved.
The present book contains much more materials than the author's previous book The Science of Financial Market Trading. Spectrum analysis is again emphasized for the characterization of technical indicators employed by traders and investors. New indicators are created. Mathematical analysis is applied to evaluate the trading methodologies practiced by traders to execute a trade transaction. In addition, probability theory is employed to appraise the utility of money management techniques. The book identifies the faultiness of some of the indicators used by traders and accentuates the potential of wavelets as a trading tool; describes the scientific evidences that the market is non-random, and that the non-randomness can vary with respect to time; demonstrates the validity of the claim by some traders that, with good money management techniques, the market is still profitable even if it were random; and analyzes why a popular trading tactic has a good probability of success and how it can be improved.
In this book, Dr Mak views the financial market from a scientific perspective. The book attempts to provide a realistic description of what the market is, and how future research should be developed. The market is a complex phenomenon, and can be forecasted only with errors — if that particular market can be forecasted at all.The book reviews the scientific literatures on the financial market and describes mathematical procedures which demonstrate that some markets are non-random. How the markets are modeled — phenomenologically and from first principle — is explained.It discusses indicators, which are quite objective, rather than price patterns, which are rather subjective. Similarities between indicators in market trading and operators in mathematics are noted, and particularly, between oscillator indicators and derivatives in Calculus. It illustrates why some indicators, e.g., Stochastics, have limited usage. Several new indicators are designed and tested on theoretical waveforms to check their validity and applicability. The indicators have a minimal time lag, which is significant for trading purposes. Common market behaviors like divergences between price and momentum are explained. A skipped convolution technique is introduced to allow traders to pick up market movements at an earlier time. The market is treated as a nonlinear phenomenon. Forecasting of when the market is going to turn is emphasized.
Financial markets are not predictable, let alone controllable. The one thing traders and investors can control is their trading tactics, where some can have higher probability of profitability than others. This book explains, by using phase analysis, why some of the indicators, and trading tactics would work better than others, and why some indicators and trading tactics would perform poorly. Emphasis is placed on Awesome Oscillator and Accelerator Oscillator, which are based on Simple Moving Average, a popular tool employed by traders. They are then compared to Moving Average Convergence-Divergence (MACD) and MACD Histogram (MACDH), which are based on exponential moving averages. By varying the parameters of MACD and MACDH, one can change the phase or time delay, and possibly make a larger profit. This book is for practitioners, and includes all MATLAB programs used in the book.
Explore the foundations of modern finance with this intuitive mathematical guide In Mathematical Techniques in Finance: An Introduction, distinguished finance professional Amir Sadr delivers an essential and practical guide to the mathematical foundations of various areas of finance, including corporate finance, investments, risk management, and more. Readers will discover a wealth of accessible information that reveals the underpinnings of business and finance. You’ll learn about: Investment theory, including utility theory, mean-variance theory and asset allocation, and the Capital Asset Pricing Model Derivatives, including forwards, options, the random walk, and Brownian Motion Interest rate curves, including yield curves, interest rate swap curves, and interest rate derivatives Complete with math reviews, useful Excel functions, and a glossary of financial terms, Mathematical Techniques in Finance: An Introduction is required reading for students and professionals in finance.
This book explores the mathematics that underpins pricing models for derivative securities such as options, futures and swaps in modern markets. Models built upon the famous Black-Scholes theory require sophisticated mathematical tools drawn from modern stochastic calculus. However, many of the underlying ideas can be explained more simply within a discrete-time framework. This is developed extensively in this substantially revised second edition to motivate the technically more demanding continuous-time theory.
Originally published in 2003, Mathematical Techniques in Finance has become a standard textbook for master's-level finance courses containing a significant quantitative element while also being suitable for finance PhD students. This fully revised second edition continues to offer a carefully crafted blend of numerical applications and theoretical grounding in economics, finance, and mathematics, and provides plenty of opportunities for students to practice applied mathematics and cutting-edge finance. Ales Cerný mixes tools from calculus, linear algebra, probability theory, numerical mathematics, and programming to analyze in an accessible way some of the most intriguing problems in financial economics. The textbook is the perfect hands-on introduction to asset pricing, optimal portfolio selection, risk measurement, and investment evaluation. The new edition includes the most recent research in the area of incomplete markets and unhedgeable risks, adds a chapter on finite difference methods, and thoroughly updates all bibliographic references. Eighty figures, over seventy examples, twenty-five simple ready-to-run computer programs, and several spreadsheets enhance the learning experience. All computer codes have been rewritten using MATLAB and online supplementary materials have been completely updated. A standard textbook for graduate finance courses Introduction to asset pricing, portfolio selection, risk measurement, and investment evaluation Detailed examples and MATLAB codes integrated throughout the text Exercises and summaries of main points conclude each chapter
This book is among the first to present the mathematical models most commonly used to solve optimal execution problems and market making problems in finance. The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making presents a general modeling framework for optimal execution problems-inspired from the Almgren-Chriss app
Modern Finance Overlaps With Many Fields Of Mathematics, And For Students This Can Represent Considerable Strain. Mathematical Techniques In Finance Is An Ideal Textbook For Masters Finance Courses With A Significant Quantitative Element While Also Being Suitable For Finance Ph.D. Students. Developed For The Highly Acclaimed Master Of Science In Finance Program At Imperial College London, It Offers A Carefully Crafted Blend Of Numerical Applications And Theoretical Grounding In Economics, Finance, And Mathematics.In The Best Engineering Tradition, Ale Cerný Mixes Tools From Calculus, Linear Algebra, Probability Theory, Numerical Mathematics, And Programming To Analyze In An Accessible Way Some Of The Most Intriguing Problems In Financial Economics. Eighty Figures, Over 70 Worked Examples, 25 Simple Ready-To-Run Computer Programs, And Several Spreadsheets Further Enhance The Learning Experience. Each Chapter Is Followed By A Number Of Classroom-Tested Exercises With Solutions Available On The Book'S Web Site.Applied Mathematics Is A Craft That Requires Practice This Textbook Provides Plenty Of Opportunities To Practice It And Teaches Cutting-Edge Finance Into The Bargain. Asset Pricing Is A Common Theme Throughout The Book; And Readers Can Follow The Development From Discrete One-Period Models To Continuous Time Stochastic Processes. This Textbook Sets Itself Apart By The Comprehensive Treatment Of Pricing And Risk Measurement In Incomplete Markets, An Area Of Current Research That Represents The Future In Risk Management And Investment Performance Evaluation.This Special Low-Priced Edition Is For Sale In India, Bangladesh, Bhutan, Maldives, Nepal, Myanmar, Pakistan And Sri Lanka Only.
the mathematics of financial modeling & investment management The Mathematics of Financial Modeling & Investment Management covers a wide range of technical topics in mathematics and finance-enabling the investment management practitioner, researcher, or student to fully understand the process of financial decision-making and its economic foundations. This comprehensive resource will introduce you to key mathematical techniques-matrix algebra, calculus, ordinary differential equations, probability theory, stochastic calculus, time series analysis, optimization-as well as show you how these techniques are successfully implemented in the world of modern finance. Special emphasis is placed on the new mathematical tools that allow a deeper understanding of financial econometrics and financial economics. Recent advances in financial econometrics, such as tools for estimating and representing the tails of the distributions, the analysis of correlation phenomena, and dimensionality reduction through factor analysis and cointegration are discussed in depth. Using a wealth of real-world examples, Focardi and Fabozzi simultaneously show both the mathematical techniques and the areas in finance where these techniques are applied. They also cover a variety of useful financial applications, such as: * Arbitrage pricing * Interest rate modeling * Derivative pricing * Credit risk modeling * Equity and bond portfolio management * Risk management * And much more Filled with in-depth insight and expert advice, The Mathematics of Financial Modeling & Investment Management clearly ties together financial theory and mathematical techniques.