Optimal Portfolio Modeling, CD-ROM includes Models Using Excel and R: Models to Maximize Returns and Control Risk in Excel and R (Wiley Trading) - Hardcover

McDonnell, Philip

Hardcover

ISBN 10: 0470117664 ISBN 13: 9780470117668

Verlag: Wiley, 2008

Inhaltsangabe

Optimal Portfolio Modeling is an easily accessible introduction to portfolio modeling for those who prefer an intuitive approach to this discipline. While early chapters provide engaging insights on the statistical properties of markets, this book quickly moves on to illustrate invaluable trading and risk control models based on popular programs such as Excel and the statistical modeling language R. This reliable resource presents modeling formulas that will allow you to effectively maximize the performance, minimize the drawdown, and manage the risk of your portfolio.

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Über die Autorin bzw. den Autor

Philip J. McDonnell (Sammamish, WA) is a trader and software and trading methodologies developer who has created proprietary data collection and analysis tools for real time analysis of market direction and stock selection with an emphasis on options analysis. Prior, he handled network operations for a venture capital incubator, The Inception Group, and developed and sold an options analysis software package. He has also developed option risk management software for Charles Schwab & Co. McDonnell served as research assistant at University of California, Berkeley, School of Business, under Victor Niederhoffer. He holds degrees in mathematics and computer science from University of California, Berkeley.

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Praise for Optimal Portfolio Modeling

"All too often, analysis ends with security selection. However, savvy investors understand that security selection is where analysis starts. In this important contribution to the literature, Mr. McDonnell discusses position sizing, portfolio construction, utility, money management, and much more, all of which can make important contributions to your total return."
―John Bollinger, CFA, CMT, www.BollingerBands.com

"This book provides a cornucopia of practical techniques with readily accessible statistical backup for maximizing returns from systematic trading."
―Victor Niederhoffer, author of The Education of a Speculator and Practical Speculation

"What happens when stock market prices collide with a mathematician that really trades? Simple: myths are dispelled and truths are established. You are sure to learn from this book."
―Larry Williams, author of Trading Stocks & Commodities with the Insiders: Secrets of the COT Report, and Long-Term Secrets to Short-Term Trading

"I can heartily recommend this wonderful, well-organized, and well-thought-out book by a very pragmatic and bright guy. It will give the reader an excellent understanding of the mathematical nature of portfolio modeling."
―Ralph Vince, author of The Handbook of Portfolio Mathematics: Formulas for Optimal Allocation & Leverage

Aus dem Klappentext

Praise for Optimal Portfolio Modeling

"All too often, analysis ends with security selection. However, savvy investors understand that security selection is where analysis starts. In this important contribution to the literature, Mr. McDonnell discusses position sizing, portfolio construction, utility, money management, and much more, all of which can make important contributions to your total return."
—John Bollinger, CFA, CMT, www.BollingerBands.com

"This book provides a cornucopia of practical techniques with readily accessible statistical backup for maximizing returns from systematic trading."
—Victor Niederhoffer, author of The Education of a Speculator and Practical Speculation

"What happens when stock market prices collide with a mathematician that really trades? Simple: myths are dispelled and truths are established. You are sure to learn from this book."
—Larry Williams, author of Trading Stocks & Commodities with the Insiders: Secrets of the COT Report, and Long-Term Secrets to Short-Term Trading

"I can heartily recommend this wonderful, well-organized, and well-thought-out book by a very pragmatic and bright guy. It will give the reader an excellent understanding of the mathematical nature of portfolio modeling."
—Ralph Vince, author of The Handbook of Portfolio Mathematics: Formulas for Optimal Allocation & Leverage

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Optimal Portfolio Modeling

Models to Maximize Returns and Control Risk in Excel and R, CD-ROM includes Models Using Excel and RBy Philip McDonnell

John Wiley & Sons

Copyright © 2007 Philip McDonnell
All right reserved.
ISBN: 978-0-470-11766-8

Chapter One

Modeling Market Microstructure-Randomness in Markets

Traditionally, portfolio modeling has been the domain of highly quantitative people with advanced degrees in math and science. On Wall Street, such people are commonly called rocket scientists. Optimal Portfolio Modeling was written to provide an easily accessible introduction to portfolio modeling for readers who prefer an intuitive approach. This book can be read by the average intelligent person who has only a modest high school math background. It is designed for people who wish to understand rocket science with a minimum of math.

The focus of this book is on money management. It is not a book about market timing, nor is it designed to help you pick stocks. There are numerous other books that address those subjects. Rather, this work will show the reader how to define models to help manage money and control risk. Stock selection is really just the details. The big picture is actually about achieving your overall portfolio goals.

Included with this book is a CD-ROM that includes numerous examples in both Excel and R, the statistical modeling language. The book assumes the user has a beginner's level knowledge of Excel and focuses mainly on those specific areas that apply to portfolio modeling and optimization. There are many books that offer an introduction to Excel, and the interested reader is encouraged to investigate those.

R is an open-source language that offers powerful graphics and statistics capabilities. Two appendices in this book offer introductory support for users who wish to download R at no cost and learn how to program. Because R is powerful, many functions and graphs can be done with very few command lines. Often, only a single line will create a graph or perform a statistical analysis.

The overriding philosophy of all of the examples is simplicity and ease of understanding. Consequently, each example typically focuses on a single simple problem or calculation. It is the job of the computer to know how to perform the calculations. The user only needs to know how to invoke the right computer function and to understand the results. Understanding and intuition are the primary goals of this book.

This chapter introduces the important background of market microstructure and randomness. This is a foundation for the ideas developed later in this book. The discussion starts with a thorough introduction to the idea of randomness and what a random walk is. The topic of randomness is presented as an essential element in understanding how and why a portfolio works. After all, the primary rationale for a portfolio is intelligent diversification.

From there, the book moves to a discussion of market microstructure and how it affects the operation of markets. Later, the reader is introduced to the efficient market hypothesis, along with its history and development, starting with early pioneers in the field. Augmenting this is the discussion on arbitrage pricing theory and its modern applications. This latter topic shows how the market identifies and eliminates any risk, less arbitrage opportunities.

Trading speculative markets has always been difficult. Over the years, several studies have shown that some 70 to 80 percent of all mutual funds underperform the averages. A study by Professor Terrance Odean of the University of California at Berkeley demonstrated that most individual investors actually lose money. This study analyzed thousands of real-life individual investor brokerage accounts. Thus, it provides a comprehensive look at how real individual traders operate. The inescapable conclusion is that both professional and individual investors find that trading the markets is challenging.

Successful trading is predicated on one thing. Traders must predict the direction of price changes in the future. At a minimum, a successful trader must predict prices so that each trade has an expectation of yielding a profit. This does not mean that each trade must be successful, but, rather, that a succession of trades would usually be expected to result in a profit. This should not be taken to mean that having a positive expectation for each trade is the only thing a successful trader needs. The astute reader will note that the use of words such as usually, average, and expectation naturally implies that the art of forecasting is far from perfect. In fact, it is best studied from a statistical perspective with a view to identifying what is random and what is predictable.

In a recent 500-day period, the stock market as measured by the Standard and Poor's 500 index was generally a modestly up market. A statistical analysis of the daily compounded returns for the period shows:

Average daily return: .038 percent Standard deviation: .640 percent Probability of rise: 56 percent

The standard deviation is simply a measure of the variability of returns around the average. From this simple analysis, we can make some interesting observations:

1. The average daily return is small with respect to the standard deviation.

2. The daily variability is relatively large, at 16 times the return.

3. The market went up 56 percent of the time, or slightly more than half. It also went down the other 44 percent of the days. So even during up markets, the number of up days is only slightly better than 50-50.

4. The variability completely swamps the average return.

Observations such as these have led many early researchers in finance to propose a model for the markets that explicitly embraces randomness at its very core. A cornerstone of this idea is that markets represent all of the knowledge, information, and intelligent analysis that the many participants bring to bear. Thus, the market has already priced itself to correspond with the sum of all human knowledge. In order to outperform the market, a trader must have better information or analysis than the rest of the participants collectively. It would seem the successful trader must be smarter than everyone else in the world put together.

THE RANDOM WALK MODEL

To the typical layman, the random walk model is the best-known name for the idea that markets are very good at pricing themselves so as to remove excess profit opportunities. The academic community generally prefers the description the efficient market hypothesis (EMH). Either way, the idea is the same-it is very difficult to outperform the market. If someone does outperform, then it is likely only attributable to mere luck and not skill.

The history of the EMH is a rather long one. The first known work was by Louis Bachelier in 1900, in which he posited a normal distribution of price changes and developed the first-known option model based on the idea of a normal random walk (see Figure 1.1). His seminal paper in the field was quickly forgotten for some 60 years. As an interesting side note, the mathematics that Bachelier developed was essentially the same analysis that Albert Einstein reinvented in 1906 in his...

Details zur Ausgabe

• Verlag: Wiley
• Erscheinungsdatum: 2008
• Sprache: Englisch
• ISBN 10: 0470117664
• ISBN 13: 9780470117668
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 312
• Kontakt zum Hersteller: Wiley-VCH GmbH; product_safety@wiley.com; ; Boschstrasse 12; Weinheim; 69469; Deutschland