
Preface
Decades ago, investors scrambled to get the smallest bit of "inside" knowledge from stock, bond, and other investment markets. Stock quotations had to be gleaned from a broker and yields were best found at the bank. A need for detailed statistics required either expensive market newsletters or a trip to the library—or both.
Today, the challenge is very different. The chore is to sort through the vast array of facts. There are figures available in the local newspaper, no less, the national financial newspapers—The Wall Street Journal, Barron's, Investor's Business Daily—and in investment magazines—Forbes, Money, Smart Money, Worth—on television— CNNfn, CNBC—on a home computer and on the Internet. Then, of course, there is the information contained in the many market advisoiy services that still thrive.
Consider this: A typical major city newspaper contains quotations on more than 8000 stocks, bonds, and mutual funds and more than 100 indexes. Add to that expanded coverage of economic statistics or the added availability of such information on television, radio, and via online information services accessed by home computers. Most investors are not able to decipher what is up from what is down.
707 Investments Tools for Buying Low and Selling High is designed to help the investor cut through all the statistical noise. It gets a reader quickly to the best financial barometers and helps him or her make informed investment decisions.
More than just an ordinary investment dictionary, 707 Investment Tools analyzes, in a concise style, the vaiious investment vanes—from stock indexes to measures of housing affordability to leading economic indicators. The reader will learn what these measures are, who is compiling them, where they are easily found (publications, media, more) and how they can, or cannot, be used to guide investment decisions. All in a handy, carry-along format.
In the ongoing complex investment climate we live in, those who understand and can use such investment tools will be the ones who succeed.
The authors are grateful to Allison Shim for her enormous word-processing and spreadsheet assistance and Marianne, Rachel, and Jake Lansner for being so understanding during this project.
Jae K. Shim, Los Alamitos, CA
Jonathan Lansner, Trabuco Canyon, CA
Jonathan Lansner, Trabuco Canyon, CA
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