Microsoft Excel for Stock and Option Traders: Build Your Own Analytical Tools for Higher Returns

eBook Details:

  • Hardcover: 208 pages
  • Publisher: FT Press; 1st edition (April 28, 2011)
  • Language: English
  • ISBN-10: 0137131828
  • ISBN-13: 978-0137131822

eBook Description:

Trade More Profitably by Exploiting Excel’s Powerful New Statistical and Data Mining Tools!

  • Uncover subtle anomalies and distortions that signal profit opportunities
  • Create powerful new custom indicators, alerts, and trading models
  • Visualize and analyze huge amounts of trading data with just a few clicks
  • Powerful techniques for every active investor who can use Excel

Now that high-speed traders dominate the market, yesterday’s slower-paced analysis strategies are virtually worthless. To outperform, individual traders must discover fleeting market trends and inefficiencies and act on them before they disappear.

Five years ago, this required multimillion-dollar data mining and analytical infrastructures. Today, you can do it with Microsoft Excel, a powerful PC, and this book.

Step by step, world-class trader Jeff Augen shows how to use Excel 2007 or 2010 to uncover hidden correlations and reliable trade triggers based on subtle anomalies and price distortions…create and test new hypotheses others haven’t considered…visualize data to reveal insights others can’t see!

From the Back Cover

Microsoft Excel for Stock and Option Traders: Build Your Own Analytical Tools for Higher Returns

There’s only one way to gain a consistent edge in today’s high-speed markets: adopt the same advanced data mining and analysis techniques the institutions use. Fortunately, with Microsoft Excel and a modern PC, you can do just that. In this book, Jeff Augen covers a variety of approaches for systematically improving your trades by exploiting Excel’s most powerful new features.

Augen demystifies key analytical concepts and teaches all the Excel skills you’ll need. Using realistic examples, he explains everything from simple conditionals and expressions to sophisticated VBA macro programming.

You’ll learn to create new indicators and alerts that identify high-profit opportunities…perform statistical analyses to back-test strategies more accurately…validate, invalidate, or tune combinations of indicators across any time frame…quickly visualize enormous datasets, so hidden trends jump out at you.

Own Excel? Use a trading platform? You already have the tools to gain a powerful trading advantage. Get this book–and put those tools to work.

  • Use Excel 2007/2010 to systematically improve the way you analyze trades
    Translate complex trading hypotheses into simple, testable Excel models

  • Uncover market distortions in time to profit from them
    Profit from inefficiencies that disappear in hours, minutes, or even seconds

  • Identify new correlations the market hasn’t noticed
    Perform “experiments” of virtually unlimited size, number, or complexity

Author Info

Jeff Augen

Jeff Augen, currently a private investor and writer, has spent more than a decade building a unique intellectual property portfolio of algorithms and software for technical analysis of derivatives prices. His work includes more than one million lines of computer code reflecting powerful new strategies for trading equity, index, and futures options.

Augen has a 25-year history in information technology. As a co-founding executive of IBM’s Life Sciences Computing business, he defined a growth strategy that resulted in $1.2 billion of new revenue, and he managed a large portfolio of venture capital investments. From 2002 to 2005, Augen was President and CEO of TurboWorx, Inc., a technical computing software company founded by the chairman of the Department of Computer Science at Yale University. He is author of Bioinformatics in the Post-Genomic Era: Genome, Transcriptome, Proteome, and Information-Based Medicine (WOW! eBook, 2004). Much of his current work on options pricing is built on algorithms for predicting molecular structures that he developed as a graduate student.

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