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Previously published as How to Build High Performance Stock Portfolios by David Brown.

Turn NASA Precision into Stock Market Profits

What if you could apply the same scientific method that landed men on the moon to grow your wealth in the stock market?

In Moon Rocks to Power Stocks, former NASA engineer and portfolio manager David Brown reveals the exact, model-driven strategies that have consistently outperformed the market for over 20 years. Combining data, discipline, and decades of real-world experience, Brown shows you how to build wealth with confidence without gambling on "hot tips" or meme stocks.

Inside you'll discover:

• A proven step-by-step process to find stocks with the greatest potential to beat the market

• How to build professional-grade portfolios for Growth, Value, Dividend, and Small Cap investing styles

• The nine powerful factors that predict strong stock performance -- and how to use them

• How to manage risk, protect your capital, and stay on track during volatile markets

• Why compounding returns can transform your financial future (and how to make it work for you)

• Real insights from NASA and Wall Street that show how disciplined systems beat emotion-driven investing

Who This Book Is For:

• Individual investors who want to grow wealth steadily over time

• Beginners looking for a clear, scientific roadmap instead of random stock tips

• Experienced investors ready to sharpen their process with proven methods

• Wealthy investors and retirees who want to protect their portfolios while aiming for superior returns

• Anyone curious how NASA-level discipline can boost investing confidence

Whether you're new to investing or ready to take control of your portfolio, this book will teach you how to think like a scientist and invest like a professional.

Stop guessing. Start investing with a proven plan.

Get your copy of Moon Rocks to Power Stocks today and build a portfolio designed to outperform.

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  • Text-to-Speech: Disabled
  • Lending: Disabled
  • Print Length: 182 Pages
  • File Size: 36 KB

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