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  2. Try GuruFocus Google Sheets Add-on' DCF Calculator Template - AOL

    www.aol.com/news/try-gurufocus-google-sheets-add...

    Users can compute a stock's intrinsic value using Google Sheets. Skip to main content. News. 24/7 help. For premium support please call: 800-290-4726 more ways to reach us. Login / Join. Mail ...

  3. Value averaging - Wikipedia

    en.wikipedia.org/wiki/Value_averaging

    As illustrated in the above example, in contrast to dollar cost averaging, which mandates that a fixed amount of money be invested at each period, the value averaging investor may on occasion be required to withdraw from the portfolio to keep to the program. Value averaging was developed by former Harvard University professor Michael E. Edleson.

  4. Google Sheets - Wikipedia

    en.wikipedia.org/wiki/Google_Sheets

    Google Sheets is a spreadsheet application and part of the free, web-based Google Docs Editors suite offered by Google. Google Sheets is available as a web application; a mobile app for: Android, iOS, and as a desktop application on Google's ChromeOS. The app is compatible with Microsoft Excel file formats. [5]

  5. Method of averaging - Wikipedia

    en.wikipedia.org/wiki/Method_of_averaging

    The averaging method yields an autonomous dynamical system ˙ = (,,) =: ¯ which approximates the solution curves of ˙ inside a connected and compact region of the phase space and over time of /. Under the validity of this averaging technique, the asymptotic behavior of the original system is captured by the dynamical equation for y ...

  6. Dollar cost averaging - Wikipedia

    en.wikipedia.org/wiki/Dollar_cost_averaging

    Dollar cost averaging: If an individual invested $500 per month into the stock market for 40 years at a 10% annual return rate, they would have an ending balance of over $2.5 million. Dollar cost averaging (DCA) is an investment strategy that aims to apply value investing principles to regular investment.

  7. Inverse-variance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse-variance_weighting

    For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().