Skip to content

Investor IQ New Analytics

June 24, 2019

We have added some new analytics to the Investor IQ report. The signals are generated using a composite of 28 different momentum and trend-following signals over time frames ranging from 1-12 months. The number of buy signals determines whether the overall signal is “buy”, “hold” or “sell.” The “Trend Strength” is a new feature which shows the percentage of buy signals across the 28 different momentum and trend systems. This allows users to differentiate between the strength of the trend across ETFs or stocks. The “Volatility Score” is also a new feature which shows the relative volatility ranking (low ranking=lower volatility) from 0-100 across all ETFs or stocks. This can provide insight into relative risk and also allow users to form lower volatility portfolios with relative ease. A visual of the new output can be seen below:

6 Comments leave one →
  1. Thomas Pasturel permalink
    June 25, 2019 1:43 am

    You’re definitely branching out into software. Go fintech Varadi 😉

  2. Damian Roskill permalink
    June 30, 2019 5:12 pm

    Good stuff as usual David – one suggestion: show the change from the prior week. Which were added to, say, the buy focus list. Hope all is well!

    • david varadi permalink*
      July 2, 2019 11:00 am

      Thanks Damian good to hear from you and hope you are well also. That is a good suggestion, I will try to incorporate it in the next couple weeks.

  3. July 6, 2019 11:59 am

    Longstanding and sincere admiration for your work, David. I’d like to use some of the insights gained from your model. How often is this updated? (Would it be possible to add a simple line of code, at the top, that says “Last updated: [Date]”?

    • david varadi permalink*
      July 6, 2019 3:57 pm

      Thanks Stephen, much appreciated. I think that is a good suggestion and easy to incorporate.
      best regards,

  4. July 8, 2019 8:54 am


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: