Tag Archives: asset allocation. tutorial. posting

We’re almost there … plus an asset allocation tutorial posting!

Hi there,

I’ve just posted an advanced 35 minute video to compare two asset allocation algorithms: mean absolute deviation and minimum maximum asset allocation.

Each has their strengths and weaknesses, but together they give you an excellent, emotion-free way to determine the best risk vs. reward allocation in your portfolio.

And do you know how to use the ‘efficiency frontier’ of various stock symbols (or any market set) with risk versus return? In the video, I apply the efficiency frontier for both the mean absolute deviation and the minimum maximum asset allocation for a sample portfolio.

By the time you’re done watching, you’ll understand exactly how to use either of these algorithms. And you’ll have all the R source code you need to actually begin using them.

I’m excited about this completed video, because we’re now very close to completing our R source code walk-throughs with the 14 most popular market forecasting models out there. We’ll be at the next step in our 7 point plan before you know it.

1.    The new Q&A section for building community is live already. Just press Q? or Q’s at the top of the Private section to get started. If you’re working on something and need an answer from another member (or me), we can all help each other out.

2.    Membership webinars are under way. In fact, I’ve just completed our first live webinar for Premium Members. This will be evolving into a weekly series of webinar for my membership community. I’ll send out a schedule once the next one is set.

3.    We’re here right now: more and more R/Matlab model coding walkthroughs have been posted. These include the most popular techniques you’ve asked for after I sifted through recent poll results.

And here’s what’s coming ASAP:

4.    The best trading platform has been finally confirmed so look out for demos on integrating with R for the new models.

5.    Demos will be shown for our upcoming private network with an internal cluster for parallelizing heavy number crunching simulations within these models.

6.    After that, an exhausting comparison will be under way to focus on most profitable models.

7.    And finally, we’ll be embarking upon an aggressive paper trading campaign with the above technology and models once built.

Join today, and you’ll get it all. Every tutorial, all the R code, and every tip and trick I know.

— > Get immediate access here.<–

Membership Benefits here.

Good trading,
Quantlabs.net Editor
“Those that know, don’t tell. Until now.”

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!