Quote Originally Posted by Harry View Post
I have always wondered as to how the +/-1000 stocks/ETF's that compromise the 20DMF model were/are selected? The reason I ask is - would have removing and replacing (say even 10 for a 1% change in the composition) impact the calculations significantly? I know we don't want to backfit, but wonder about the impacts of a difference set on the overall 20DMF model? Same question goes for the 4 inverse ETF's - why choose these 4 versus other inverse ETF's?

I am sure these questions were answered long ago when you were building the model.
The 20DMF is a sectors based model. When I started working with it, I had about 60 sectors. The selection process was straightforward: whenever I could find at least 5 stocks in the same sector (searched through IBD, Yahoo and by reading the annual reports) I created a sector. Adding or retrieving a stock from a given sector has almost no bearing on the indicator, because each of the 96 sectors has an equal weight. Therefore, if there are let say 10 stocks in one sector, removing 10 from 10 different sectors would have much less than 1% impact on the general model. It is only if I started to completely remove or add many sectors that there would be an impact.

For example, yesterday, I added about 6 stocks in different sectors (Leisure equipment, drugs, etc). I do that only for sectors that include only five or six stocks, so that each stocks does not have a strong influence on the sector MF.

With this approach, a stock like AAPL, even though it moves its own MF sector by almost 80%, Its influence on the 20DMF is no more than 1/96

Regarding the four inversed ETFs, I just took those with the strongest volume. I selected double inversed, because traders would close position much quicker on these type of ETFs and hence, moves would be detected much quicker than on non-leveraged ETFs.


Pascal