ludowillems
111 posts
msg #67039
- Ignore ludowillems |
9/7/2008 9:20:31 AM
Dear all,
I would like to filter out the sector that gained/lost the most over the last n-periods, show the results in columns (1 week-1month-1 quarter performance), and from there on, filter on industries in a particular sector, to end up finally with a simlist.
To illustrate my question, go www.finviz.com" and click "groups" on the main page.
Thanks for helping me out with this
Ludo
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decipherlinda
133 posts
msg #67153
- Ignore decipherlinda |
9/11/2008 12:06:51 AM
Hi Ludo. I don't have time to go to your referrenced site so this probably isn't exactly what you want, but am attaching a filter I use to evaluate various industries. I go to the industries list on SF's home page and pull out those that have done well in the last week and then apply this filter to them. For each stock it shows % change for the last five days, a summation for the last 2 weeks, weekly for the last 4 weeks and a summation for the last month. I have 2 other filters that get it thru the last 5 months, if you're interested. I download the results of the 3 filters and cut and past (an easy job) to get a clear picture. Then I go to stockcharts.com, select the Perf charts and key in each of the stocks (10 at a time) to whittle down the strongest performers (no subscription necessary -- I think). I found that very often there will be one very cheap stock that has skewed the results for the entire industry which makes this kind of analysis very important. Sorry, I can't quickly find my notes on how to make this filter clickable. Linda
set{C1Z, close / close yesterday}
set{PctZ, C1Z -1}
set{Today, PctZ * 100}
add column Today
set{C1A, close 1 day ago / close 2 days ago}
set{Pct1, C1A -1}
set{C1, Pct1 * 100}
add column C1
set{C2A, close 2 days ago / close 3 days ago}
set{Pct2, C2A -1}
set{C2, Pct2 * 100}
add column C2
set{C3A, close 3 days ago / close 4 days ago}
set{Pct3, C3A -1}
set{C3, Pct3 * 100}
add column C3
set{C4A, close 4 days ago / close 5 days ago}
set{Pct4, C4A -1}
set{C4, Pct4 * 100}
add column C4
set{W1A, close / close 5 days ago}
set{Pct5, W1A -1}
set{ThsW, Pct5 * 100}
add column ThsW
set{W2A, close 5 days ago / close 10 days ago}
set{Pct6, W2A -1}
set{W2, Pct6* 100}
add column W2
set{W3A, close 10 days ago / close 15 days ago}
set{Pct7, W3A -1}
set{W3, Pct7 * 100}
add column W3
set{W4A, close 15 days ago / close 20 days ago}
set{Pct8, W4A -1}
set{W4, Pct8 * 100}
add column W4
set{M1B, close / close 20 days ago}
set{Pct9, M1B -1}
set{M1, Pct9 * 100}
add column M1
/*and apply to watchlist(Airlines8508)*/
and apply to industry(Surety Title Insurance)
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decipherlinda
133 posts
msg #67154
- Ignore decipherlinda |
9/11/2008 2:29:46 AM
One last thought. My hypothesis at this point, after studying some industries using my filters is that when an industry is out-of-play, some of the stocks will be up and many will be down. When 90% of the stocks in a small industry (say 20) are all up or all down on any given day or week, the industry is in-play. For example, Surety Title Insurance week of 7/18 to 7/24, 14 of 15 stocks were up. Three of them > 70% for the week. This was the start of Surety's recent run.
For industries with many stocks, I would expect the same principle but with less than 90% of the stocks moving together.
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