Thursday, March 10, 2011

CL charts












see this DOJI post for details

also good read , print this http://www.scribd.com/doc/7029006/2/Bull-Flag-Patterns-Continuation-Pattern , more importantly practice it ...
asr: see the powerful combination of
a) this DOJI patterns ( see scribd for full list to master)
b) add Volume spread analysis plug-in s/w of 'amibroker'
c) vantage point PHigh/Plow
d) both EOD and 5 min historic data stored in CSV files , and using sqlDB have queries like 7 continuous UPdays , what happened next ... then after 2 days down what happend Next ..
e) use options to buy earlier and use it as insurance ...
e) japanese candle stick plug of amibroker
f) my 'possible configuration of the day' analysis based on different conspiracy theory ...
what a powerful combinationn
( on 4/15/11 moring low was 107.12 , previous day low indicate low was 106.5 , so where can this go on friday when low is fixed 106.5, and currently at 107 , CL needs $2 range for the day it HAS to goup $2 even it goes down later ...)

asr wow: this has so many punch points for CL , KID/DOJI are master of these , now we know how KID is so successful ..

No, what I mean is that trading programs are programmed to try various price levels (previous bar highs/lows, previous pivot highs/lows, trend line touches, moving average touches, etc.) until they catch a level that holds. So if there's a clean channel, it's very likely that the channel lines will continue to be bought/sold until eventually there's a breakout one way or the other (today favored the bulls).

I've attached the 5-min chart with the bull flag channel. There were enough buyers at that lower TL to maintain the TL as support, at which point I imagine the majority of trend-following trading programs (those "bots") will buy until price hits the next key level, in this case the upper channel line, which held as resistance at first. Then there were enough buyers at the "second mouse" long entry level I described earlier to attract more buyers to position for a potential break of the channel (bull flag continuation breakout, the Bigsnack trade).

Notice that the touch to the lower channel line at 1:45pm ET @ 109.89 had the additional confluence of being a "previous resistance becomes support" level as well (top of the 10:55 - 11:20am range).

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here is 3/10/11 action chart , was on long 103.40 , 102.10 , 100.69 , 100.91 ( add 2 )
- final exit 103.80 all





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Event-Raise-Fall model: base on this model for OIL , once a event happens price raise ( like Alaska pipe line broken ) say raise is $3 , then when the issue settles after a week price will come back by losing $3 , it may come back immediatly after FALL of the incident

hidden price delayed realization theory: in the above example , after event winds down it may take few days for price to come back ,price will drop on the next event day such as EIA data down day , part of that $3 ( $1.5 ) will be added to the down side on that day , say that day down is $1 , then total of $2.5

- so for this record Retures EOD news and assign day price hike to events and follows when events fade price will drop
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4/10/11
- a day to day account of Gaza events , we need this kind of record for events , once the events are stored in simple TEXT based DB , these can be retrived to display on OUR charts

http://news.bbc.co.uk/2/hi/middle_east/7812290.stm




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asr: try this Logit method for CL different variable to determine Friday close based on previous days etc.. good learning , seems this kind of regression works better than simply doing this kind of analysis on charts . investiage


Next, the authors run a logit regression to determine how the laundry list of variables described above are related to the probability of a stock showing up as a short recommendation.
Abstract:

“We examine whether information arbitrageurs attempt to exploit the return predictability in valuation and fundamental signals. Using a unique database of short sale recommendations, we document that firm fundamentals, such as accruals, sales growth, gross-margin and SG&A, and valuation indicators, such as book-to-market ratio and return momentum, contain valuable information correlated with the trading behavior of short sellers. We show that our empirical model explaining short seller recommendations is successful in predicting both short interest and future returns for a broader sample in an out-of-sample period. We present an important application of the model in distinguishing between valuation and arbitrage-motivated short selling. Overall, these findings present additional insights into the decision process of short sellers and validate the importance of fundamental analysis in the information arbitrage process.”

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