CrystalVol : The Ultimate Forbidden Fruit. Financial Predictions For 100 Markets and ETFS November 16 , 2009
BrainCapital Technologies (S) Pte Ltd
Smashwords Edition
Copyright 2009 BrainCapital Technologies (S) Pte Ltd
Smashwords Edition, License Notes
This ebook is licensed for your personal enjoyment only. This ebook may not beresold or given away to other people. If you would like to share this book with another person, please purchase an additional copy for each person you share it with. If you’re reading this book and did not purchase it, or it was not purchased for your use only, then you should return to Smashwords.com and purchase your own copy. Thank you for respecting the hard work of this author
Wealth Warning : Eating the Ultimate Forbidden Fruit may make you Seriously Rich.
Ultra High Finance For Ultra High Net Worths
& Hedge Fund Managers
Visit http://www.dealingmachines.com
Copyright © BrainCapital Technologies (S) Pte Ltd
This book is dedicated to
Dr. Gerald Chan ,
Dr. Bill Fung
And All My Hedge Fund Clients
Synopsis:In a nutshell . Using hybrid artificial intelligence technologies , we run billions of computations and do a prediction ranking of all the stocks in our universe . We use the same methodology Google uses in its PageRank Technology by assigning a vote for the most commonly referenced page . Here we assign a U vote for a Up prediction vs a D vote for a Down prediction . Then we make a Overall Summary Prediction Score to decide if equity markets are generally going up to Heaven or coming down to Hell .All the prediction rankings are laid out in a stock almanac format thus creating an encyclopedia of prediction rankings with the Stock Symbol,Prediction Date ,Price Level prediction is made from and finally Prediction Ranking B which measures Prediction ranking from 1 to 6 days and Prediction Ranking C which measures prediction Ranking from 3 to 9 days . Inevitably with financial markets , some overlap would occur and we just need to be roughly correct as we know that any Prediction Ranking above 33 level , 33U or 33D is valuable as the probability is higher than 66 percent for the prediction to come true . Choose the highest probability ranking stocks above 33U to go long and the highest probability ranking stocks 33D and above to go short . For stocks with a neutral prediction ranking use the Overall Summation Prediction Score to determine overall Prediction Score for the whole market and use it as a proxy for stocks with prediction ranking of neutral .And finally if we lay out all the signals and trade all the signals , we get a straight equity line sloping north and upwards with hit rate of more than 70 percent . and equity returns in excess of 20 percent for each year in the last 21 years using Dow Jones represented by ^DJI and Volatility represented by ^VXO
.
“ FANTASTIC !
…If there ever is an Oriental Alchemist of Finance , David Lee certainly qualifies as one . His Volatility Models are believed to be more than 70 percent accurate , I personally found them to be even pin point accurate and hugely profitable .
In the last few years , when many models fail , Braincap Volatility Models held up spectacularly well .In Sept 4 , a long call in Hang Seng Index till September 11 2009 was worth more than a 1000 points .
His 2 Black Swan Events highlighted in the Training Seminar book in July and August 2009 did spectacularly well . It turned 10c to 2 dollars within days .
His Basic Models have been well researched and supported in many scientific journals , namely when people buy , they do slowly as greed slowly creeps in . But when they do sell , they do in great Fear and HUGE volatility .
David Lee 's Contribution to the Financial World is to use Maths to detect spikes in Volatility as sell Signals and slow drops in Volatility as Buy signals . He found a way to quantify these signals and lay them over a 21 year track record to show a upward sloping equity line .
For that , I salute him . “
… Product and Book Review by David LCH , CEO , Hedge Fund Manager
Introduction. Introducing DealingMachines For Banks, Hedge Funds and Program Funds. Powered by Hybrid Neural Nets Technologies and Fuzzy logic, It can make a Billion Computations to give you the Best possible price Scenarios. When all agree, you can be sure that it is the best way to trade the market.Used by One of the Top Program Traders in the World and a select list of MNC Foreign Exchange Banks, this Technology is now available for use on the mobile platform for Iphones and Blackberry .
History. The history of BrainCapital technologies has its humble beginnings in 1988 . David Lee secured a Singapore Merchant Banking Scholarship which led to stints in Goldman Sachs New York and trips to Chicago Trading Houses . This helped to incubate an idea to develop a machine driven program-trading software for foreign exchange.
David with help from scientists came up with the first version a couple of years later and subsequently in April 1993, made a presentation of the model and findings at the SECOND ANNUAL INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS ON WALL STREET. The underlying pattern recognition technology has undergone much refinement ever since.Between 1993 and 1997, the software was used extensively by program traders at Hong Kong Bank, Swiss Bank Corp and BHF Bank.Subsequently , a governmental grant and venture capital group funding by Boston based VC followed in 1998 .Since then , Braincapital technologies has been used by several MNC banks and also a Top 10 program trader who traded 12 percent of stocks on the NYSE. The technologies use state of the art artificial intelligent technologies like neural nets , fuzzy logic and genetic algorithms . Through millions of computational intensive mathematical calculations , the technologies output a 6 step best scenario for each individual stock , bond or currency .Statistically , it can be verified that the technologies has a 65 to 80 percent accuracy rate of predicting price momentum ( speed of trend ) for intraday , daily and weekly time spans. Viceroy International Limited in 2002 completed the 100 percent buy back of BrainCapital technologies .
The Rationale for Predicting Price Patterns.
To develop the perfect Stock Market Machine may be an impossible task but with better technologies and mathematics , we can strive for the next best thing .
Towards this , we develop our serving infrastructure and breakthrough BQT ™ technology to continuously search for price patterns within the worlds Top 1881 Stocks and changed the way stock markets analyses are being conducted.
From the beginning, our developers recognized that providing the fastest and most accurate results required a new kind of rigorous approach that is highly robust and can withstand the most stressful periods of market trading .
To do this , we maximize the use of today ‘s high speed computers and use more than 200 signals in our (patent pending ) BQT ™ algorithm . Patiently , all 1881 Key Stocks of the World are put through our pattern recognition machines and analyzed individually
The importance of each prediction signal generated is then cast as an Independent Vote . And as all the Votes are independently generated and gathered from 1881 stocks worldwide , the Summation of all Signals are collated and considered to have greater value than each individual prediction signal . It is the Summation of All Prediction Signals that then leads us to conclude the future state of Equity Markets World Wide for the next 9 days .
And Thus , we coined the phrase : Heaven Markets for UP Markets and Hell Markets for DOWN Markets . In principle , this methodology is similar to the methodology Google uses in its PageRank Search Algorithm that has made it the world ‘s most successful search engine .
We have always taken a pragmatic approach to help improve pattern recognition search quality and create useful products and our technology uses the collective intelligence of the world ‘s 1881 stocks to determine the future state of equity markets worldwide .
The life span of a Prediction Signal may take less than half a second but it involves a million calculations drawing multiple variables from momentum , stochastic , relative strength , time window space and trend .
This kind of detailed , high speed computation and accuracy is only made possible by Today ‘s advances In Technologies and Mathematics.
Forbidden Fruits in the Garden of Eden
By Anonymous Artist
The Forbidden Fruits of Finance :
1881 Financial Predictions for The Entire World
The predictions cover stocks from Asia , Malaysia, Jakarta, South Korea , Taiwan , Latin Americas , Mexico, Brazil , Canada Toronto, China Shanghai, India NSE , Hong Kong , Australia and including 800 US Listed ETFS , ^NDX 100 and S&P500 Index stocks , the Most Important Stocks in the world .
The S&P 500 Index represents 500 of the largest companies designed to give a big picture view of the US stock market. About $1.5 trillion in investments mirror the moves of the S&P index and 4.9 trillion in investments are measured against it .
True Secrets of Predictions .
Quantifiable over 20 years of Market History .
When at least 3 Predicted Lines stick together and lie parallel in ONE LINEAR DIRECTION . That is a Prediction , Highly Probable and most likely to come true .
We Offer this Highly Valuable Consultation Service to Hedge Funds and High Net Worth Players Mainly. The Service includes a predicted Look Forward Graph showing 3 Independently Generated Scenarios of a Stock Chosen by the Client . When the 3 Scenarios coincide , stick together and lie parallel in ONE LINEAR Direction , we know that it is a highly probable pattern and likely to come true . Visual Examples are given below in the following pages .
This individual stock prediction is then measured and balanced against the Intermarket Analyses of the Volatility Indexes and Overall Prediction Score for 1881 Stocks within our universe.
In Reference to the Prediction and Probabilities Rating , we use
Criterion B and Criterion C to measure Look Forward Scenarios .
Criterion B Predicts for the first 1 to 6 days with a Probability Ranking using U to represent UP and D to represent Down .
Criterion C Predicts for the first 3 to 9 days .
For Up Predictions , Highest Probability Ranking is 100U for 100 UP . Lowest Probability Ranking is 16 U .
Similarly for Down Predictions , Highest Ranking is 100D for 100 Down . Lowest Probability Ranking is 16 D
We advise to concentrate on Stocks that have Probability Rankings that have a minimum level of 33 U or 33 D . We found that when Probability ranking is higher than 33 percent level , the probability of a profitable trade is more than 66 percent and the Equity Line is a lot smoother for Signals with Higher Probability Rankings.
Visual Examples are given below in the following pages .
So if both Criteria B and Criteria C are U for UP , then it is highly likely that the price would be UP for next 6 to 9 days . Similarly if both Criteria B and Criteria C are D for Down , then it is highly likely that the price would be Down for next 6 to 9 days
If Criteria B is Up and Criteria C is Down , then it is a A shaped pattern with price going up for first 1 to 6 days and perhaps coming down from first 3 to 9 days .
If Criteria B is Down and Criteria C is Up , then it is a V shaped pattern with price going down for first 1 to 6 days and perhaps going up from 3 to 9 days .
KEYS to PREDICTION: Look Forward Scenarios
Graph below shows a Highly Probable UP Prediction .
Notice the 3 Predicted lines of 6 points stick together and lie parallel with each other . These are the characteristics of a Highly Probable Prediction .
Graph below shows a 6 DAYS UP Pattern superimposed over 9 DAYS actual price INCREASE for the VXO Volatility Index (^VXO)
Notice the first 3 points of the yellow , maroon and blue lines coincide together and seen as 1 single line .
Graph below shows a 6 DAYS DOWN Pattern superimposed over 9 DAYS actual price DECREASE for the Dow Jones Index (^DJI)
This pattern is
deliberately chosen to depict a LESS Probable Down Prediction .
Looking at it , one can decipher that it may be a Less Probable
Pattern to come true as the 3 Predicted Lines do not Stick together
and do not lie Parallel with each other .
Nevertheless , with the Verdict at 33 D , and its 3 Criteria B and C all showing Down , the prediction Still Came True .
Notice both Predictions for the DJI and VXO agree with each other from 4/11/2008 . The rule in the market is when Volatility increases , the Market Drops .
Track Records Over 20 Years : What have we learned .
The Perfect Hedge is a Long Equity and Long Volatility Portfolio .
It produces a Straight Equity Line over 20 years with Low Drawdowns and High Hit Rates for Long Equity and Long Volatility Signals .
Even In the Most Volatile years of 2006 to 2009 , Applying the Same Principle of Long Equity and Long Volatility Produces Superb returns in excess of 20 percent each year with Low Drawdowns.
Yellow Equity Line Below shows a Combo of Both Long and Short Positions for DJI and VXO . Blue Line shows Long Volatility and Long Stock Position . Red line shows Short Volatility and Short Stock Positions .
When we apply this rule to VXO and DJI , the Equity Line is a lot more smoother which means Lower Drawdown of Equity and Higher Leverage can be applied . Please refer to following Equity Line below .
Refer to the Graph below , using VXO Volatility Index ‘s Criterion C as a leading Indicator over the DJI , the Decision is to go Short Volatility as Criterion C shows 33D for Volatility Index ^VXO . This decision coincides with Go Long for Dow Jones Index as Criterion C for ^DJI is 44 U .
S
o
How do we Trade Volatility ?
Fortunately there are 49 Highly correlated Ultrashort ETFs to choose from ,
Please see table below :
Top 20 Positively VIX Correlated ETFs
In Ascending Order of Correlation .
Name Symbol
ProShares UltraShort Semiconductors SSG
ProShares UltraShort Oil & Gas DUG
ProShares UltraShort Technology REW
ProShares UltraShort Financials SKF
ProShares UltraShort Consumer Goods SZK
ProShares UltraShort Basic Materials SMN
ProShares UltraShort Consumer Services SCC
ProShares UltraShort SmallCap600 SDD
ProShares Short SmallCap600 SBB
ProShares UltraShort Industrials SIJ
ProShares Short QQQ PSQ
ProShares Short Russell2000 RWM
ProShares UltraShort QQQ QID
ProShares UltraShort Russell2000 TWM
ProShares Short MidCap400 MYY
ProShares UltraShort MidCap400 MZZ
ProShares Short Dow30 DOG
ProShares UltraShort Dow30 DXD
ProShares Short S&P500 SH
ProShares UltraShort S&P500 SDS
The Ultimate Forbidden Fruit :
Financial Predictions for November 13 , 2009
REVELATIONS :
Summary Prediction Score for 100 Stock Markets and ETFS November 16 2009 :
145 UP Stock Markets Indexes vs 186 Down Stock Market Indexes
Prediction Verdict : November 16 2009 for Next 9 days …
More Hell than Heaven…
Equity Markets Looking to GO DOWN .
End Result : We Shall See …
Intermission
M
y
Idea of Measuring Heaven and Hell Markets is inspired by William
Blake who wrote The Marriage of Heaven and Hell.
Here , the material world of physical desires share equal parts .
w
ith
the divine world . Heaven and Hell reside together.
Blancpain, ‘s 1 Million Dollar Watch.
No, It does Not Foretell the
Future Either
The Next Course of Action from Reader .
Attend the CrystalVol Training Seminar
Summary of Training Seminar :
How to Trade like a Successful Hedge Fund Manager
and Build a Successful Track Record .
Please contact dealingmachines@gmail.com for event details ,
(Pricing : 999 USD 1 full day training seminar )
Timing is EVERYTHING
Train and Trade like a Real Hedge Fund Manager .
When to be Fearful when others are Greedy
When to be Greedy when others are Fearful
Dehumanise the trader .
Be a Hybrid Half Machine Half Human Trader .
Throw away charts as they cloud your thinking .
A billion Calculations to make a buy sell decision .
Ying and Yang , quant and quality ,
Quantitative and Qualitative .
Visually looking at Volatility .
Looking at 1000 stocks in 1 second .
Jim Symons Renaissance Technologies : String Theory and Fractals .
Volatility as a fractal , Intraday , daily , weekly .
When all the stars align , 1000 stocks , or 3000 stocks , 3 volatilites , 49 ultrashorts ,
Hedge : Long and Long : long volatility ( buy puts ) and long stocks .
Macro Hedge Funds : from stocks , to Cash Bonds to Oil to currencies
Basic Building Block is Volatility and 1000 stocks from Russell 1000 .
Being 65 percent sure vs 90 percent sure .
Always in the market verses blue moon markets.
Puts , Calls , Ultra Long Ultra Short ETFS , SDS SSO , Warrants Hang Seng
Joining the Hedge Fund Industry
Portable Inheritable ALPHA for Hedge Funds
Quant Track record is Portable and Inheritable .
BQT Quant Models
Using a Hybrid of neural nets , fuzzy logic and genetic algorithms , the technologies generate millions of calculations and predict periods of rising Volatility before they happen .Statistically , it can be verified that the technologies has a 65 to 80 percent accuracy rate for 9 week and 9 day models .
Transparency of Quant Models .
Traders and users of Quant models know that there is clear transparency in Quant Models . We know exactly , What we did , When and Why .
Keeping it Small and Confidential
Client details and trades are kept strictly confidential .
Prediction
Ranking for 100 Stock Markets and ETFS DAYS from November 16 2009
.
Criterion B shows Probability of Prediction For Next 1 to 6 Days .
Criterion C shows Probability of Prediction For Next 3 to 9 Days .
Symbol Predict Date From Level Criterion B Criterion C
Rating Table for Next 9 Periods
Symbol Predict Date From Level Criterion B Criterion C Verdict
^JKSE 20091117 2468.675 N N N
^KS11 20091117 1597.21 16 U 33 D N
^N225 20091117 9824.7197 N 100 D 100 D
^NZ50 20091117 3165.488 16 U N 16 U
^STI 20091117 2777.52 N N N
^TWII 20091117 7865.3599 66 D N 66 D
000001.SS 20091117 3275.0481 N 16 D 16 D
^AEX 20091116 322.16 33 D N 33 D
^BFX 20091116 2535.3201 16 D N 16 D
^BSESN 20091116 17032.5098 50 D N 50 D
^DJA 20091116 3516.3999 N 16 U 16 U
^DJC 20091116 136.08 100 D N 100 D
^DJI 20091116 10406.96 16 D N 16 D
^DJT 20091116 4046.5 16 D N 16 D
^DJU 20091116 378.32 N N N
^DWC 20091116 11374.7998 16 D 16 D 33 D
^FCHI 20091116 3863.1599 N 33 U 33 U
^FTSE 20091116 5382.7002 N N N
^FVX 20091116 2.18 N N N
^GDAXI 20091116 5804.8198 33 D 16 U 33 D
^GSPC 20091116 1109.3 16 D 16 D 16 D
^HSI 20091116 22943.9805 N N N
^IIX 20091116 228.08 33 D 16 U 33 D
^IRX 20091116 0.05 N N N
^IXBK 20091116 1594.38 N N N
^IXF 20091116 1941.79 N N N
^IXFN 20091116 3621.4199 33 D N 33 D
^IXIC 20091116 2197.8501 N 16 D 16 D
^IXID 20091116 1701.89 N 50 D 50 D
^IXIS 20091116 3494.99 N N N
^IXK 20091116 1119.9301 N N N
^IXTR 20091116 1899.0601 N 16 U 16 U
^IXUT 20091116 211.96 N 16 U 16 U
^JKSE 20091116 2468.6799 N N N
^KLSE 20091116 1278.3101 16 D N N
^KS11 20091116 1592.47 N 16 U 16 U
^MID 20091116 710.57 33 D 16 D 33 D
^N225 20091116 9791.1797 16 U N 16 U
^NBI 20091116 821.89 N N N
^NDX 20091116 1807.5601 N N N
^NY 20091116 5132.79 N 16 U 16 U
^NYA 20091116 7237.1001 N N N
^NYI 20091116 5396.0698 16 D N 16 D
^NYL 20091116 5336.8901 16 D N 16 D
^NYY 20091116 5277.1401 16 D N N
^NZ50 20091116 3173.97 N 16 D 16 D
^OEX 20091116 515.01 N N N
^OMXSPI 20091116 304.024 N N N
^OSEAX 20091116 407.273 N 16 U 16 U
^PSE 20091116 843.79 16 D N 16 D
^QQV 20091116 21.21 16 D N 33 D
^RUA 20091116 646.5 N 16 D 16 D
^RUI 20091116 607.13 N N N
^RUT 20091116 602.87 N 16 D 16 D
^SML 20091116 319.22 N N N
^SMSI 20091116 1252.03 50 D N 50 D
^SOXX 20091116 323.83 16 D 50 D 66 D
^SPSUPX 20091116 252.78 N N N
^SSMI 20091116 6422.7998 33 D 50 D 50 D
^STI 20091116 2783.8501 N N N
^TNX 20091116 3.33 N 16 U 16 U
^TWII 20091116 7792.6802 50 D N 50 D
^TYX 20091116 4.26 N 16 U 16 U
^VIX 20091116 22.89 N N N
^VXN 20091116 23.13 N 33 U 33 U
^VXO 20091116 21.84 16 U 16 U 16 U
^XMI 20091116 1152.1899 N N N
BKF 20091116 47.49 N 33 U 33 U
ECH 20091116 52.4 33 D 16 D 33 D
EIS 20091116 52.58 N N N
EPP 20091116 43.44 N N N
EWA 20091116 24.5 66 D N 66 D
EWC 20091116 26.11 33 D N 33 D
EWD 20091116 25.85 50 D N 50 D
EWG 20091116 23.02 50 D 16 D 50 D
EWH 20091116 16.32 66 D N 66 D
EWI 20091116 20.93 16 D N 33 D
EWJ 20091116 9.67 N 16 D 16 D
EWK 20091116 13.56 N 33 D 33 D
EWL 20091116 22.52 16 D 16 D 33 D
EWM 20091116 11.17 N N N
EWN 20091116 21.12 50 D N 50 D
EWO 20091116 22.28 66 D 33 D 66 D
EWP 20091116 52.11 16 D 16 D 33 D
EWQ 20091116 26.84 N N N
EWS 20091116 11.59 16 D 50 D 50 D
EWT 20091116 13.12 16 D 16 U N
EWU 20091116 17.1 16 D N 16 D
EWW 20091116 48.66 N 16 U 16 U
EWY 20091116 46.15 N 16 D 16 D
EWZ 20091116 76.77 83 D 66 D 100 D
EZA 20091116 56.87 N 50 D 50 D
SCJ 20091116 41.468 N 16 U 16 U
THD 20091116 41.97 16 D 33 U 33 U
TUR 20091116 51.64 16 D 33 D 50 D
^AEX 20091113 317.37 N N N
^BFX 20091113 2506.47 16 U 33 U 50 U
^BSESN 20091113 16848.8301 33 D 33 D 33 D
^DJA 20091113 3462.1201 N 33 U 33 U
^DJC 20091113 131.68 16 D 16 U N
^DJI 20091113 10270.4697 N N N
^DJT 20091113 3960.5701 N 16 U 16 U
^DJU 20091113 373.57 33 U N 33 U
^DWC 20091113 11200.5 N N N
^FCHI 20091113 3806.01 N 16 D 16 D
^FTSE 20091113 5296.3999 N N N
^FVX 20091113 2.26 50 U 16 U 50 U
^GDAXI 20091113 5686.8301 N N N
^GSPC 20091113 1093.48 N N N
^HSI 20091113 22553.6309 N 16 U 16 U
^IIX 20091113 226.35 N N N
^IRX 20091113 0.05 16 D 66 D 66 D
^IXBK 20091113 1566.64 33 U N 33 U
^IXF 20091113 1912.75 N 50 D 50 D
^IXFN 20091113 3565.3899 N N N
^IXIC 20091113 2167.8799 N N N
^IXID 20091113 1672.34 33 U N 33 U
^IXIS 20091113 3431.28 N 16 U 16 U
^IXK 20091113 1105.78 N N N
^IXTR 20091113 1853.2 N N N
^IXUT 20091113 211.15 N N N
^JKSE 20091113 2426.8 16 D 16 U N
^KLSE 20091113 1270.96 16 D 33 D 50 D
^KS11 20091113 1571.99 N 33 U 33 U
^MID 20091113 698.26 N 33 D 33 D
^N225 20091113 9770.3096 N 50 D 50 D
^NBI 20091113 808.09 N 33 D 33 D
^NDX 20091113 1788.61 16 U N 16 U
^NY 20091113 5060.9702 N N N
^NYA 20091113 7119.8901 N 33 D 33 D
^NYI 20091113 5305.5601 N 16 D 16 D
^NYL 20091113 5255.4199 16 D 66 D 66 D
^NYY 20091113 5203.02 N 33 D 33 D
^NZ50 20091113 3158.1399 50 U N 50 U
^OEX 20091113 508.08 N 16 D 16 D
^OMXSPI 20091113 301.42 N 16 D 16 D
^OSEAX 20091113 395.68 N N N
^PSE 20091113 832.88 N N N
^QQV 20091113 20.26 N 16 D 16 D
^RUA 20091113 636.47 N N N
^RUI 20091113 598.31 N N N
^RUT 20091113 586.28 16 U 16 U 33 U
^SML 20091113 310.46 33 U N 33 U
^SMSI 20091113 1239.1801 N N N
^SOXX 20091113 317.5 N N N
^SPSUPX 20091113 249 N 33 D 33 D
^SSMI 20091113 6351.1001 N 33 D 33 D
^STI 20091113 2727.23 N 33 U 33 U
^TNX 20091113 3.43 N 16 D 16 D
^TWII 20091113 7665.6299 N N N
^TYX 20091113 4.36 N N N
^VIX 20091113 23.36 N 33 U 33 U
^VXN 20091113 22.92 16 D 16 U N
^VXO 20091113 22.26 N 16 U 16 U
^XMI 20091113 1136.98 N 16 D 16 D
000001.SS 20091113 3187.6499 N 33 D 33 D
BKF 20091113 46.25 N N N
ECH 20091113 51.96 N 33 D 33 D
EIS 20091113 51.56 33 U 16 D 33 U
EPP 20091113 42.7 16 U N 16 U
EWA 20091113 24.11 50 D 50 D 50 D
EWC 20091113 25.87 N N N
EWD 20091113 25.55 16 D 16 D 16 D
EWG 20091113 22.49 N N N
EWH 20091113 16.08 33 D 50 D 50 D
EWI 20091113 20.61 N 16 D N
EWJ 20091113 9.58 16 U N 16 U
EWK 20091113 13.4 16 U 33 D 33 D
EWL 20091113 22.28 N 33 D 33 D
EWM 20091113 11 N 16 D 16 D
EWN 20091113 20.8 33 D N 33 D
EWO 20091113 22.2 16 D 83 D 100 D
EWP 20091113 51.6 16 D 83 D 83 D
EWQ 20091113 26.46 N 16 D 16 D
EWS 20091113 11.25 N 16 D 16 D
EWT 20091113 12.5 N N N
EWU 20091113 16.69 N N N
EWW 20091113 47.75 N N N
EWY 20091113 45.1 33 U N 33 U
EWZ 20091113 74.96 N 66 D 66 D
EZA 20091113 55.97 N 16 D 16 D
SCJ 20091113 41.01 N N N
THD 20091113 40.85 N N N
TUR 20091113 51.48 16 D 16 D 16 D