The stats are in our VXX trade, entered 14 days ago – closed on Friday 13, 2015.

Stock quote and option quote for VXX on 10/19/15 10:11:06

-194.010 -21.600 -52.978 -7.545 0.969
-385.90 -42.86 -113.31 -18.69 0.0681
-1.16% -1.12% -1.54% -0.72% 1.29%


Look on the Right side column “C-Return” and “Inverse”.  This is the key factor in knowing whether to lean into the Call or Put side.

Asset Price 21.96 C-Return 1.4900
Net Change 1.400 Inverse -0.4900
Price Action 1.9100 Inverse P Act 0.7236
STDEV Price 0.361 IV Rank 0.6005

Below is our “front month” outcome – November Option Cycle.  The Call reaped $1779.00 in profits, while the Put fell prey to “time decay” eventually zeroing out almost all Ask/Bid strike premiums.  Our loss was $0.38.

NOV 15 (14) 100

$1,179.00 $1,179.38 $0.38
Strike 17 Strike 18
Premium 5.05 DELTA Premium 0.040
Entry Price 1.12 PUT Entry Price 0.039
Target 5.19 Target 0.18
Skew Price 5.21 IV Skew Price 0.206
Delta Hedge 0.2430 CALL Delta Hedge 0.811
Gamma 3.5006 Gamma 0.1106
IV 0.610 SPRD > .0003 IV 0.417
Intrinsic 3.900 CALL Intrinsic 0.015
Strike 17.00 ~ Strike 18.00
Ask-Bid Spread 0.000 PUT A- B SPREAD 0.000
Prob of Profit 0.2419 ~ Prob of Profit 0.800
Profit/Loss $1,179.00 Profit/Loss $0.38

(Disclaimer:  This is posted for educational purposes only.  We make no claims or advise to make trades based on this data.  All of our posts are Proof of Concept for a working Excel spreadsheet model titled <codex.qbt>.)

For more information please write to use at: tecktomaket4@gmail.com immediately.  You don’t want to miss out the insightful data inputs that help your trading strategies to be mechanical and profitable.


Without going into great detail and laborious contextual arguments that comprises a thesis or worse yet a “white paper” at this time, here is the initial visual introduction of our revamping of Excel equations and formulas we’ve been using for robust profitable investing.

The sole purpose of this project is to push encryption code through keyword behaviors that tested and evaluated by description so as to prevent deprecation hacking; going beyond syntactical constraints such as the XML schema.

Moreover, we express a limited capability with data type syntax such as add/edit, through “PUBLIC” Formal Public Identifiers (FPI), to be used for global financial market’s routing exchanges ISP data packets.

By using Boolean predicates, the data content must satisfy the governing context ( say between the exchanges Bid and Ask spreads) filtered through specialized rules that comply with “uniqueness” and “referential integrity”.


At the core of our revision is incorporation of the Qubit – or quantum bit – that is fast becoming known through the acceleration of the D Wave quantum computer, and its quickly evolving incorporation into our global social network, given a recent combined purchase by Google and NASA for $10 billion dollars.

Dominance of our global networking economy through internal means, is a mechanism that can override just about every programming language used today.

Qubit superposition algorithm driven trading, i.e. High Frequency Trading, is quickly morphing into augmented intelligence, the interplay between human and machine; the later taking on a more more dominate role.  The constructive aspects of this can be tackled in many formats, all of which have the same means to the end: profitability or worse yet, skewed presentation of profitability.

The challenge to us is if we can dial down this high level of sophisticated black box engineering to the most common denominator of a stylesheet language to be juxtaposed into the “backward compatibility” or  “quirk mode”  using Excel grammar and/or a similar mathematical formatted spreadsheet.

The instruction provided by the coded syntax is associated with document type definition (DTD), where the mark up conforms to the layout mode of quirk mode rather than “standard mode”.

We change the “text/html” serialization of HTML 5, for example, (not SGML-based), to “qbt/html”.

The basic HTML parsers that don’t implement full SGML-based documents such as HTML, become associated with a notable system identifier, the cataloging file resolving the FPI system identifier.

We hypothesize that since the “qubit” superposition control through magnetic gravity – using a phosphorous molecule as the directional compass for in deciding its choice between the superposition binary coded one or zero; we seek compatibility, through the use of Excel as a baseline platform, coupled with a “real world” scenario – Wall Street for validation of our implementation of this rendering mode.

We’re in development of implementing a “Qubit’ stylesheet, that involves highly innovative coding that is not traditional nor is presently used.  Consequently, as much as it sounds to be an experiment in futility, it can attain Proof of Concept if we approach the over-all architecture in a serialized format that takes into account HTML, XML, and

Moreover, we compartmentalize input/equation “bins” that have specific functions that can be seamlessly calibrated with a high degree of confidence to trigger the presence of a “Document Type Declaration” or DOCTYPE, for example.

We are piecing this together having built over 100 Excel templates.  It has been painfully difficult through trial and error over the years, though we remain motivated as much as the first “ah ha” moment of inspiration we experienced in 2012, and even going further back to 2000 when we delved into Quantum Mechanics analytics in trading Forex through Dr. Duka’s Dukascopy Forex trading platform located in Geneva, Switzerland.


price charts

Market Performance – Dow, S&P 500, NASDAQ, Russel 2000

Using only the Net Change in comparison to Price Action

aapl price


Price Range: Open, Bid, Intraday, Ask, Last

The positioning of the “Last” price in relationship to the High, Intraday, and Low prices gives us an immediate optic on the price direction – bullish, bearish or range bound.

Trend Line Polynomial – 2 Periods (Includes R-Square)

msft price formation

Microsoft (NASDAQ: MSFT)

The same parameters used with AAPL.

vxx price formation

IPath SP 500 VIX Short Term FUT ETN: VXX

Incorporating the futures index gives us a more robust insight to a possible “mean reversion” during trading hours.

There are a total of 12 charts calibrated to our Excel spreadsheet.  The entities are selected from our watch list data; a cache of forty-seven assets that are notable for both Implied Volatility, Dividend payouts, and a combination of “growth” and “value” entities robustness.

The Codex .qbt Excel Chart relates to the end-user (trader) real time price movement, based on five price range elements for “real time” price tracking through “Thinkorswim” (TOS) platform.  Latency is approximately 900 -3000 milliseconds using a conventional desktop PC and Ethernet cable connection.

Our input parameters are the current price range; Yesterday Close, Open, High, Low, Last, Bid and Ask.


A polynomial trend line set at 2 periods (Green line with arrow) to provide us with a sense of the prevailing directional move and any anomalies, e.g. “shock event” or “HFT Shark Bait” inventory spike.


We are working on presenting this “live” and/or available for traders using TOS.

Contact us if you’d like to receive a template: grtsmarket@gmail.com

(Disclaimer:  This post is for educational purposes only.  We make no claims or provide information for making trades or investments.  All of the copy presented is for simulation and hypothetical scenarios and is the sole property of GRTSMARKET.  Reproduction of this material is available per prior request through: grtsmarket@gmail.com)



In this blog we discuss how we found which option side to lean into prior to Twitter’s (NASDAQ:TWTR) earnings release the following day – 10/27/2015.

It never amazes me when the predictable is always the unpredictable when it comes to trading options around earnings.  The “zero sum” outcome and randomness of the efficient market indicators are equally reliable to be unreliable.  What goes down must come up.

And paradoxically, TWTR posted a plus in earnings, though minuscule by our standards, market makers obviously have inventory lined up to short TWTR, proving that our PUT weighed values were correct: but only momentarily since TWTR returned to the breakout price on during intraday trading on 10/28.

Posted Table on October 26, 2015 the day before Twitter posted earnings.

Estimate is -0.24 cents and actual was 0.10 in After Market Reporting.  What transpired as to the volatility of movement provides excellent feedback as to why you’re flying blind, even with statistical evidence to support a “mechanical” risk defined trade.

In this table below you’ll see our goal post statistical data indicator’s comparison between the NOV 2015 Call/Put analytic matrix that is calculated by our Codex.qbt* formula.

How to read this graph:  On both left and right sides we have Call and Put coinciding indicators: Premium (Ask), our entry price (calculated for a limit order entry), Bio premium price, Delta Hedge (not direct Delta, but our own calibration), Gamma, Implied Volatility at the Strike, Probability Out-of-the-Money, Strike, Number of contracts in hundredths, Probability of Profit (calibrated to our own formulary), P/L, and Skew price.  Note: Intrinsic is purposely left blank as this is a short term trade.

In the middle are the Logic signals:  Delta Hedge shows “Call” and Implied Volatility shows “Put”, a contradiction that played out accordingly.  The “Spread .03” Alert is to signal us when the spread between the Bid and Ask expands greater than two cents.

Stock quote and option quote for TWTR on 10/26/15 08:13:03
CALL P/L Strangle PUT P/L
$38.00 $260.00 $222.00
NOV 15 (25) 100
Premium 1.98 $260.00 Premium 2.060
Entry Price 1.78 DELTA Entry Price 1.931
Bid Price 1.93 PUT Bid Price 2.07
Delta Hedge 0.3381 Delta Hedge 0.427
Gamma 0.0887 IV Gamma 0.1272
IV 0.743 PUT IV 0.760
Prob OTM 0.61 Prob OTM 0.52
Intrinsic Spread > .03 Intrinsic
Strike 32.00 CALL Strike 30.00
Contracts 100.00 ALERT Contracts 300.000
Prob of Profit 0.1921 PUT Prob of Profit 0.1935
Profit/Loss $38.00 ALERT Profit/Loss $222.000
Skew Price 1.94 Skew Price 2.209

What sticks out is that the Implied Volatility is .743, well above our .45 threshold for mean reversion of a Buy Call signal; and that the Put indicators out weigh the Calls.

With a favorable out come of TWTR going short, we executed a cost reduction limit order with 3 Long Put contracts and 1 Long Call contract, to protect the upside, so not to diminish our profits.  You’ll notice we were pretty close in matching up the premiums for pairwise management of risk to reward ratios.

twtr earnings
Entered around $30.89. Surged up for a Call scalp profit and closed out at closing bell. Held the Put side to the opening bell on 10/28 to lock in profits at $28.80.

TOS “think back chart” (The outcomes are not as accurate given the intraday subtleties involved in our trade executions.)

The totals are listed in the above graph: Call profit was $38 on one contract and Put profit was $222 giving us a $260 pay out minus the per contract fees.  The whipsaw volatility on price formation was foretold by the OTM percentage.

*Codex.qbt is our bootstrapped Excel quantitative statistical model name.

It is in the Proof of Concept phase; based on the hypothetical Qubit “superposition” of categorical data inputs compiled into statistical data bins then calibrated for a “measure of certainty” outcome.

**Offset is the combined profit/loss between the Call and Put positions.  This is an excellent visual for “Strangles” and “Straddles” as you can see how both positions can become profitable at the same time.

Do you use TOS?  Would you like to have our Open Source Excel spreadsheet models for your own use?

Available for MSN Excel 2010, Apache Open Office and Google Spreadsheets.  These spreadsheets can be customized for your own trading style and watch list selections.

Inquire at: grtsmarket@gmail.com for a list.



Disclaimer:  The above information is for educational purposes only.  We make no claims of validity or suggestion for trading the assets listed.


Quant Org Internal Memo – received July 5 by Def-Vet from E.M

Author Code Name: Woet.  True Identity unknown at this time.  Considered high security risk for the national financial sector.

“Write Him Off” – Zine Equals A Zero

The new updated report on the probability calibration of trouble shooting the Zine algorithm carried a lot of problems with the probability density function that surfaced as an unknown and difficult to understand .

I surmised this because of the notation bugs resulting from the raw data qubits in correlation to the combinations and permutations of binary data mining inputs which upon the advent of a forced upgrade gave only the instructions for “x” that I found written on the wall in the office kitchen by the firm’s trustee who is often slow to be glad about my current position as data analyst, because he is a die-hard traditional mind-set of frameworking the tiling isohedras gathered from the TOS platform.

The less the limbs on the decision tree, I claimed that everything comes in threes pertaining to the measures of the percentiles and quartiles, ref: Ian Steen. He claims the recent score for in-house or not is his only standard data into one hot flipflop of the swithces that equates Clarks – 40 S Saint Theorem based on Laurent linear polynomial format.

A recent thesis by Rees, et al shows that they denied this by at least one P separation, ref. Seth E ETC; when you start at 90, he said that Warren’s data is the first percentile of the city’s demographic while I doubt his algorithm session performed without a flaw from the “glide” which is suppose to present no doubts that the Notation is an alternate code alone at best to intuit the percentile construct built into the adaptive agent learning memory.

It was expressed at the board meeting that with the firms aggregate years of experience, that should enhance the unit of intelligence to a 10/80 power, our ability to supersede humanity’s own ability to absorb experiences at 650 milliseconds – deviated by 3 milliseconds per neural synapse, should be 15% greater than the citizen consumer based on a control group of 91 witnesses to the machine-to-machine prototype.

This extends Tesselers equal or better than 75% social class needs to notice that we’d been already prepared infinitely per person to collect substantial profits from what was clearly 45% of the “witnesses” bias performance valuation versus the “child-parent union” factor.

Consumer response to the product launch was 20% higher than expectations while in the second quartile analysis, the thought processing averaged per millisecond or glide was 20% higher confirming that going forward will be just routine for the third programming quartile session. The citizen’s techno-device quest was identified by 4% use of the quarter range of our own data set; based on global consumption and natural resource availability.

Cheating bias was in need for the entire data set to be firmly set with empirical evidence in the first quartile correlated to the standard score median that was already shooting beyond the third quartile score.

This indeed helped me to own what was Kingsley’s proof of concept prior to my own thesis release, showing that the man lives on an island when it comes to incorporating the irrational user behavior numbers between what is displayed here as step one, and arranged accordingly through the sequencing.

We’re in small ways moving towards the largest break through in quibit coding, but facing less outside funding which means that our entire data set goal may or may not have an even chance of meeting the valuation deadline.

The only means of accomplishment at this time is to find a deep pockets cell among the 19 Seventies Equity Funds that she and myself are tuning into for an equal split on top of the 35 plus 45 ratio, designated by the late 19 – 40 baseline point system that is worth taking into consideration given our game changing breakthrough with fungi circuitry for the motherboard if we are given patent approval, re: 1223 in the 35 segmentations of required purposes.

To be sure we remain ahead of our competition, I added the all-odd numbers scores squared by integers that result in the “bringing in the money” outcome. No valued headlines in the media regarding a possible competitor or infiltrator to our project.

This is a relief since Switches and Witches reported that the median of old values are heating up certain sectors, three in fact reporting a code sequenced output of 35566778 to the power of 79 – known as the male bonding citizen element in human DNA. The TOS quartiles define this appropriately as the termed “injured portal ranges” that I discovered last Saturday after receiving a text from outlier user E. Martinez (code name DG 3-2). He reported that one 67-12 equaled 51 points in the set of data which minus “King One” closes the critical logic gate that must produce many standard deviations by perceptive observation that is fundamentally a responsibility of in our Eastern research court.

They calculated the following formation based on the quad-triangle analysis of the Zuni temple. Digging through my archival notes of hundreds of failed arguments in the algorithm Zine, all produced by “halt” calculations showed that Team Score X didn’t do the observations that I had instructed them to do, which made me have to present my ITM in front of the firm’s CEO.

But in terms of the interchangeability of less content, as I explained, for the standard score, I actually provided the proof of concept result without the Asian sector’s trouble shooting support saving our firm millions of dollars. Regardless, the mean score came out at 85, equivalent of the test score from the formula I created known as “Three Easy Zero”.

In this formula “E” equals zero, that makes the program quirky enough which was inspired by my niece Courtney’s own quirky behavior in decision making; who is a complete deviation of zeros from sigma.

Anyway I resolved the upper echelon’s Zoo Courts dilemma by declaring that their inputs into the formula were “walls” and to get around this was to calibrate the sub-syntax code to five minus the new standard deviation embedded in Zine – line 3298756-123-a234.

That reduces the outcome to exactly where we wanted the prototype to be expressed for confirmation of being bug free – proved by the seeing on the computer monitor: “Write Him Off; Z Equals Zero”


May 7, 2015

Here’s our 9 AM (PST) equity matrix update for intraday trading.  Price Skew alignment verifies the Price Target.

Ticker Pearson Last Quote Forecast Target Price Skew
AAL 0.3635 49.24 49.59 50.68 50.68
YHOO 0.8051 43.61 43.93 43.44 43.44
GOOG -0.0315 531.2 533.26 535.93 535.93
VXX 0.9302 21.8 21.75 21.65 21.65
IBM 0.6700 171.54 171.86 172.97 172.97
UPS 0.3645 99.72 99.76 100.00 100.00
TWC 0.1592 156.3 156.63 157.10 157.10
HFC 0.3391 41.11 41.40 42.20 42.20
BLUE 0.2177 150.15 151.82 156.31 156.31
HD 0.4630 110.21 110.55 111.62 111.62
MSFT 0.4027 47.04 47.20 47.62 47.62




Microsoft (NASDAQ:MSFT)continues to inch upwards.  Here is the Pearson graph posted on Macroaxis.

msft pearson correlation coefficient


Disclaimer: This post is for educational purposes only and not intended to give trading advice or recommendations.  The charts are provided as a courtesy from Maxcroaxis, a financial services website for portfolio analysis and optimization.


May 7. 2015 – OPENING BELL

It’s a mixed heat map, with red dominating crude oil while consumer discretionary patches are reflecting an undecided market.   We’re sidelined.

Equity: Alibaba (NASDAQ:BABA) and Yahoo (NASDAQ:YHOO) bolted up during extend hours opening at extreme highs at opening bell, but those gains are being erased with pull backs to the 50% price level.

Energy: Crude oil  is halted after a 29% bull run since March 17, 2015.  The BP Prudhoe Royalty Trust (NYSE:BPT)- our bell weather asset – made a sudden drop at opening bell.  Valero (NYSE:VLO) is the contrarian play, making a meager gain this morning

Currency: The green back is making gains after the Euro showed a solid recovery nearly breaking through 1.1400 before pulling back, now at 1.1256.

TICKER Pearson Last Predicted FORECAST
AAPL -0.0500 125.25 125.18 125.17
YHOO 0.9925 44.27 46.44 44.93
PBR 0.4740 9.64 9.80 9.72
JBLU 0.0015 21.35 21.56 21.31
AXP -0.1278 78.08 78.26 78.02
WMT 0.1715 77.98 78.25 77.92
TGT 0.3216 79.76 80.23 79.64
AWAY 0.6632 27.06 27.25 27.06
MSFT 0.1396 46.73 47.06 46.64
YHOO 0.9925 44.27 46.44 44.93
TYC -0.5523 39.54 39.61 39.65
UAL 0.2253 61.25 62.18 60.89


TICKER Pearson Last Mode Price FORECAST
FB -0.2239 77.68 77.98 78.09
AXP 0.8541 77.96 78.01 78.20
INTC 0.9455 32.50 32.53 32.86
HPQ 0.7847 32.68 32.76 33.08
AAPL 0.3157 125.03 125.12 125.42
MSFT 0.9554 46.68 46.66 47.05
TWTR 0.8630 37.50 37.60 38.03
P 0.9085 18.05 18.23 18.57
BTU -0.8609 4.59 4.96 5.51
JBLU 0.9826 21.28 21.39 21.66

Next update 9AM (PST).

Disclaimer: This post is for educational purposes only and not intended to give trading advice or recommendations.  The charts are provided as a courtesy from Maxcroaxis, a financial services website for portfolio analysis and optimization tools.


(Update:  Since we posted this portfolio, we re-balanced it taking Netflix (NASDAQ: NFLX) and adding HACK.  You can track the optimized portfolio in Chrome.)

Back Up The Truck is a Wall Street term for being extremely bullish on a particular asset. It’s like a “Risk On” mode when buying of consumer discretionary brands suggest the economy is robust; at about 70% of the US GDP.  We’re extremely “up beat” and “confident” that daily expected returns will be met since all assets out perform the S&P 500.


Netflix (NASDAQ: NFLX); Amberalla (NASDAQ: AMBA); CarMax (NYSE: KMX); Palo Alto Networks Inc (NYSE: PANW) and VipShop Holdings LtdADR (NYSE:VIPS)

Click on the asset’s brand name and you’ll be taken to Macroaxis; the most comprehensive financial services data mining available to self-directed investors.


This is a defined risk scenario: – because instead of buying shares individually (approximately $10,000 to make it worthwhile) Motif Investing has a required minimum deposit of $250, where upon you can use a portion of this to buy all six assets calculated by the equal allocation percentages to give you a comparable if not more leveraged like a hedge fund.

Our criteria was to load the TRUCK with assets that had annual yields over 100%, with exception of robust performance based on their individual Implied Volatility relationship to Historical Volatility.  And that they were optionable so we could Write Calls or execute Protective Puts if any of the assets negated our portfolio profits by 5% or more.


Added to that is our own Exponential Moving Average set up to Fibonacci Ratios (instead of the traditional MA 20, 50, 100, 200 overlays).

On the Daily chart, all assets are above all EMAs and the overlays are spread out which gives us a divergence signal.  This means they will eventually go bearish at some point.  Our EMAs are used for key price levels: Support, Resistance and Pivot Point (calibrated to the Price Range Geomean).

SPX performance is far below their current positions.



We’ll invest $250 overall to kick-start our investment.  Then, we’ll track each asset individually as they all have certain pre-determined entry points.  Motif Investing allows us to purchase shares of each asset individually, however, given the commission costs and our strategy to reduce our cost basis by investing a small amount, we have enough liquid capital to “BACK UP THE TRUCK” when the time is right and take a lion’s share of profits off the table.

If you want to know more about GRTS Market Analysis, please feel free to contact us.

(Disclaimer: This portfolio and or any other that GRTS Portfolio (Market) Analysis blog posts on the Internet are for strictly for educational purposes only. We take no responsibility for individual traders investment decisions nor are we making recommendations or predictive claims that results will be profitable.  We are not paid to promote Motif Investing or Macroaxis.)

Royalty Trusts: High Yields Offset Cost Basis

Want to get in on a unique investment?



BP Prudhoe Royalty Trust (NYSE: BPT) closed today at $66.40 – up $1.40 (2.15%) for the day with a trading Delta of 1.36%.  You’ll notice on the far right that recent drop has bottomed (March 16, 2015) and has started to make the second leg in a “corrective move” signaling a bullish trend upwards to $90.00.

BPT is a unique investment tool because you are investing in the “trust” that will eventually deplete your investment (cost basis) but increase your Rate of Return from the dividend payout, thus you can out ahead by the time the “trust” has expired.  Please read a more definitive explanation in Investopedia.  There are many others that you can explore that can bring substantial returns, though the calibrations between gain and loss is complex.

BPT does not have stellar indicators because of past historical ups and downs, but we like the dividend pay out as an “investment” given the back test of 30 days showed 16.97% increase on a hundred share investment. ($5,557 invested made $943 in 30 days.)  It just might be ready to start turning things around.  Currently the Price Value shows that the Bulls are in control.  As “Trust” BPT holds a sustainable future for the short term, so we’re looking at making back a higher yield on our investment against other instruments using the same amount of capital.

What it boils down to is what is going to happen to the price of crude oil in a year from now.  We expect it to go up.

Comparatively, Valero’s (NYSE: VLO) 30 day back test showed a -7.89% loss, with 18.35 million shares shorted.  BPT’s number of shares shorted are 1.39 million, with tells us investors are in for the long haul on this one. Exxon (NYSE: XOM) has shorted 42.34 million with a 7 out 100 market performance over the past 30 days. VLO has 0 of 100 in performance.  BPT has 27 of 100 performance rating.

If you’ve asked yourself what are the headlines going to be 270 days from now, as most financial managers worth their salt do, market turmoil is expected.  BPT can ride out the storm with significant outperforming returns.

Daily Expected Return% – Macroaxis


As the world’s first cyber-security we were curious to investigate the PureFunds ISE Cyber Security ETF (NYSEARCA:HACK) that tracks the ISE Cyber Security Index (HXR).

Designed to deliver competitive returns, the overall asset classes of 30 securities included in the HACK ETF are approximately two-thirds software and programming and double digit allocation of communication equipment and mobile Internet devices.


Internationally, US based cyber-security firms lead at 72% over Israel (12%), Netherlands (5%), South Korea (5%), Japan (4%), Finland (2%), and Canada (1%) according to the Zack Funds report.

Clearly, publicly traded cyber-security firms that produce security solutions software against attacks on Internet of Things (IoT) devices are fast becoming highly sought after earners since the governments initiative to be proactive on legislation combating cyber-attacks.

Back in February 2014, bolstered by strong earnings and when President Obama pressed for new legislative initiatives to crack down IoT espionage,  the “cash on the barrel-head” stock CyberArk Software (NASDAQ:CYBR) skyrocketed.

CYBR was already showing an upward trajectory based on their quarterly net income at five times the previous fourth quarter in 2013 of $1.4 million.  Then it surged to a 52-week high of $72.48 in February before settling down to establish a new price strata in March around $50 per share.


The HACK’S three month performance on Market Value was 12.67%, rising to 15.54% this past month.  The top three holdings are Infoblox (NYSE:BLOX); CyberArk Software LTD (NASDAQ:CYBR) with 5.24% in total net assets, Fireeye, Inc. (NYSE:FEYE) with 5.19% and ProofPoint, Inc. (NYSE:PFPT) 5.16% in total net assets. As well, Palo Alto Networks, Inc (NASDAQ:PANW) and Qualys, Inc. (NASDAQ:QLYS).

Our volatility generator forecasts a 96.88% probability that HACK will hit $30.00 per share within the next 60 days.  Last Friday’s close was $27.84. Right now the price level is position near the 50% Fibonacci Ratio – showing a consolidation that precedes a breakout.

On March 26, HACK traded at an unusually high “buy” volume, a signal to us that its going into a 7-day Bullish trend.  This gives us confidence that an upward trend is in the making.  Listed below are all 30 assets in the HACK and their last “weights” performance (3/27/2015). Source: ISE Cyber Security Index.


Taking a lead from the projected increase in global security spending from $71.1 billion (2014) to $76.9 billion in 2015, three more cyber-security firms have announced that they are going public. Collectively, analysts are estimating a $1 billion or higher purchase total.  The firms are Rapid 7, LogRhythm and Veracode.


As deals flow to upgrade the cyber-security cycle in enterprising innovations coming on the market, coupled with the government’s “bullet train fast track” to take on the offensive against IoTs plaguing  American business and individuals, it is predicted that Wall Street traded cyber-security solutions sector’s profitability will be reach 25% or more by the end of this year.


Symbol Weights Company Name
PANW.N 4.69 Palo Alto Networks Inc.
SAIC.N 4.08 Science Applications International Corp
FTNT.OQ 4.65 Fortinet Inc
PFPT.OQ 4.82 Proofpoint Inc.
CUDA.N 3.96 Barracuda Networks Inc
RDWR.OQ 3.54 Radware Ltd
FEYE.OQ 5.17 FireEye Inc
SPLK.OQ 4.1 Splunk Inc.
QLYS.OQ 4.59 Qualys Inc.
BLOX.N 5.25 Infoblox Inc
IMPV.N 3.17 Imperva Inc
MANT.OQ 0.8 Mantech Intl Corp A
XLS.N 0.99 Exelis Inc.
SYMC.OQ 3.5 Symantec Corp
CHKP.OQ 4.06 Check Point Software (US)
CSCO.OQ 3.82 Cisco Systems Inc
ZIXI.OQ 0.77 Zix Corp.
FSC1V.H 2.55 F-Secure Oyj
JNPR.N 4 Juniper Networks Inc
CMP.WA 0.2 Comp SA
ABT.TO 0.78 Absolute Software Corp
GTO.AS 0.69 Gemalto NV
AVG.N 4.29 AVG Technologies NV
WYY.A 0.68 Widepoint Corp
IL.N 3.74 IntraLinks Holdings Inc
053800. 4.73 Ahnlab Inc
KEYW.OQ 3.17 Keyw Holding Corp
CYBR.OQ 5.2 Cyber-Ark Software Ltd/Israel
VDSI.OQ 3.16 VASCO Data Security Intl Inc
4704.T 4.26 Trend Micro Inc


The log-linear rule falls in between the “traders” price and the “net orders” affecting the price action.”  Prof. Doyne Farmer and Prof. Shareen Joshi*

Let’s be absolutely clear:  The National Best Bid and Offer (NBBO) is meant to protect the retail trader from pricing manipulation by their counter-party that could cheat them out of their profits, while benefiting the brokerage, proprietary dark pools and/or High Frequency Trading driven by their respective algorithms.

So I ask: Have you ever experience a “price dislocation”?  What I mean is that the price that you executed your exit at was blatantly offset so much – say over five cents – that an elephant could walk through it?  Well, you’re not alone.  Unless you the means of tracking this, say with an excel spreadsheet that is plugged into a brokerage house platform, you won’t know the origin of the “offset” that cut your calculated profits before closing.


Here is the comparison between the Thinkorswim (TOS) platform’s option chain for AAPL (Apple, Inc) premium prices and my Sharebuilder (SB) close price.  I traded AAPL at the APR option chain, the Strike price was 127.14.  My entry as shown below from the SB transaction history was a scaled in 2 contracts per 2 trades with a Long Call position.

My target limit was 2.05 on the Ask premium.  When 2.05 was hit I executed my close on the SB positions, but was you see, even though there was a drop in the premium on the TOS platform, the SB platform – connected to the BATS exchange – didn’t give me “best price” in accordance to NBBO rules.

sb aapl.jpeg (2)


Above is the SB transaction history.  My closing premium for all 4 contracts was 1.93, not anywhere near what the TOS platform was showing at the same Strike price.

2015-03-26-StockAndOptionQuoteForAAPL (2)


Just below the yellow highlighted ban is the current premium prices, last price and mark price, which all are well above the 1.93 closing price that SB gave me.  My profit loss was over $50 on the four contracts, leaving me with $16 in net profit.  Moreover, SB’s real-time price at this Strike price was previously held at 1.86 while the TOS platform’s Call premium price increased dramatically toward 2.05.  The lag time on the SB to catch up, and then not even matching “best price” as shown on the TOS platform didn’t exceed 1.96.


Whose the culprit behind this?  Conniving Leprechauns?  Pesky GPU malfunctions?  You may be surprised to learn that it boils down to High Frequency Trading algorithms (HFTs) trolling the exchanges for an opportunity to “flash trade” off of your executed trade; either when you open or close.  Since HFTs have direct access to contracted co-location to Wall Street exchanges, primarily located in New Jersey, their latency is measured in nanoseconds, whereas yours and mine are measured in milliseconds.


If you’re inspired to build an excel spreadsheet that will expose this detrimental price aberration you could turn to Walras’ formula:

dp over dt = -Beta D(p, …)

Or Kyle’s model formula:

P t+1 – P t = ω

But let’s keep it simple, as my point here is to just make you more aware of the fact that virtual pricing is overtaking your “true price” formation.  Take into consideration the first element in their formula concerning an asset or option premium’s price formation:


Form has two components that determine to be path dependent based on the price range (Bid/Offer) inputs provided by any one of the 13 market exchanges at any one second that eventually shows upon your computer screen.

The origin of the asset’s  “price” is fundamentally started at the opening of the market session and then sequential accumulation of both Ask and Bid share orders can be calibrated to determine intraday price trends.  That means if you set up an excel generator to record any equity Ask and Bid share orders, you can scale out a directional price movement forecast using the appropriate computational statistical mathematics.

According to Farmer & Joshi:

“a. This defines the weighted side which in turn shows the propensity toward formulating a trend that is either Bullish or Bearish.

b. Exponential Distribution equation defines the next calibration that is probability density accumulation.”

High Frequency Traders Can Shift “True Price”

There are 24,000 seconds during the Wall Street scramble to trade in one day session.  Within those 24,000 seconds, High Frequency Trading (machines talking to machines) causes 2.4 price dislocations, most often times cheating retail traders out of a few pennies on the equity’s Bid/Offer spread, including option’s premiums. That comes out to 57,600 price dislocations per trading day.


I have built a deterministic trading strategy that incorporates a quantitative excel spreadsheet “real-time” data input, calibrated to a set of parameters that eliminate the “noise” while showing the directional price formation of the underlying asset correlated to the options premium.  The most telling function is the price shifts and comparative profit between simulated Call/Put profits during intraday trading that are depicted on the GRTS Tactical Trader.

Below is a screenshot of the GRTS Tactical Trader spreadsheet:**

screenshot-{domain} {date} {time} (1)


I currently use TD Ameritrade, Thinkorswim, Dough, and Capital One Sharebuilder.  The reason is for the very reason I mentioned at the beginning of this article: tracking price dislocations, i.e. “flash trading” by HFTs that cause “virtual price dislocations” giving them a profitable edge on my trade executions, while I take a greater loss.


Rich K.

* “The dynamics of common trading strategies”, Farmer, Doyne, J. & Joshi, Shareen

** For TOS traders, the GRTS Tactical Trader is currently available in the Apache Open Source Excel format, for a token donation.  Inquiries via email are welcomed for further information and explanation.  This is for advanced users of excel and day traders.