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Mar 18, 2013 new Tables 2, 3 Oct 24, Table 4 new Oct 27, Table 5 new Oct 31, Chart 1,4,5,8 updated thru Nov 2, Charts 1,2,3,4,5 updated thru Nov 9, Charts 1,8 updated Nov 16, Charts 1,8 updated Nov 30, Chart 2 updated Dec 2,
BIGGEST GUARANTEE
on the Internet from one of the smallest sites We guarantee these VXX VIX Volatility Forecasts and Predictions 100% right, never wrong yet
About our guarantee, Frog is rewriting Shakespeare again:
“Your honor is your life; both doth grow in one; If honor doth be taken from thee, thy life is kaputeth.” (Volatility Research Frog 2012)
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Oct 19, 2012
We accidently stumbled onto and discovered while trying different moving averages that — when 10 Run Weighted Moving Average 10wRMA crosses zero
VXX up and down price trends STOP or REVERSE Predictions are 100% right so far, some pretty good early signals and no false signals. Very unusual for us.
We do not recall ever seeing any forecast or prediction of anything non-predictable that comes close to being 100% right.
This discovery may be important and useful if it proves out in 'real time,' especially for options and futures traders and savvy investors. This breakthrough will be announced in a major financial publication. This page may prove to be the most important page you read here.
Frog says, "Go for it. Finally a winner. This dog's gonna fetch."
Got it Frog. You're the master of metaphoric oxymora and hopefully perception.
Predicting VXX price trends is simple and easy — all you have to do is see when the red line in Charts 1-3 crosses zero. You don't have to know any math, statistics, standard deviations, calculus, etc. If LOG's are confusing, just think of the green lines as VXX spread out to better see its changes.
We define:
Run as one or more consecutive days of VXX closing price up or down. Through Aug 31, there were 191 Runs since Jan 3, 2011 — 95 up (1.9 days avg), 96 down (2.5 days avg), 7 days maximum Runs, 421 days. See Table 1 below for Runs History. Trend when 10wRMA has same sign (+) or (-) for two or more consecutive Runs. Through Aug 31, there were 13 UP and DOWN Trends since Jan 3, 2011, longest 98 days DOWN, from Nov 28, 2011 to Apr 16, 2012, X-axis 115 to 73. Time Span as the duration of 10wRMA having same sign (+) or (-) measured along the X-axis in Charts 1-7 below.
Optimized 10 Run Weighted Moving Average 10wRMA in charts 1-3 and 6-7 below eliminates 12+ 'rogue predictions' of one-day Runs up and down. Chart 1-1019 10wRMA with Standard Deviations of 10wRMA Chart 2-1019 10wRMA with VXX Runs Chart 3-1019 Contributions of (+) and (-) Runs to 10wRMA Chart 4-1019 VXX Predictions by Cumulative Runs Factor CRF Chart 5-1019 Correlation VXX Actual & Cumulative Runs Factor CRF Chart 6-1019 10wRMA Slope, calculus 1st derivative Chart 7-1019 10wRMA Slope Change, calculus 2nd derivative
(Y-axis in charts is Log (y) unless shown otherwise)
- Up / Down Trends are primarily controlled by (+) / (-) Contributions of Runs to 10wRMA, Chart 3:
- Increasing Contributions of (+) Runs are generally leading indicators of
UP Trends before and as soon as UP Trends begin.
- Decreasing Contributions of (+) Runs are generally leading indicators of DOWN Trends before and as soon as UP Trends end.
- Increasing* Contributions of (-) Runs are generally leading indicators of DOWN Trends before and as soon as DOWN Trends begin.
- Decreasing** Contributions of (-) Runs are generally leading indicators of
UP Trends before and as soon as DOWN Trends end.
* more negative ** less negative
- Trends' strength appears inversely proportional to 10wRMA Standard Deviations, e.g. high SD low strength.
- Trends are strongest when both (+) / (-) Contributions of Runs to 10wRMA have same slope sign, calculus first derivative, more so at Trends' beginnings.
- Trends are weakest when both (+) / (-) Contributions of Runs to 10wRMA have different slope sign, calculus first derivative, more so at Trends' ends.
- 10wRMA is leading indicator of Trends' reversal before crossing zero.
- Trends reverse when 10wRMA crosses zero.
- Most surprising — near-perfect correlation, one-to-one, R2=0.9860, of Cumulative Runs Factor CRF predicting VXX, Chart 5 — surprising because CRF is the cumulative-sum of the alternating series of only 13 Run-integers -7 to +6 below:
Table 2-1024 208 Runs from Jan 3, 2011 thru Oct 24, 2012
2, -1, 1, -4, 1, -2, 2, -4, 2, -1, 2, -3, 1, -2, 1, -3, 1, -5, 4, -1, 3, -3, 2, -4, 1, -4, 2, -3, 3, -1, 1, -3, 1, -1, 1, -2, 1, -4, 1, -1, 1, -1, 1, -5, 1, -1, 1, -5, 3, -2, 1, -1, 1, -1, 6, -1, 2, -1, 3, -1, 1, -4, 1, -1, 2, -2, 1, -2, 5, -3, 2, -2, 1, -5, 1, -5, 1, -1, 1, -3, 2, -5, 2, -1, 4, -4, 2, -3, 1, -5, 1, -1, 1, -6, 1, -1, 1, -1, 2, -5, 1, -1, 1, -1, 2, -2, 1, -4, 2, -1, 1, -1, 2, -1, 1, -2, 1, -2, 1, -2, 2, -3, 1, -2, 2, -1, 1, -5, 1, -3, 2, -1, 1, -2, 3, -1, 1, -4, 3, -1, 5, -2, 1, -2, 5, -1, 1, -1, 1, -1, 5, -2, 4, -4, 1, -1, 5, -1, 2, -5, 3, -3, 2, -1, 2, -1, 1, -1, 2, -1, 1, -5, 2, -3, 2, -1, 1, -3, 5, -7, 1, -3, 1, -1, 2, -7, 1, -7, 3, -1, 2, -1, 2, -1, 2, -3, 6, -2, 2, -7, 1, -4, 1, -1, 1, -6, 2, -3
Sum |
-71 |
193 |
-264 |
Count |
208 |
104 |
104 |
Average |
-0.34 |
1.86 |
-2.54 |
StDevP |
2.66 |
1.24 |
1.71 |
Max |
6 |
6 |
-1 |
My |
-7 |
1 |
-7 |
|
But there were 208 VXX closes on Runs beginning dates Jan 3, 2011 thru Oct 24, 2012 — ranging from 8.22 to 53.37 before VXX Oct 5 1:4 reverse split, 32.88 to 213.48 after split:
Table 3-1024 208 VXX closes from Jan 3, 2011 thru Oct 24, 2012
037.50 034.55 032.88 034.22 035.41 035.55 034.52 035.52 036.04 034.84 038.28 035.08 035.40 036.28 036.72 039.44 039.72 046.04 045.76 045.28 046.00 046.04 046.96 046.84 048.88 053.36 053.04 057.80 052.80 050.28 051.40 053.40 056.64 056.24 058.12 057.00 057.60 065.04 067.24 066.72 068.72 063.56 070.80 073.96 082.44 078.44 079.80 086.68 082.20 080.88 081.68 081.04 082.44 079.60 069.92 068.84 068.56 067.72 064.76 064.04 066.20 071.64 073.44 071.08 073.00 076.04 077.12 080.04 068.40 069.12 068.84 069.16 074.32 086.36 087.84 099.04 104.20 096.76 097.08 099.84 100.32 107.76 106.08 103.04 095.80 104.64 107.44 106.68 111.28 125.08 126.00 122.76 124.64 134.64 142.12 139.88 143.32 137.56 135.32 156.56 163.08 162.52 163.20 162.44 166.92 162.76 163.28 187.28 194.40 185.68 190.16 187.56 185.16 176.52 178.48 181.84 193.72 171.28 173.16 178.00 160.40 167.92 175.24 175.12 183.64 172.00 178.68 186.40 201.00 211.92 213.48 199.44 202.84 194.40 180.84 171.52 171.80 183.28 167.40 164.76 155.72 164.28 166.76 167.24 131.40 128.72 136.36 135.40 140.92 125.24 095.96 093.64 086.04 089.96 094.56 092.64 081.40 080.44 081.48 096.68 094.28 100.92 097.72 090.20 091.48 088.44 091.28 089.92 089.44 089.32 090.44 093.96 090.96 094.80 094.52 093.32 094.24 099.20 092.56 107.08 112.68 113.72 115.68 114.56 113.52 119.96 123.00 145.92 133.28 132.04 129.00 127.36 126.64 123.72 129.92 134.72 112.40 112.08 114.00 128.12 128.40 126.32 128.92 127.40 128.72 144.00 143.72 145.96
Sum |
| 22320.91 | Count |
| 208 | Average |
| 107.31 | StDevP |
| 46.97 | Max |
| 213.48 | My |
| 32.88 |
Before this research, it seemed impossible that there was ANY correlation between data in Table 2 and 3, especially R2=0.9860. Now, ALL 10wRMA and CRF correlations and predictions are based on Table 2 Runs' data — We're surprised.
CHALLENGE We challenge everybody to get a better correlation of Runs in Table 2 predicting VXX in Table 3. Until this happens, we would like to claim our correlation of R2=0.9860 in Chart 5 is the highest possible. Super techs and savvy mathematicians ought to win— we're neither. Winner prize and retraction in WSJ. Data
- Also surprising are logarithmic linearity of all Trends and the nearly identical slopes (0.0168,0.0177) and R2 (0.9558,0.9569) of VXX downward Trend lines in Chart 1 since Nov 23, 2011.
- These facts may be intuitively obvious but are important for projecting VXX price changes using Runs:
Today's Run will always either increase by "1" if positive, decrease by "1" if negative, or remain unchanged. First day of next Run after today is always "1" with sign opposite of today's Run-sign.VXX without Runs has no such predictable 'bounds'.
- 10wRMA is shaped like a sine wave in Trends' Time Spans and becomes a leading indicator of Trends' reversal by about half-way through Time Spans.
- Contributions of Runs to 10wRMA in Chart 3 are also shaped like a sine wave but only in the 'controlling' Contributions of Runs (+) or (-); e.g. Contributions of Runs (-) are shaped like a sine wave when 10wRMA is negative (-) and VXX is in a DOWN trend — and Contributions of Runs (+) are shaped like a sine wave when 10wRMA is positive (+) and VXX is in an UP trend.
- Steeper 10wRMA Slope, stronger 10wRMA move UP / DOWN.
- 10wRMA move-strength generally proportional to sum and # of consecutive same-sign Slopes but not always.
- Zero Slope, horizontal 10wRMA, no VXX change.
- Good traders and savvy investors might glean more buy/sell signals from Charts 1-7 — e.g. look at Slope and Slope Change, Charts 6-7, before and after where 10wRMA crosses X-axis = zero and where 10wRMA reverses direction. See patterns?
Charts 1-7
Charts 4,5 updated thru Nov 9 shows significant improvement using Segmented Data Regression and Correlation — R2 increased from 0.8561 to 0.9887
Chart 8-0318 VXX shows Reasons Why VXX VIX Volatility Crash May Have Turned DOWN Again and BACK ON DOWN Trend Line
Facts and Opinions - This technology correctly forecast and predicted VXX and VIX volatility trends UP / DOWN, 100% right, nothing wrong yet.
- We're not aware of any other way to do this.
- Time will tell if this technology is as powerful as it seems.
- This technology may have broader applicability to other stocks, ETF's and ETN's, especially those most volatile.
There are hidden secrets we can't find in this table to answer why so many 5-day Runs Jan 3, 2011 to Aug 31, 2012, 421 days
|
| Run |
|
|
| Run | Runs | # (-) | Days | %VXX | %VXX | # (+) | Days | 1 | 42 | 42 | -132.92 | 183.88 | 49 | 49 | 2 | 15 | 30 | -104.71 | 173.50 | 27 | 54 | 3 | 14 | 42 | -116.22 | 96.09 | 8 | 24 | 4 | 9 | 36 | -110.30 | 37.76 | 3 | 12 | 5 | 10 | 50 | -150.90 | 150.11 | 6 | 30 | 6 | 2 | 12 | -28.99 | 52.88 | 2 | 12 | 7 | 4 | 28 | -56.88 |
|
|
|
|
|
|
|
|
|
| Total | 96 | 240 | -700.92 | 694.21 | 95 | 181 |
We are unable to explain why this unusually high occurrence of 5-day positive runs compared to 4 and 6-day runs.
Table 5-1026 Runs History Updated and Expanded Summary
Table 5-1026 Data
NOTES 1) Weighting Factors f(X)=a+bXN and Moving Average Length can be easily adjusted for user preferences. There is an optimum set of constants a, b, N and Length for each user-preference and each data-set — and these constants can be changed over time X to compute Run Weighted Moving Averages with dynamic Weighting Factors. 2) Contributions of Runs (+) plus Contributions of Runs (-) may not equal 10wRMA because of data smoothing. 3) Cumulative Runs Factor is CRF=Sum(Runs to date from Jan 3, 2011). 4) Segmented Data Regression and Correlation are used with Cumulative Runs Factor CRF to achieve near-perfect correlation and predictions of actual VXX R2=0.9860 5) We're not aware of any other way to get this near-perfect correlation between variables that appear to have low correlation, especially since CRF is the cumulative sum of an alternating series of Runs (+) (-) calculated using only 13 Run-integers-7 to +6 — but CRF is now well correlated with 191+ VXX closes ranging from 34.84 to 213.48 from Feb 9, 2011 to Sep 28, 2012. 6) Theory of Segmented Data Regression and Correlation and results here suggest that recombinant correlation after all correlated segments are re-combined is always greater than the 'sum' of correlation of each segment and is always greater than before Segmented Data Regression and Correlation. If y=ax+b is the regressions trend line correlating y and x and y=VXX actual and x=CRF actual, then (VXX predicted)=a(CRF actual)+b, which essentially maps CRF domain into the VXX domain using Segmented Data Regression and Correlation. 7) Our attorney has advised us to remove this page from our site "in order to protect our proprietary rights." There must be a better solution. 8) As a calculations-example assuming Down Trend continues using the Trend Line equation in Chart 1, VXX would be:
f(x)=0.0166x-0.3132 R2=0.9558
=(Log(VXX)-1.402)*1.9
VXX =10^((0.0166*x-0.3132)/1.9+1.402)
where Run # x=30 on Oct 19, VXX actual=34.97
Assuming 13 Runs by Thanksgiving
Chart 9-1019
9) Summary data of VXX actual vs. CRF-predicted with Segmented Data Regression and Correlation through Oct 8 confirms near-perfect correlation: R2=0.9848
|
Log |
(VXX) |
|
Actual |
Predicted |
Sum |
361.167 |
361.161 |
Count |
182 |
182 |
Average |
1.984 |
1.984 |
StDevP |
0.206 |
0.205 |
Max |
2.329 |
2.317 |
My |
1.538 |
1.531 |
Frog says, "It just don't get no better" :)
10) Below are VXX Runs' beginning dates (yy-mm-dd)
Table 4-1024 208 VXX Runs' beginning dates from Jan 3, 2011 thru Oct 24, 2012
12-10-23 12-10-22 12-10-19 12-10-15 12-10-12 12-10-10 12-10-08 12-10-02 12-09-28 12-09-27 12-09-25 12-09-20 12-09-19 12-09-17 12-09-14 12-09-11 12-09-10 12-08-31 12-08-27 12-08-24 12-08-21 12-08-16 12-08-14 12-08-09 12-08-07 12-08-01 12-07-30 12-07-25 12-07-20 12-07-19 12-07-18 12-07-13 12-07-12 12-07-11 12-07-10 12-07-06 12-07-05 12-06-28 12-06-27 12-06-26 12-06-25 12-06-22 12-06-21 12-06-15 12-06-13 12-06-12 12-06-11 12-06-04 12-05-30 12-05-25 12-05-24 12-05-23 12-05-22 12-05-21 12-05-11 12-05-10 12-05-08 12-05-07 12-05-02 12-05-01 12-04-30 12-04-24 12-04-23 12-04-20 12-04-18 12-04-16 12-04-13 12-04-11 12-04-03 12-03-29 12-03-27 12-03-23 12-03-22 12-03-15 12-03-14 12-03-07 12-03-06 12-03-05 12-03-02 12-02-28 12-02-24 12-02-16 12-02-14 12-02-13 12-02-07 12-02-01 12-01-30 12-01-25 12-01-24 12-01-17 12-01-13 12-01-12 12-01-11 12-01-03 11-12-30 11-12-29 11-12-28 11-12-27 11-12-22 11-12-15 11-12-14 11-12-13 11-12-12 11-12-09 11-12-07 11-12-05 11-12-02 11-11-28 11-11-23 11-11-22 11-11-21 11-11-18 11-11-16 11-11-15 11-11-14 11-11-10 11-11-09 11-11-07 11-11-04 11-11-02 11-10-29 11-10-26 11-10-25 11-10-21 11-10-19 11-10-18 11-10-17 11-10-10 11-10-07 11-10-04 11-09-30 11-09-29 11-09-28 11-09-26 11-09-21 11-09-20 11-09-19 11-09-13 11-09-08 11-09-07 11-08-30 11-08-26 11-08-25 11-08-23 11-08-16 11-08-15 11-08-12 11-08-11 11-08-10 11-08-09 11-08-02 11-07-29 11-07-25 11-07-19 11-07-18 11-07-15 11-07-08 11-07-07 11-07-05 11-06-27 11-06-22 11-06-17 11-06-15 11-06-14 11-06-10 11-06-09 11-06-08 11-06-07 11-06-03 11-06-02 11-06-01 11-05-24 11-05-20 11-05-17 11-05-13 11-05-12 11-05-11 11-05-06 11-04-29 11-04-19 11-04-18 11-04-13 11-04-12 11-04-11 11-04-07 11-03-29 11-03-28 11-03-17 11-03-14 11-03-11 11-03-09 11-03-08 11-03-04 11-03-03 11-03-01 11-02-24 11-02-15 11-02-11 11-02-09 11-01-31 11-01-28 11-01-24 11-01-21 11-01-20 11-01-19 11-01-10 11-01-06 11-01-03
11) Tables 4 and 5 calculations
%VXX/Run/Day=(VXX close Run last day/VXX close day before Run begins - 1)*100
%VXX =(VXX close today/VXX close yesterday -1)*100
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