penta-secting $SPY

$SPY Penta-Section

By Penta-section what I mean is this: we divide the current day’s range into five segments. For example, assume high and low 100 and 105 respectively. If we were to divide the range between the high and the low into five segments, here is what we get:

  • Segment 1: 100-1o1
  • Segment 2: 101-102
  • Segment 3: 102-1o3
  • Segment 4: 103-104
  • Segment 5: 104-1o5

Now, if current open is say 100.5 then it falls under Segment 1; likewise, if current close is 102.3, then it falls under Segment 3, and we thus call it as O1C3 ( as an abbreviation for this study )

as you can see the OHLC values for 7 Oct 2013 for $SPY OHLC being , 167.42, 168.45 , 167.25 , 167.43 , and both the Open and Close falling under the segment 1 ( from 167.25 to  167.49 ) , we can mark it as O1C1

Why are we doing this penta-section on $SPY ? 

reason 1) data-mining  under the possible hangovers carried from previous day’s night drinks / wild thoughts by reading one of those top 10 trading books 

reason 2) inspired by “openings and closings that occur in various segments of a price bar” page 227-234 , of Day Trading With Short Term Price Patterns and Opening Range Breakout

reason 2-a)  Empirically. the trading volume , constructed for various half- an hour intervals is observed to be U- shaped for the day. In other words, the trading volume is high at the first half an hour and the last half an hour, and are lower during the middle of the trading day, rest of the various hours . Under the assumption that Open is controlled by amateurs and the close is controlled by the professionals, the penta-section tool is trying to quantify the trading day’s range in to the emotions of the amateur’s and the professional’s emotions by giving them a rating on a scale of 1-5 ( 1 being the lowest and 5 being the highest )

below the three studies of $SPY penta-section

$SPY overnight odds for various Penta-Sections

assuming we go long at close and exit at next open , when $SPY forms a type of penta-section, backtest period is from Jan 200o t0 7 Oct 2013

$SPY trading odds for overnight longs after various penta-section segments , since Jan 2000

$SPY Next Day Open to Close exits odds for various Penta-Sections

assuming we go long at next open and exit at next close when $SPY forms a type of penta-section, backtest period is from Jan 200o t0 7 Oct 2013

$SPY trading odds for longs from next open to next close after various penta-section segments , since Jan 2000

$SPY Current Close  to Next Close exits odds for various Penta-Sections

assuming we go long at current close and exit at next close when $SPY forms a type of penta-section, backtest period is from Jan 200o t0 7 Oct 2013

$SPY trading odds for longs from current close to next close after various penta-section segments , since  2000

 whats your limn of the $SPY and penta-section studies ??

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$SPY and Doji’s

$SPY and Doji’s 


$SPY Doji Candle Stock Pattern

With $SPY posting a Doji candle stick pattern on 7 Oct 2013 , below few studies ,

firstly Doji definition,

Doji: On a candlestick chart, a Doji is defined as the one , when the open price and close price are the same, or the difference between the open and the close is very small. “Very small” is a relative term, so we have taken the range for the day as the reference. For example, if the range for the day is 1 point and if the absolute difference between open and close is 0.01 points, we have called it as a 1% Doji ,

with 7 Oct 2013, $SPY OHLC values being , 167.42, 168.45 , 167.25 , 167.43 , the range being , 1.2 points and the absolute difference between open and close , being 0.01 points , we can qualify that as a 1% Doji .

below the few combinations of trading studies

$SPY posts a Doji 

below the trading odds for longs , with various exit periods ( t+1, being the exit after 1 trading days , and t+20 being the exit after 20 trading days etc.) , the backtest period is from Jan 2000.

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 40 18 45.0 -0.28 -0.12 1.10 -1.40 0.78
t+2 40 20 50.0 -0.37 0.00 1.27 -2.01 0.63
t+3 40 22 55.0 0.24 0.22 1.65 -1.49 1.11
t+4 40 22 55.0 -0.14 0.22 1.45 -2.08 0.70
t+5 40 23 57.5 -0.47 0.26 1.26 -2.81 0.45
t+10 40 23 57.5 -0.34 0.52 1.84 -3.29 0.56
t+20 40 24 60.0 0.65 1.60 3.15 -3.11 1.01

$SPY posts a Doji & $SPY Closed down for the day 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 21 6 28.6 -0.84 -0.38 0.97 -1.56 0.62
t+2 21 9 42.9 -0.75 -0.19 1.08 -2.13 0.51
t+3 21 12 57.1 0.44 0.39 1.83 -1.41 1.30
t+4 21 12 57.1 -0.04 0.16 1.37 -1.93 0.71
t+5 21 11 52.4 -0.77 0.45 1.29 -3.03 0.43
t+10 21 12 57.1 -0.50 0.61 2.13 -4.00 0.53
t+20 21 12 57.1 0.63 0.35 3.52 -3.23 1.09

$SPY posts a Doji & $SPY Closed above 200 DMA 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 27 14 51.9 0.04 0.03 0.84 -0.83 1.02
t+2 27 15 55.6 0.14 0.22 1.09 -1.05 1.05
t+3 27 15 55.6 0.12 0.07 1.14 -1.16 0.99
t+4 27 16 59.3 0.08 0.28 1.07 -1.35 0.79
t+5 27 17 63.0 0.11 0.28 1.01 -1.42 0.71
t+10 27 17 63.0 0.56 0.69 1.91 -1.75 1.09
t+20 27 18 66.7 1.23 1.79 2.83 -1.96 1.45

$SPY posts a Doji & $SPY Closed below 50 DMA 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 12 5 41.7 -1.01 -0.48 1.25 -2.62 0.48
t+2 12 6 50.0 -1.04 -0.19 1.55 -3.62 0.43
t+3 12 8 66.7 0.78 1.16 2.15 -1.95 1.10
t+4 12 6 50.0 -0.16 0.00 2.20 -2.53 0.87
t+5 12 5 41.7 -1.29 -1.12 2.24 -3.81 0.59
t+10 12 6 50.0 -1.44 -0.41 2.05 -4.92 0.42
t+20 12 6 50.0 -0.01 -0.51 3.65 -3.68 0.99

$SPY posts a Doji & $SPY Closed below 20 DMA 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 12 5 41.7 -1.06 -0.47 1.25 -2.70 0.46
t+2 12 7 58.3 -0.68 0.84 1.60 -3.87 0.41
t+3 12 7 58.3 0.82 1.60 2.63 -1.72 1.53
t+4 12 5 41.7 -0.61 -0.62 2.41 -2.76 0.87
t+5 12 5 41.7 -1.40 -1.12 2.25 -4.00 0.56
t+10 12 6 50.0 -1.67 -0.22 2.43 -5.77 0.42
t+20 12 6 50.0 -0.56 -0.51 3.30 -4.41 0.75

looking at few of the red highlighted , in the above studies , looks like downward bias might continue for the next 1 or 2 trading days .

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$SPY down for 2nd and 3rd trading day after up on 1st trading day – bit bearish

$SPY down for 2nd & 3rd trading day after up on 1st trading day

$SPY Stock Chart

With $SPY down for both the 2nd and 3rd trading day , while the first trading day was , below few studies ..

pattern 1) $SPY down for 2nd & 3rd trading day after being up on 1st trading day

below the trading odds for longs , with various exit periods ( t+1, being the exit after 1 trading days , and t+20 being the exit after 20 trading days etc.) , the backtest period is from Jan 2000.

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 25 10 40.0 -0.70 -0.46 0.68 -1.62 0.42
t+2 25 8 32.0 -0.99 -0.61 1.23 -2.04 0.61
t+3 25 11 44.0 -0.93 -0.40 0.89 -2.36 0.38
t+4 25 9 36.0 -1.39 -0.70 0.79 -2.62 0.30
t+5 25 11 44.0 -1.22 -0.40 0.75 -2.77 0.27
t+10 25 14 56.0 -0.07 0.32 2.61 -3.48 0.75
t+20 25 14 56.0 -0.02 0.57 3.14 -4.04 0.78

as you can see in the above table the trading odds for longs are not encouraging !!

{ Free to Download } Anatomy of $SPY on First Trading Day of the Month 

pattern 2) $SPY down for 2nd & 3rd trading day after being up on 1st trading day , and on the 3rd trading day $SPY erased all the gains made on the 1st trading day

an easy language code would look like ,

trade_day[0]=3 && Close[0]<Close[1] && Close[1]<Close[2] && Close[2]>Close[3]&& Close[0]<Close[3]

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off
t+1 20 7 35.0 -0.82 -0.64 0.81 -1.69 0.48
t+2 20 6 30.0 -1.09 -0.70 1.35 -2.14 0.63
t+3 20 9 45.0 -1.05 -0.37 0.95 -2.70 0.35
t+4 20 8 40.0 -1.49 -0.77 0.67 -2.92 0.23
t+5 20 9 45.0 -1.48 -0.42 0.72 -3.29 0.22
t+10 20 10 50.0 -0.61 0.08 2.59 -3.82 0.68
t+20 20 9 45.0 -0.86 -0.33 3.01 -4.04 0.75

again the odds for longs are not that favorable !!

Below the historical instances of $SPY gaining on 1st trading day , while the 2nd and 3rd tradings were down. since 2000

Date Close 3rd Trading Day 2nd Trading Day 1st Trading Day t+1 t+2 t+3 t+4 t+5
03-Oct-13 167.62 -0.92 -0.09 0.79 ?? ?? ?? ?? ??
05-Jun-13 159.64 -1.4 -0.48 0.55 0.91 2.19 2.19 1.13 0.3
03-May-12 134.85 -0.76 -0.3 0.62 -1.62 -1.55 -1.94 -2.52 -2.32
04-Apr-12 135.44 -0.99 -0.41 0.73 -0.05 -1.17 -2.84 -2.05 -0.77
05-Mar-12 131.85 -0.41 -0.3 0.51 -1.46 -0.77 0.21 0.6 0.61
05-May-10 108.64 -0.59 -2.35 1.29 -3.32 -4.76 -0.56 -0.85 0.53
03-Dec-09 101.68 -0.78 -0.05 1.23 0.57 0.42 -0.7 -0.32 0.24
06-Jul-09 82.33 -0.01 -2.73 0.42 -1.93 -2 -1.81 -2.05 0.34
03-Oct-08 99.08 -1.34 -3.63 0.06 -5.1 -9.35 -11.63 -17.8 -19.79
05-Feb-08 118.56 -2.68 -1.26 1.61 -0.8 -0.15 -0.79 -0.29 0.64
03-Oct-07 135.21 -0.2 -0.14 1.13 0.16 1.35 0.81 1.76 1.59
03-Mar-06 109.72 -0.46 -0.01 0.89 -0.46 -0.61 -0.4 -1.07 -0.13
03-Feb-06 107.6 -0.5 -1.16 0.7 0.26 -0.62 0.28 0.11 0.3
04-Aug-04 91.19 -0.01 -0.77 0.21 -1.62 -3.04 -2.9 -1.64 -1.84
04-Feb-04 92.72 -0.82 -0.16 0.43 0.29 1.42 1.45 1.78 2.86
03-Dec-03 87.63 -0.16 -0.25 1.08 0.41 -0.29 0.39 -0.39 -0.4
05-Feb-03 68.6 -0.62 -0.98 0.19 -0.48 -1.69 -0.99 -1.68 -3.25
04-Dec-02 74.38 -0.44 -1.35 0.16 -1.1 -0.46 -3.2 -1.9 -1.82
03-Oct-02 66.22 -1.02 -2.99 4.8 -1.84 -3.87 -2.36 -5.12 -2.04
03-May-02 85.86 -1.08 -0.39 1.22 -1.96 -2.31 1.33 0.16 -1.72
03-Apr-02 90.3 -0.7 -0.55 0.04 -0.42 -0.4 -0.19 -0.89 0.24
05-Jul-01 96.14 -1.96 -0.02 1.25 -2.15 -1.62 -2.81 -2.7 -0.4
03-May-01 98.65 -1.27 -0.18 0.3 1.7 0.83 0.78 0.35 0.65
06-Sep-00 116.91 -1.14 -0.8 0.1 0.86 0.17 0.03 -0.7 -0.44
03-May-00 109.77 -2.34 -2 1.36 0.76 1.98 1.2 0.4 -1.86
05-Apr-00 116.35 -0.62 -0.75 0.58 0.87 1.51 1.11 0.82 -1.95

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Anatomy of S&P 500 Index 5-Day losing streaks : e-book

Anatomy of S&P 500 Index 5-Day losing streaks : e-book

Anatomy of S&P 500 Index 5- Day losing streaks

 

Anatomy of S&P 500 Index 5-Day losing streaks : e-book Table of Contents

  1. Disclaimer……6
  2. Feedback……6
  3. Introduction……9
  4. 5 Day Losing Streaks……10
  5. Moving Averages……12
  6. Current Day’s Loss %……15
  7. Magnitude Of Current Day’s Loss……18
  8. Magnitude Of Loss % Over Last 5 Trading Days……20
  9. Month Low And Year Low……23
  10. Month High And Year High……25
  11. Volume……26
  12. Narrow Range And Wide Range……28
  13. ROC……31
  14. Bollinger Bands……34
  15. Lower Highs And Lower Lows……37
  16. After Not Having Done So……39
  17. For The First Time In The Year……41
  18. Seasonality – Day Of The Week……44
  19. Seasonality – Month……46
  20. Seasonality – By # Trading Week/Day……49
  21. Seasonality – By Quarter / Half……52
  22. 20 Trading Strategies Collection with 75% Win Rate ……54
  23. Self – Promo’s/ Coupon Codes……55
  24. Sayonara……58
ps: we would publish the results of our Pay What You Want experiment , after 1000 downloads ,  please make it happen , by being social , the share buttons are right below !! 
pps: your e-mail will be shared with NSA only upon request 🙂 and will not be used for purposes other than sending an alert , when this e-book is updated or a similar e-book of any kind is published #HTH
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3 bar decline pattern on $SPY – suggesting a bounce for tomorrow

3 bar decline pattern on $SPY 

Below the trading strategy ( a.k.a “3 bar decline” )  patter that triggered today at close , suggesting a bounce for the next day

1 bar decline definition

today’s open < prev day’s open && today’s high < prev day’s high && today’s low < prev day’s low && today’s close < prev day’s close

Here are the trading strategy rules that we employed

  • $SPY posts 3 bar decline
  • go Long at close ( i.e as on 24th Sep 2013 ,close)
  • exit at close at the next trading session ( i.e 25th Sep 2013, open)

Below the backtest performance summary of “3 bar decline pattern on $SPY  trading strategy”, since 2000.

go long at close when $SPY posts a 3 bar decline pattern and exit at next close , trading strategy , backtest performance summary since 2000

what if today is 3rd day of the week ? 

yes excel the tool we use considers Tuesday to be third day of week , and taking into account that , TA-25 ( Tel Aviv 25 ) starts opening on Sunday ,we might well call Tuesday to be the third day of the week 🙂

below the backtest performance summary of “go long at close when $SPY posts a 3-bar decline on 3rd day of week and exit at next close” trading strategy perfromance , since 2000.

  • Winners : 9
  • Losers : 2
  • % Winners : 82%
  • Average Change % : 1.41
  • Median Change % : 0.64
  • Maximum Gain % : 5.97
  • Maximum Loss % : -1.22
  • Average Gain %if Winner : 1.91
  • Average Loss % if Loser : -0.82
  • Average Gain % / Average Loss % : 2.33
  • Profit Factor : 10.30
  • Out-liar Adjusted Profit Factor : 7.55

below the last 25 trades generated by the “3 bar decline pattern on $SPY” for the readers to replicate the trading strategy in thier backtesting platforms !!

Date Close Lower Open Sequence Lower High Sequence Lower Low Sequence Lower Close Sequence Next Day Change Next Day Change %
24-Sep-13 169.53 3 3 3 4 ?? ??
19-Aug-13 163.97 3 4 3 4 0.81 0.49
10-Oct-12 140.21 3 3 3 3 0.08 0.06
04-Jun-12 124.05 4 4 3 4 0.94 0.76
18-May-12 125.64 6 5 6 6 2.16 1.72
17-May-12 126.72 5 4 5 5 -1.08 -0.85
16-May-12 128.63 4 3 4 4 -1.91 -1.48
10-Apr-12 131.6 4 5 4 5 1.07 0.81
09-Apr-12 133.85 3 4 3 4 -2.25 -1.68
25-Nov-11 111.46 8 8 4 7 3.23 2.9
23-Nov-11 111.67 7 7 3 6 -0.21 -0.19
06-Sep-11 111.51 3 3 3 3 3.14 2.82
08-Aug-11 107 5 5 11 3 4.98 4.65
29-Jul-11 123.27 3 6 5 5 -0.52 -0.42
12-Jul-11 125.24 3 3 3 3 0.42 0.34
08-Jun-11 121.8 6 5 6 6 0.93 0.76
07-Jun-11 122.31 5 4 5 5 -0.51 -0.42
06-Jun-11 122.39 4 3 4 4 -0.08 -0.07
05-May-11 126.72 3 3 4 4 0.56 0.44
24-Feb-11 123.64 3 3 3 3 1.32 1.07
12-Aug-10 101.5 3 3 3 3 -0.3 -0.3
01-Jul-10 96.02 3 8 3 4 -0.52 -0.54
24-Jun-10 100.37 3 3 4 4 0.42 0.42
06-May-10 105.03 4 5 3 3 -1.56 -1.49
28-Oct-09 96.18 3 3 3 4 2.07 2.15

SSRN paper that we are reading for the week

The Price of Wine by Prof, Elroy Dimson  (London Business School; University of Cambridge – Judge Business School) , Peter L. Rousseau (Vanderbilt University – Department of Economics) and Christophe Spaenjers (HEC Paris – Finance Department) published on September 6, 2013

Brief Summary : 

The  geometric average real return of 5.3% between 1900 and 2012. Taking into account storage and insurance costs lowers this estimate to 4.1%. Over our time frame, wine has been outperformed by equities, and that transaction costs may further reduce the relative attractiveness of wine. However, the performance of wine has been better than that of art and stamps—assets for which aging matters much less. In line with expectations, there was an evidence of positive correlation between the equity and the wine market.

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When $SPY prints an open equals high price pattern – what next ?

$SPY prints an open equals high price pattern

With $SPY printing Open equals High Price bar , below trading study triggered.

Here are the “$SPY posts an Open equals High price bar” trading strategy rules we employed.

  • $SPY current Open equals High ( there must be a Japanese candle stick name for this , which am not able to recollect , if the reader is aware , please do so by posting a comment)
  • go short at close ( as on 20 Sep 2013)
  • buy to cover after five trading days day at close ( i.e 27 Sep 2013)

Below the backtest performance summary of “”$SPY posts an Open equals High price bar trading strategy , since Jan 2000.

ps: for interleaving trades generatedShort $SPY when Open equals high and buy to cover five trading days later, trading strategy , backtest performance summary since 2000

Below the historical trade details , generated by “$SPY posts an Open equals High price bar” trading strategy , and the change , and change% , details after next five trading days.

Date Open High Low Close Loss % Change 5 Trading days later Change% 5 Trading days later
20-Sep-13 172.33 172.33 170.58 170.72 -0.7 ?? ??
19-Oct-12 142.43 142.44 139.99 140.32 -1.67 -2 -1.43
10-Jun-09 87.04 87.05 84.96 86.06 -0.25 -2.6 -3.02
23-Feb-09 70.85 70.85 67.52 67.57 -3.58 -3.66 -5.42
03-Jul-08 113.47 113.47 111.58 112.76 0.1 -2.2 -1.95
20-Jun-07 134.4 134.4 132.1 132.26 -1.39 -0.64 -0.48
05-Jun-06 110.24 110.25 108.46 108.76 -1.45 -2.68 -2.46
08-Apr-04 95.16 95.16 93.78 94.3 -0.23 -0.44 -0.47
18-Nov-02 74.13 74.13 72.69 72.79 -1.01 2.42 3.32
09-Apr-02 90.33 90.33 89.33 89.5 -0.7 0.85 0.95
04-Feb-02 89.31 89.31 87.09 87.42 -2.49 1.27 1.45
03-Aug-01 96.68 96.68 95.53 96.35 -0.55 -2.09 -2.17
06-Jun-01 101.51 101.51 100.35 100.64 -0.83 -2.31 -2.3
23-May-01 103.26 103.26 101.84 101.84 -1.69 -2.6 -2.55
09-Mar-01 99.08 99.08 96.73 96.93 -2.96 -6.31 -6.51
14-Feb-01 104.23 104.23 102.67 103.77 -0.15 -4.91 -4.73
09-Feb-01 104.79 104.79 103.14 103.6 -0.96 -1.13 -1.09
19-Jan-01 107.02 107.02 105.2 105.31 -0.57 1.46 1.39
15-Dec-00 104.61 104.61 102.59 102.91 -2.31 -0.02 -0.02
08-Nov-00 112.89 112.89 110.15 110.15 -2.22 -0.78 -0.71
09-Oct-00 110.75 110.75 109.23 109.72 -0.75 -1.42 -1.29
18-Aug-00 117.56 117.56 116.65 117.02 -0.33 1.22 1.04
21-Jul-00 117.06 117.06 115.45 115.45 -1.95 -4.38 -3.79
18-Jul-00 117.75 117.75 116.74 117.08 -0.81 -1.92 -1.64
16-Jun-00 115.93 115.93 114.03 114.59 -0.83 -1.73 -1.51
12-Jun-00 114.62 114.62 112.99 112.99 -1.16 3.07 2.72
03-May-00 112.3 112.3 109.01 109.77 -2.34 -2.04 -1.86
18-Feb-00 108.04 108.04 104.73 105.26 -2.15 0.64 0.61
17-Feb-00 109.25 109.25 107.52 107.57 -0.52 -3.85 -3.58
14-Feb-00 108.74 108.74 107.59 108.52 0.58 -3.53 -3.25
09-Feb-00 112.38 112.38 109.89 109.9 -2.1 -1.77 -1.61
21-Jan-00 113.18 113.18 112.06 112.36 -0.21 -6.66 -5.93
20-Jan-00 114.33 114.33 111.87 112.6 -1.53 -3.5 -3.11
12-Jan-00 112.48 112.48 111.15 111.29 -1 1.31 1.18
03-Jan-00 115.33 115.33 111.93 113.14 -0.98 0.63 0.56

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When $SPX closes in the bottom 10% of the monthly range

When $SPX closes in the bottom 10% of the monthly range 

with the $SPX monthly OHLC for August being , 1689.42, 1709.67 ,1627.47 ,1632.97

giving us the closing price range value as , (Close-Low)/(High-Low) , (1632.97-1627.47)/(1709.67-1627.47) = 6.69%

We looked at what happens in the next month , when $SPX closes in the bottom 1o% of the monthly range

Winning odds for the next month  after $SPX closes in the bottom 10% of the monthly range, since 1950

  • Winners : 34
  • Losers : 14
  • % Winners : 71%
  • Average Change % : 1.69
  • Median Change % : 1.75
  • Maximum Gain % : 16.30
  • Maximum Loss % : -14.58
  • Average Gain %if Winner : 4.22
  • Average Loss % if Loser : -4.44
  • Average Gain % / Average Loss % : 0.95

Winning Odds for any random month for $SPX ,  since 1950

  • Winners : 452
  • Losers : 311
  • % Winners : 59%
  • Average Change % : 0.69
  • Median Change % : 0.91
  • Maximum Gain % : 16.30
  • Maximum Loss % : -21.76
  • Average Gain %if Winner : 3.34
  • Average Loss % if Loser : -3.18
  • Average Gain % / Average Loss % : 1.05

Lets tweak a further with the following rules.

  • $SPX closes in the bottom 10% of the monthly range
  • $SPX close is above 10-month moving average

Winning odds for the next month  after $SPX closes in the bottom 10% of the monthly range, and $SPX closes above 10 month moving average, since 1951

  • Winners : 20
  • Losers : 4
  • % Winners : 83%
  • Average Change % : 2.12
  • Median Change % : 2.39
  • Maximum Gain % : 8.31
  • Maximum Loss % : -14.58
  • Average Gain %if Winner : 3.45
  • Average Loss % if Loser : -4.51
  • Average Gain % / Average Loss % : 0.76
  • Average Absolute Change% : 3.18

Lets tweak a bit further with the following rules.

  • $SPX closes in the bottom 10% of the monthly range
  • $SPX close is above 10-month moving average
  • $SPX closes in red for the month

Winning odds for the next month  after $SPX closes in the bottom 10% of the monthly range, and $SPX closes above 10 month moving average, and $SPX closed in red for the month since 1951

  • Winners : 19
  • Losers : 3
  • % Winners : 86%
  • Average Change % : 2.21
  • Median Change % : 2.39
  • Maximum Gain % : 8.31
  • Maximum Loss % : -14.58
  • Average Gain %if Winner : 3.43
  • Average Loss % if Loser : -5.53
  • Average Gain % / Average Loss % : 0.62
  • Average Absolute Change% : 3.18

Below the table with $SPX change % details for the next month,

$SPX closes in the bottom 10% of the monthly range, and $SPX closes above 10 month moving average, and $SPX closed in red for the month , since 1951

Date Open High Low Close Close Range % Cls/10-MA Loss% Next Month Change%
Aug-13 1689.42 1709.67 1627.47 1632.97 6.69 1.05 -3.13 ??
Jan-10 1116.56 1150.45 1071.59 1073.87 2.89 1.06 -3.70 2.85
Jul-07 1504.66 1555.9 1454.25 1455.27 1 1.01 -3.20 1.29
Dec-05 1249.48 1275.8 1246.59 1248.29 5.82 1.03 -0.10 2.55
Jun-05 1191.5 1219.59 1188.3 1191.33 9.68 1.02 -0.01 3.60
Apr-04 1126.21 1150.57 1107.23 1107.3 0.16 1.03 -1.68 1.21
Jul-99 1372.71 1420.33 1328.49 1328.72 0.25 1.05 -3.20 -0.63
Jul-98 1133.84 1190.58 1114.3 1120.67 8.35 1.07 -1.16 -14.58
Aug-97 954.29 964.17 893.34 899.47 8.65 1.09 -5.75 5.32
Mar-97 790.82 814.9 756.13 757.12 1.68 1.05 -4.26 5.84
Jan-92 417.03 421.18 408.64 408.78 1.12 1.05 -1.99 0.96
Nov-84 166.09 170.41 162.99 163.58 7.95 1.03 -1.51 2.24
Oct-83 165.99 172.65 162.86 163.55 7.05 1.02 -1.52 1.74
Jan-81 135.76 140.32 128.57 129.55 8.34 1.05 -4.57 1.33
Jul-71 99.16 101.52 95.08 95.58 7.76 1.00 -3.16 3.61
Oct-67 96.71 98.25 93.29 93.3 0.2 1.02 -3.53 0.75
May-67 94.01 95.25 88.71 89.08 5.66 1.06 -5.24 1.75
Feb-63 66.31 66.96 64.08 64.29 7.29 1.07 -2.89 3.55
Jun-61 66.56 67.08 64.47 64.64 6.51 1.06 -2.88 3.28
Oct-54 32.29 32.76 31.68 31.68 0 1.09 -1.95 8.08
Aug-54 30.99 31.21 29.83 29.83 0 1.08 -3.40 8.31
Sep-51 23.28 23.71 23.26 23.26 0 1.06 -0.09 -1.38
Jun-51 21.48 22.05 20.96 20.96 0 1.00 -2.60 6.87

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$SPY Posts a 1.5% Range Trend Sell Day , Buy at Next Open Trading Strategy Since 2009

$SPY Posts a 1.5% Range Trend Sell Day , Buy at Next Open

Trend Sell Day is defined as a day with the open is at the top 20 % of  intra-day’s range and the close is in the bottom 20 % of the intra-day’s range .

For example, Yesterday’s ( 12 Jun 2013) $SPY OHLC ( Open , High , Low , Close) were 164.22 , 164.39 , 161.6 , 161.75, giving us the open’s position in the  intra-day range as top 6% ( ( High-Open)/(High-Low)), while the close’s position in the intra-day range as bottom 5% (( Close-Low)/(High-Low))

1.5% range or range is defined as , (High-Low)/Average(High,Low) expressed in percentage terms , for yesterday the $SPY range% is 1.71

here are the trading system rules we employed

  • $SPY posts a trend sell day previous trading day
  • $SPY previous day range is more than 1.5% ( we are taking 1.5% as a cutoff value because we are rounding yesterday’s range to the nearest number)
  • Go long at open
  • Exit at the close

below the backtest performance summary of  “$SPY Posts a 1.5% Range Trend Sell Day , Buy at Next Open Trading Strategy” since 2009

$SPY Posts a 1.5% Range Trend Sell Day , Buy at Next Open Trading Strategy Since 2009

We are merely revealing this over optimization variant via day of the week technique ( even though not applicable for today), if you restrict this trade to only Mondays and Tuesdays Openings , while the previous trading day was a 1.5% trend sell day .

here the backtest performance summary report , which stunned us !!!

$SPY Posts a 1.5% Range Trend Sell Day , Buy at Next Open if it is Mon or Tue, Trading Strategy Since 2009

Next time keep an alert to Monday/Friday Trend Sell Day sell-offs .

below the last 25 historical trades generated by $SPY Posts a 1.5% Range Trend Sell Day , Buy at Next Open Trading Strategy”  for your reference and if you want to replicate this strategy coding in the platform of your choice !!

Date Open High Low Close Close-Open Close – Open %
13-06-2013 161.66 ?? ?? ?? ?? ??
16-04-2013 156.29 157.49 155.91 157.41 1.12 0.72
26-02-2013 149.06 149.54 148.08 149.36 0.3 0.2
15-11-2012 134.43 134.93 133.64 134.15 -0.28 -0.21
05-11-2012 139.74 140.55 139.32 140.23 0.49 0.35
22-10-2012 141.51 142.03 140.65 141.77 0.26 0.18
26-09-2012 142.42 142.46 141.31 141.65 -0.77 -0.54
11-07-2012 131.97 132.35 131.15 131.92 -0.05 -0.04
22-06-2012 130.91 131.48 130.40 131.23 0.32 0.25
12-06-2012 128.92 130.12 128.31 130.03 1.11 0.86
21-05-2012 127.33 129.15 127.12 129.10 1.77 1.39
18-05-2012 128.51 128.74 126.73 126.92 -1.59 -1.24
11-04-2012 134.30 134.55 133.78 134.02 -0.28 -0.21
20-12-2011 119.00 120.90 117.23 120.70 1.7 1.43
09-12-2011 120.51 122.31 120.40 122.00 1.49 1.24
26-10-2011 120.35 120.75 118.28 120.30 -0.05 -0.04
22-09-2011 109.61 110.54 107.72 109.23 -0.38 -0.34
26-08-2011 111.39 114.11 109.62 113.59 2.2 1.97
23-08-2011 108.94 112.24 108.39 112.11 3.17 2.91
05-08-2011 117.24 117.54 112.52 115.62 -1.62 -1.38
28-07-2011 125.75 126.87 125.18 125.38 -0.37 -0.29
02-06-2011 126.43 126.70 125.47 126.21 -0.22 -0.17
02-03-2011 124.73 125.75 124.35 125.17 0.44 0.35
31-01-2011 122.18 122.86 121.87 122.76 0.58 0.48
22-07-2010 102.26 103.77 102.25 103.32 1.06 1.03

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$SPY Close to Close Price Patterns

$SPY Close to Close Price Patterns

With $SPY for the last 7 days doing  down/up/down/up/down/up/ now down & inspired by the cult classic “Day Trading With Short Term Price Patterns and Opening Range Breakout” by Toby Cable

from the Section-II Short Term Price Patterns , Chapter 6 Close to Close ( on Bonds) ,

Here we tested all one , two , three, four, five day close to close ( C/C) patterns on $SPY , entry was assumed on the last close of the pattern with the exit on the next day’s close.

Now a few examples to help clarify the close-to-close price patterns:

DDUUD: The latest day (today) was a down close, yesterday was an up close, the day before yesterday was an up close, 3 day ago was a down close, 4 days ago was also a down close.
UDDDU: The latest day (today) was an up close, yesterday was a down close, the day before yesterday (i.e. 2 days ago) was a down close, 3 days earlier was a down close, 4 days ago was an up close.
DDDUU: The latest day (today) was an up close, yesterday was also an up close, the day before yesterday (i.e. 2 days earlier) was a down close, 3 days ago was a down close, and 4 days ago was also a down close.
UUDDD: The latest day (today) was a down close, yesterday was a down close, the day before yesterday (i.e. 2 days earlier) was a down close, 3 days ago was an up close, and 4 days ago was also an up close.

Glossary of the columns used 

Pattern is the price patterns
Wins Total number of trades that were profitable assuming one goes long after the price pattern
Loss Total number of trades that were unprofitable.
%Wins : Number of winning trades
Avg: Avg gain/loss for the price pattern
Avg Win : Average amount of profit for the profitable trades.
Avg Loss: Average amount of loss for the losing trades.
Win / Loss Ratio: The average profit of all winning trades divided by the average loss of all losing trades. Please note that it is not the number of winning trades divided by the number of losing trades.
Gross P&L:  Total profit achieved by the price pattern, it is simply an arithmetic sum of the next day $SPY change in percentages

The test period if from 5 Feb 1993 till 3rd Jun 2013

A listing of the $SPY close -to-close patterns is given in below tables for one – to – four days.

$SPY 1, 2, 3, 4 close-to-close price patterns since Feb 1993

as a naked eye can notice , anything ending with D is positive the next day in average returns terms , hence the acronym BTFD 🙂 on the trading desks ??

A listing of the $SPY close -to-close patterns is given in below tables for five days.$SPY five days close-to-close price patterns since Feb 1993

the current five day price pattern combo of DUDUD  has occurred 157 times on $SPY since Feb 1993, with 87 times $SPY gaining next day with an average gain of of 0.06% , with a pay-off ratio of 1.02 

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TradeIdea : Materials Select Sector SPDR $XLB Forms Bull Hook Price Pattern

Materials Select Sector $XLB Forms Bull Hook Price Pattern

Materials Select Sector SPDR (XLB) Bullhook Price Pattern Stock Chart

Materials Select Sector SPDR ( $XLB ) forms a Bull Hook Price Pattern 

  • $XLB forms bull hook price pattern
  • Go Long at close
  • Exit at next trading day’s close

Bull Hook Price Pattern Definition :

Bull Hook Price Pattern is authored by Toby Crabel first in Stocks and Commodities Magazine and is defined, as

A bull hook day opens above the previous day’s high and closes below the previous day’s close with a narrowing range.

Below the backtest performance summary for going Long when “XLB forms a bull hook price pattern ” trading system during the last four years.

Go Long when XLB ETF forms a bull hook price pattern back test performance summary
Total number of trades 14 Percent profitable 93%
Number of winning trades 13 Number of losing trades 1
Average profit per trade % 1.06 Median trade 0.63
Average winning trade % 1.34% Avg Loss Trade % -2.56%
Largest winning trade % 3.96% Max Loss Trade % 2.56%
Max consecutive winners 13 Max Consecutive Losses 1
Ratio avg win/avg loss % 0.52 T-Test 2.47
Profit Factor 6.82 Outlier Adjusted Profit Factor 5.34

Below the details of next day change, change% of $XLB ETF Price, when  XLB ETF forms a bull hook price pattern , during the last 4 years

XLB ETF next day change , change % for last 4 years, when ever XLB forms a bull hook price pattern 
Date 1 Day Change 1 Day Change %
09-May-13 ?? ??
11-Feb-13 0.02 0.05
19-Dec-12 0.36 0.98
22-May-12 0.39 1.19
24-Feb-12 0.01 0.03
26-Jan-12 0.05 0.14
24-Jun-11 0.07 0.19
11-Oct-10 0.09 0.28
26-Aug-10 0.84 2.98
21-Jul-10 0.61 2.15
12-Jul-10 0.75 2.7
26-May-10 1.1 3.96
08-Feb-10 0.68 2.46
10-Dec-09 0.08 0.27
23-Oct-09 -0.74 -2.56

Could we get 14th time lucky this time ??

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hi there ,  don’t put funny queries like number of trades > 100 & win rate > 90% etc , if such kind of trades exist we won’t be starting out this portal , nor we would be blogging  ..