$FDX unfilled gap up closings post ER , since Jan 2000

$FDX unfilled gap up closings post ER , since Jan 2000

$fdx stock chartwith $FDX posting an unfilled gap up ( current low > previous close) , below the trading odds for $FDX longs after an unfilled gap up on ER day since Jan 2000 ,

for a 1o trading day’s holding period

  • Winners : 13
  • Losers : 3
  • % Winners : 81%
  • Average Change % : 3.73
  • Median Change % : 3.07
  • Maximum Gain % : 8.91
  • Maximum Loss % : -2.05
  • Average Gain %if Winner : 4.90
  • Average Loss % if Loser : -1.34
  • Payoff Ratio 3.67

for a 20 trading day holding period 

  • Winners : 12
  • Losers : 4
  • % Winners : 75%
  • Average Change % : 4.43
  • Median Change % : 5.53
  • Maximum Gain % : 18.07
  • Maximum Loss % : -5.03
  • Average Gain %if Winner : 6.98
  • Average Loss % if Loser : -3.23
  • Payoff Ratio 2.16

Historical instances of $FDX unfilled gap up closings post ER , since Jan 2000

$FDX unfilled gap up closings on ER day's since Jan 2000

 

 

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

 

$INTC 5% ++ gap up openings since 2000

$INTC 5% ++ gap up openings since 2000

with $INTC set to open with a gap up opening of 7.3% at ~ 29.99 ( at the time of writing ) , below the trading odds for the longs taken at open with exit set to close , when ever $INTC opens with 5% or more gap up opening , since 2000.

  • Winners : 12
  • Losers : 15
  • % Winners : 44%
  • Average Change % : 0.15
  • Median Change % : -0.26
  • Maximum Gain % : 7.05
  • Maximum Loss % : -7.58
  • Average Gain %if Winner : 3.13
  • Average Loss % if Loser : -2.24
  • Payoff Ratio 1.40
  • Average Absolute Change% : 2.09

few statistics that might help the scalpers 

  • 100% of the times moved higher than open , when $INTC opened with more than 5% of gap up , with an average change from the open to the high of the day standing at 2.3% , while the median change % from open to high stands at 0.91% .
  • 100% of the times moved lower than open , when $INTC opened with more than 5% of gap up, with an average change % from open to the low of the day standing at -2.9% , while the median change% from open to low stands at -2.3%

Below the table with details of $INTC 5% or more gap up openings since 2000.

$INTC 5% ++ gap up openings since Jan 2000

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

updated blog post -> $AAPL Stock Price During the WWDC Since 2003

  $AAPL Stock Price During the WWDC Since 2003

WWDC 2014

with $AAPL Worldwide Developers Conference -2014 , to start from 2nd June 2014 , below how the stock price behaved during the the week of WWDC since 2003. 

below the trading odds for the $AAPL longs from open prince on the WWDC start till the closing price of WWDC end , since 2003 .

  • Winners : 0
  • Losers : 11
  • % Winners : 0%
  • Average Change % : -4.88
  • Median Change % : -4.76
  • Maximum Gain % : -1.85
  • Maximum Loss % : -9.07
  • Average Gain %if Winner : NA
  • Average Loss % if Loser : -4.88
  • Payoff Ratio NA

below the details of the $AAPL stock price details , during the WWDC , since 2003

WWDC Start Open WWDC End Close Change%
02-Jun-14 ?? 06-Jun-14 ?? ??
10-Jun-13 444.73 14-Jun-13 430.05 -3.30
11-Jun-12 587.72 15-Jun-12 574.13 -2.31
06-Jun-11 345.7 10-Jun-11 325.9 -5.73
07-Jun-10 258.29 11-Jun-10 253.51 -1.85
08-Jun-09 143.82 12-Jun-09 136.97 -4.76
09-Jun-08 184.79 13-Jun-08 172.37 -6.72
11-Jun-07 126 15-Jun-07 120.5 -4.37
07-Aug-06 67.72 11-Aug-06 63.65 -6.01
06-Jun-05 38.33 10-Jun-05 35.81 -6.57
28-Jun-04 34.18 02-Jul-04 31.08 -9.07
23-Jun-03 19.3 27-Jun-03 18.73 -2.95

and the colorful table of $AAPL during the WWDC since 2003

$AAPL during the WWDC ,since 2003

could this be 12 in row ??

you might want to consider subscribing to our daily quant rants email  !!

contact us for your quant trading programming needs in python and or R 

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

trade-idea : $AAPL breaks above upper bollinger band

$AAPL breaks above upper bollinger band

$AAPL close crosses above upper bollinger band stock chart

below the trading odds for the longs , when ever $AAPL close crosses above upper bollinger band , while on previous trading the close is below the upper bollinger band ,

20 day period average and 2 standard deviations are used for calculating the upper bollinger band

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss %
t+1 26 22 84.6 0.85 0.82 1.15 -0.80 1.43 -1.37
t+2 26 20 76.9 1.20 0.97 1.74 -0.64 2.75 -1.67
t+3 26 19 73.1 1.35 1.49 2.18 -0.89 2.45 -2.38
t+4 26 19 73.1 1.82 1.27 2.79 -0.80 3.47 -1.78
t+5 26 21 80.8 1.93 1.77 2.83 -1.82 1.56 -2.56
t+10 26 19 73.1 2.36 3.14 4.83 -4.35 1.11 -9.00
t+20 26 19 73.1 4.83 5.41 8.20 -4.32 1.90 -8.91
1st +’ve exit in 5 days 26 26 100.0 1.14 0.95 1.14 INF INF NA

below the prior instances of $AAPL close crosses above upper bollinger band , during the last 4 years ( since 24 Mar 2010, the standard look back period uses )

Date $AAPL t+1 t+2 t+3 t+4 t+5 t+10 t+20
25-Mar-14 544.99 ?? ?? ?? ?? ?? ?? ??
26-Nov-13 530.23 2.35 4.25 3.34 6.17 5.92 5.24 5.72
17-Oct-13 498.59 0.87 3.34 3.05 4.06 5.43 3.61 5.3
13-Aug-13 483.83 1.83 1.7 2.61 3.71 2.35 -0.2 -4.46
02-Aug-13 454.12 1.49 0.59 0.53 0.33 -1.1 9.32 6.03
29-Jul-13 439.64 1.24 1.06 1.99 3.29 4.84 5.06 13.07
14-Sep-12 667.28 1.23 1.54 1.56 1.07 1.27 -3.5 -8.91
20-Aug-12 642.06 -1.37 0.56 -0.38 -0.29 1.58 1.48 5.53
02-Jul-12 569.5 1.16 2.94 2.25 3.61 2.65 2.43 3.08
18-Jun-12 563.03 0.28 -0.01 -1.39 -0.63 -2.56 1.15 3.61
19-Mar-12 577.75 0.81 0.23 -0.29 -0.84 0.98 2.92 1.43
13-Mar-12 546.03 3.78 3.07 3.07 5.81 6.66 8.16 10.23
13-Feb-12 483.08 1.36 -0.98 -0.08 -0.1 2.44 6.53 13.03
09-Feb-12 474.01 0.05 1.91 3.3 0.91 1.83 5.93 10.54
25-Jan-12 429.31 -0.45 0.14 1.42 2.2 2.13 6.72 15.61
27-Dec-11 390.74 -0.96 -0.35 -0.38 1.16 1.7 3.94 9.37
19-Sep-11 395.64 0.44 0.12 -2.38 -1.78 -2.05 -9 2.03
20-Jul-11 371.87 0.1 1.65 3 4.27 1.47 1.47 -1.67
01-Jul-11 329.93 1.8 2.48 4.06 4.79 3.13 8.9 15.58
08-Feb-11 341.4 0.83 -0.18 0.47 1.12 1.32 -3.54 -0.77
03-Jan-11 316.77 0.52 1.34 1.26 1.99 3.91 3.36 4.69
15-Oct-10 302.51 1.04 -1.67 -1.34 -1.66 -2.31 -4.37 -2.13
16-Sep-10 265.83 -0.44 2.41 2.6 4.04 4.47 2.6 9.31
08-Sep-10 252.71 0.06 0.19 1.57 1.95 2.77 9.44 9.99
17-Jun-10 261.31 0.81 -0.62 0.73 -0.33 -1.06 -8.6 -8.08
21-Apr-10 249.15 2.8 4.48 3.97 1.09 0.92 -1.24 -4.2
05-Apr-10 229.23 0.44 0.88 0.61 1.38 1.59 3.59 11.68

t+1 , is the percent change for a one day holding period , and so on and so forth

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

S&P 500 Stocks bearish high odds seasonal trades for March 2014

S&P 500 Stocks bearish high odds seasonal trades for March 2014

Four_seasons

image courtesy : ashdenizen.blogspot.com/2008/05/there-are-various-blogs-discussing.html

here are three S&P 500 Stocks that meet the following criteria of high odds seasonal trades of loosing in the month of March from seasonal perspective.

With the aid of ” Paststat Seaonality Search ” 

  • Current S&P 500 Constituents and the stock is trading since 1990 ( or with a minimum trading history of 20 years)
  • The Average loss in March is at-least -1%
  • Percentage win rate for March is less than or equal to 40% ( in other words they lost by more than 60% of the times in February)
  • Pay-Off Ratio ( defined as Avg win% divided by Avg Loss% ) more than 1

below the three most bullish S&P 500 stocks which qualifies for the bearish high odds seasonal trades for March

Symbol Company Name # # Wins % Wins Avg Avg Win # Loss Avg Loss Pay Off Max Min
ADM Archer Daniels Midland Company 24 9 38 -1.08 4.2 15 -4.25 0.99 8.3 -12.6
ORCL Oracle Corporation 24 9 38 -2.92 10.16 15 -10.77 0.94 28.03 -33.33

High Odds Seasonal Trades definitions

  • # : Total number of instances
  • Avg: Average March Monthly Returns in percentage
  • Max : Best March Monthly returns in percentage
  • Min: Worst March Monthly returns in percentage
  • # Wins : Number of winning March Months ( i’e number of months when returns are positive)
  • Avg if Win : Average % change if the returns in March month are positive
  • # Loss: Number of loosing March Months ( i’e number of months when returns are negative)
  • Avg if Loss : Average % change if the returns in March month are negative
  • % Wins: Percentage times that March Month had given positive returns.
  • Avg Win/ Avg Loss: Ratio of Average Win % divided by Average Loss% , a.k.a Pay-off Ratio.

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

S&P 500 Stocks bullish high odds seasonal trades for March 2014

S&P 500 Stocks bullish high odds seasonal trades for March 2014

Four_seasons

image courtesy : ashdenizen.blogspot.com/2008/05/there-are-various-blogs-discussing.html

here are three S&P 500 Stocks that meet the following criteria of high odds seasonal trades of gaining in the month of March from seasonal perspective.

With the aid of ” Paststat Seaonality Search ” 

  • Current S&P 500 Constituents and the stock is trading since 1990 ( or with a minimum trading history of 20 years)
  • The Average gain in March is at-least 4%
  • Percentage win rate for March is at-least 80%

below the three most bullish S&P 500 stocks which qualifies for the bullish high odds seasonal trades for March High Odds

Symbol Company Name # # Wins % Wins Avg Avg Win # Loss Avg Loss Pay Off Max Min
BBBY Bed Bath & Beyond Inc. 21 20 86 8.3 10.22 3 -3.26 3.14 38.76 -6.92
MAS Masco Corporation 24 18 88 5.8 7.62 3 -6.91 1.1 35.42 -10.37
PX Praxair Inc. 21 22 86 5.52 7.28 3 -5.01 1.45 24.49 -7.52
QCOM QUALCOMM Incorporated 22 19 91 11.19 12.87 2 -5.62 2.29 70.32 -7.97
TIF Tiffany & Co. 24 18 83 7.52 10.18 4 -5.76 1.77 31.04 -12.3

High Odds Seasonal Trades definitions

  • # : Total number of instances
  • Avg: Average March Monthly Returns in percentage
  • Max : Best March Monthly returns in percentage
  • Min: Worst March Monthly returns in percentage
  • # Wins : Number of winning March Months ( i’e number of months when returns are positive)
  • Avg if Win : Average % change if the returns in March month are positive
  • # Loss: Number of loosing March Months ( i’e number of months when returns are negative)
  • Avg if Loss : Average % change if the returns in March month are negative
  • % Wins: Percentage times that March Month had given positive returns.
  • Avg Win/ Avg Loss: Ratio of Average Win % divided by Average Loss% , a.k.a Pay-off Ratio.

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

$PCLN Earnings day cheat sheet since Jun 2009

$PCLN Earnings day cheat sheet since Jun 2009

 

$PCLN ER day cheat sheet since Jun 2009

 

Gap ; is the overnight movement from the previous close to the opening on the earnings day

CFO : is the Change From Open

T : is the over all change in percent on the Earnings day

up 76% times on the ER day morning , with a max loss of -15.4% and median gain of 6.2%

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

 

January 2014 Seasonal Trades Walk forward performance

January 2014 Seasonal Trades Walk forward performance

Four_seasons

Here the performance figures in 100/30 Long /Short portfolio methodology for Jaunary 2014 Seasonal Trades

Bearish Seasonal Trades for January Performance 

ps: the performance is adjusted for dividend pay-outs 

Symbol Company Name Dec Jan P/L%
BF-B Brown-Forman Corporation 75.57 77.00 -1.89
CPB Campbell Soup Co. 42.97 41.21 4.10
KO The Coca-Cola Company 41.31 37.82 8.45
PGR Progressive Corp. 25.63 23.24 9.33
    Average 4.99

Bullish Seasonal Trades  for January Performance 

Symbol Company Name Dec Jan P/L%
HRS Harris Corp. 69.81 69.34 -0.67
LLTC Linear Technology Corp. 45.55 44.54 -2.22
ROK Rockwell Automation Inc. 118.16 114.84 -2.81
Average -1.90

100/30 Long /Short Portfolio of S&P 500 Stocks Seaonal Trades for January – 2014 performance

(-1.9*100+(4.99)*30)/130 = -0.31% against -3.52% for $SPY

3.22% out-performance !

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

S&P 500 Stocks bullish high odds seasonal trades for February 2014

S&P 500 Stocks bullish high odds seasonal trades for February 2014

Four_seasons

image courtesy : ashdenizen.blogspot.com/2008/05/there-are-various-blogs-discussing.html

here are three S&P 500 Stocks that meet the following criteria of high odds seasonal trades of gaining in the month of February from seasonal perspective.

With the aid of ” Paststat Seaonality Search ” 

  • Current S&P 500 Constituents and the stock is trading since 1990 ( or with a minimum trading history of 20 years)
  • The Average gain in February is at-least 4%
  • Percentage win rate for February is at-least 75%

below the three most bullish S&P 500 stocks which qualifies for the bullish high odds seasonal trades for Februrary High Odds

Symbol Company Name # # Wins % Wins Avg Avg Win # Loss Avg Loss Pay Off Max Min
AVP Avon Products Inc. 24 20 83 4.74 7.39 4 -8.49 0.87 26.58 -13.82
HP Helmerich & Payne Inc. 24 18 75 4.75 8.61 6 -6.85 1.26 19.61 -15.98
HSY Hershey Co. 24 22 92 4.32 5.5 2 -8.64 0.64 12.83 -8.84
IR Ingersoll-Rand Plc 24 19 79 4.05 7.05 5 -7.34 0.96 22.11 -17.9
PBCT People’s United Financial Inc. 23 18 78 7.48 10.33 5 -2.81 3.68 73.68 -6.67

Seasonal Trades definitions

  • # : Total number of instances
  • Avg: Average February Monthly Returns in percentage
  • Max : Best February Monthly returns in percentage
  • Min: Worst February Monthly returns in percentage
  • # Wins : Number of winning February Months ( i’e number of months when returns are positive)
  • Avg if Win : Average % change if the returns in February month are positive
  • # Loss: Number of loosing February Months ( i’e number of months when returns are negative)
  • Avg if Loss : Average % change if the returns in February month are negative
  • % Wins: Percentage times that February Month had given positive returns.
  • Avg Win/ Avg Loss: Ratio of Average Win % divided by Average Loss% , a.k.a Pay-off Ratio.

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?

S&P 500 Stocks bearish high odds seasonal trades for February 2014

S&P 500 Stocks bearish high odds seasonal trades for February 2014

Four_seasons

image courtesy : ashdenizen.blogspot.com/2008/05/there-are-various-blogs-discussing.html

here are three S&P 500 Stocks that meet the following criteria of high odds seasonal trades of loosing in the month of Februrary from seasonal perspective.

With the aid of ” Paststat Seaonality Search ” 

  • Current S&P 500 Constituents and the stock is trading since 1990 ( or with a minimum trading history of 20 years)
  • The Average loss in February is at-least -2%
  • Percentage win rate for February is less than or equal to 33% ( in other words they lost 67% of the times in February)
  • Pay-Off Ratio ( defined as Avg win% divided by Avg Loss% ) more than 1

below the three most bullish S&P 500 stocks which qualifies for the bearish high odds seasonal trades for February 

Symbol Company Name # # Wins % Wins Avg Avg Win # Loss Avg Loss Pay Off Max Min
BBBY Bed Bath & Beyond Inc. 21 6 29 -2.81 5.77 15 -6.24 0.92 12.5 -11.99
MDT Medtronic, Inc. 24 8 33 -2.16 5.01 16 -5.75 0.87 17.05 -13.33

High Odds Seasonal Trades definitions

  • # : Total number of instances
  • Avg: Average February Monthly Returns in percentage
  • Max : Best February Monthly returns in percentage
  • Min: Worst February Monthly returns in percentage
  • # Wins : Number of winning February Months ( i’e number of months when returns are positive)
  • Avg if Win : Average % change if the returns in February month are positive
  • # Loss: Number of loosing February Months ( i’e number of months when returns are negative)
  • Avg if Loss : Average % change if the returns in February month are negative
  • % Wins: Percentage times that February Month had given positive returns.
  • Avg Win/ Avg Loss: Ratio of Average Win % divided by Average Loss% , a.k.a Pay-off Ratio.

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

you might want to consider subscribing to our daily quant rants email  !!

check out Quant-Ideas  to aid the short term trader to find high probability winning trades

have you bought the Anatomy of $SPY on First Trading Day of the Month  , written the co-founder of this site, on Amazon yet ?