Few statistics around $SPY bear hook pattern formation

Few statistics around $SPY bear hook pattern formation

$SPY Bear Hook Price Pattern chart

Definition of ‘Bear Hook’
A Bear Hook occurs when you have an narrower range than that of previous day’s range ( range defined as high – low) && with the current open less than the previous bar’s low && the current close greater than the previous bar’s close.

This pattern is from Toby Crabel’s cult classic Day Trading With Short Term Price Patterns and Opening Range Breakout 

with $SPY forming a Bear Hook as on 12 Mar 2014 close , below trading odds with various Bear Hook Combinations , since 1994 on $SPY

1) $SPY forms a Bear Hook pattern 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss %
t+1 54 29 53.7 0.07 0.09 0.98 -0.99 0.99 -4.50
t+2 54 23 42.6 -0.21 -0.21 1.15 -1.21 0.94 -4.49
t+3 54 28 51.9 -0.08 0.07 1.23 -1.50 0.82 -4.31
t+4 54 28 51.9 -0.11 0.12 1.69 -2.05 0.82 -7.32
t+5 54 29 53.7 -0.27 0.46 1.64 -2.49 0.66 -7.28

don’t worry all the negativity stems from the $SPY being below 200-DMA

2) $SPY forms a Bear Hook pattern , and $SPY close is above 200-DMA 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss %
t+1 35 21 60.0 0.13 0.09 0.70 -0.72 0.97 -2.87
t+2 35 19 54.3 -0.05 0.20 0.89 -1.16 0.77 -3.61
t+3 35 21 60.0 0.13 0.31 1.06 -1.26 0.85 -3.71
t+4 35 20 57.1 0.43 0.47 1.65 -1.20 1.37 -3.00
t+5 35 23 65.7 0.50 0.67 1.64 -1.69 0.97 -3.25
1st +’ve exit in 5 days 35 30 85.7 0.35 0.51 0.67 -1.58 0.42 -2.64

3) $SPY forms a Bear Hook pattern , and current trading day is hump day ( i,e Wednesday) 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss %
t+1 18 13 72.2 0.74 0.54 1.28 -0.67 1.92 -1.01
t+2 18 12 66.7 0.60 0.32 1.23 -0.66 1.85 -1.69
t+3 18 11 61.1 0.29 0.18 1.16 -1.08 1.07 -2.59
t+4 18 8 44.4 -0.12 -0.15 2.00 -1.82 1.10 -3.55
t+5 18 7 38.9 -0.22 -0.43 2.08 -1.68 1.24 -3.25
1st +’ve exit in 5 days 18 16 88.9 0.87 0.82 1.17 -1.54 0.76 -2.86

16/18 times ( or 89% ) $SPY closed at higher close than the current close at some point of time than the current close over the next five trading days with an average gains of 0.87% .

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 ?

few First Trading Day of the Month $SPY trading setups triggered on 31-Oct-2013

$SPY on First Trading Day of the Month

image courtesy : http://www.yesplusme.com/post.php?id=275

collection from the {free to download }Anatomy of $SPY on First Trading Day of the Month : e-book 

1) $SPY close is above 200-DMA during the previous trading day, backtest summary since 2000.

  • Winners : 78
  • Losers : 33
  • % Winners : 70%
  • Average Change % : 0.39
  • Median Change % : 0.50
  • Maximum Gain % : 2.57
  • Maximum Loss % : -2.51
  • Average Gain %if Winner : 0.88
  • Average Loss % if Loser : -0.75
  • Average Gain % / Average Loss % : 1.18
  • Average Absolute Change% : 0.84
  • Profit Factor : 2.66

2) $SPY close is above 50-DMA , during the previous trading day, backtest summary since 2000.

  • Winners : 67
  • Losers : 32
  • % Winners : 68%
  • Average Change % : 0.40
  • Median Change % : 0.43
  • Maximum Gain % : 3.01
  • Maximum Loss % : -2.79
  • Average Gain %if Winner : 0.96
  • Average Loss % if Loser : -0.78
  • Average Gain % / Average Loss % : 1.24
  • Average Absolute Change% : 0.90
  • Profit Factor : 2.43

3) $SPY is up during the previous month , first trading day backtest summary since 2000.

  • Winners : 65
  • Losers : 30
  • % Winners : 68%
  • Average Change % : 0.38
  • Median Change % : 0.43
  • Maximum Gain % : 3.01
  • Maximum Loss % : -3.81
  • Average Gain %if Winner : 0.96
  • Average Loss % if Loser : -0.86
  • Average Gain % / Average Loss % : 1.11
  • Average Absolute Change% : 0.93
  • Profit Factor : 2.35

4) first trading day of the month is Friday backtest summary since 2000.

  • Winners : 16
  • Losers : 8
  • % Winners : 67%
  • Average Change % : 0.49
  • Median Change % : 0.42
  • Maximum Gain % : 3.01
  • Maximum Loss % : -2.51
  • Average Gain %if Winner : 1.06
  • Average Loss % if Loser : -0.65
  • Average Gain % / Average Loss % : 1.64
  • Average Absolute Change% : 0.94
  • Profit Factor : 2.97

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

check out Quant-Ideas ( starting from $ 49.95 per month) to aid the speculators to find high probability winning trades.