when $SPY posts a top range close ahead of FOMC ??

when $SPY posts a top range close ahead of FOMC ??

Fed_Cartoon

 

below a ” bullish Fed day pattern “, and here are the trading strategy rules ,

1) $SPY current day close’s is in the top 10% of day’s range ( i.e high[0]-close[0]/(high[0]-low[0]) < 0.1) , ps: it doesn’t necessarly mean a $SPY closed up for the day , as there are 2 negative days in the trading strategy sample

2) and the next trading day is Fed Day

3)  below the $SPY returns for the next 1/2/3/4/5 /10/20 trading days , since Y2K

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss % PF OAPF STDEV T-Test
t+1 23 15 65.2 0.37 0.39 0.93 -0.66 1.40 -1.70 2.45 2.09 0.95 1.89
t+2 23 19 82.6 0.84 0.65 1.14 -0.59 1.95 -0.78 8.00 7.00 1.06 3.82
t+3 23 17 73.9 0.71 0.90 1.39 -1.23 1.13 -2.17 3.25 2.83 1.46 2.32
t+4 23 15 65.2 1.14 1.02 2.11 -0.69 3.09 -2.86 4.92 4.26 1.86 2.94
t+5 23 16 69.6 1.10 1.22 2.00 -0.96 2.08 -3.59 4.10 3.36 2.12 2.48
t+10 23 15 65.2 0.67 1.31 2.16 -2.14 1.01 -4.26 2.31 1.96 2.42 1.32
t+20 23 16 69.6 0.67 1.98 3.30 -5.35 0.62 -14.21 1.60 1.36 5.19 0.62
1st +’ve exit in 5 days 23 22 95.7 0.79 0.59 0.85 -0.51 1.66 -0.51 21.60 19.08 0.76 4.97

22/23 times  $SPY closed at higher than the current close at some point of time in the next five trading days .. with an average gain of 79 basis points at the 1st positive close within in the next five trading days, when $SPY closed at the top 10% of the day’s range , before the Fed Day

PF: Profit Factor, and OAPF is the outlier adjusted profit factor ( which is profit factor recalculated after removing the maximum winner )

below the prior instances of $SPY closing at the top 10% of the day’s range before the Fed day and the next 1/2/3/4/5 trading days returns

Date $SPY t+1% t+2% t+3% t+4% t+5% 1st +’ve exit (%) in 5 days
28-Apr-15 211.44 ?? ?? ?? ?? ?? ??
28-Oct-14 196.44 -0.15 0.49 1.64 1.70 1.34 0.49
29-Oct-13 172.07 -0.50 -0.78 -0.54 -0.19 -0.51 -0.51
17-Sep-13 165.34 1.16 0.99 0.28 -0.18 -0.42 1.16
30-Apr-13 153.52 -0.88 0.04 1.06 1.32 1.82 0.04
24-Jan-12 123.10 0.84 0.32 0.27 -0.07 -0.11 0.84
25-Jan-11 118.47 0.39 0.63 -1.12 -0.38 1.22 0.39
15-Mar-10 103.88 0.80 1.40 1.35 0.83 1.37 0.80
17-Mar-09 68.73 2.24 0.97 -1.18 5.92 3.84 2.24
28-Oct-08 81.76 -0.72 2.72 3.28 3.58 7.09 2.72
27-Jun-07 127.83 -0.02 0.02 0.92 1.28 1.18 0.02
20-Mar-07 119.30 1.64 1.57 1.72 1.58 1.34 1.64
30-Jan-07 120.36 0.67 1.27 1.41 1.45 1.47 0.67
24-Oct-06 115.58 0.34 0.65 0.02 -0.05 -0.07 0.34
28-Jun-06 104.11 2.03 2.03 2.45 1.86 2.16 2.03
02-May-05 95.04 0.17 0.94 0.90 0.59 1.22 0.17
13-Dec-04 97.43 0.35 0.43 0.37 -0.30 -0.28 0.35
08-Dec-03 85.44 -0.77 -0.78 0.33 0.53 0.02 0.33
17-Mar-03 68.14 0.59 1.35 1.57 3.74 0.29 0.59
01-Oct-01 80.32 1.26 2.95 3.04 2.84 2.17 1.26
20-Aug-01 90.42 -1.70 -0.69 -1.04 1.02 0.41 1.02
14-May-01 95.96 0.46 2.83 2.99 3.46 4.98 0.46
30-Jan-01 105.16 -0.56 0.10 -2.17 -1.45 -1.74 0.10
15-May-00 110.00 0.96 -0.09 -1.31 -2.86 -3.59 0.96

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

Leave a Reply