yellow jacket trading strategy

Wow, this is way more sophisticated than my simple excel spreadsheet calculation. :thumbsup::thumbsup::thumbsup:

I've heard of the proverb, "Good things come to those who wait." So I tried the same strategy delayed one week:

If (today is the fourth Friday of the month) or (today is the day before the fourth Friday of the month and the market is closed tomorrow),
Then enter long at the close today. Exit at the close the following Friday or the next trading day if the market is closed the following Friday.

The results were much better. For July 22, 1983 through July 5, 2019, the same statistics on the simulated trade results in S&P 500 points without accounting for trading costs were:
numValues 432
sum 1688.290964
prod -Inf
min -114.04004
max 127.609863
mean 3.90808093518518
sampleStdDev 25.3388719411513
median 2.8250275
medianAbsDev 9.52000450000001
geomean NaN
skewness 0.0814835093665896
excessKurtosis 4.3138012900674
>Thresh_0_Pct 62.73


The attached enter_long_week_after_optexp_one_week.xls has individual trade results as before except I added a column for log(exitPrice / entryPrice). This makes it easier to calculate the compounded return of 515 percent for an annual growth rate of 5.18 percent. This doesn't look that bad considering the strategy had market exposure of 2,084 out of 9,063 trading days (in market 23 percent of the time).
 

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I've heard of the proverb, "Good things come to those who wait." So I tried the same strategy delayed one week:

If (today is the fourth Friday of the month) or (today is the day before the fourth Friday of the month and the market is closed tomorrow),
Then enter long at the close today. Exit at the close the following Friday or the next trading day if the market is closed the following Friday.

The results were much better. For July 22, 1983 through July 5, 2019, the same statistics on the simulated trade results in S&P 500 points without accounting for trading costs were:
numValues 432
sum 1688.290964
prod -Inf
min -114.04004
max 127.609863
mean 3.90808093518518
sampleStdDev 25.3388719411513
median 2.8250275
medianAbsDev 9.52000450000001
geomean NaN
skewness 0.0814835093665896
excessKurtosis 4.3138012900674
>Thresh_0_Pct 62.73


The attached enter_long_week_after_optexp_one_week.xls has individual trade results as before except I added a column for log(exitPrice / entryPrice). This makes it easier to calculate the compounded return of 515 percent for an annual growth rate of 5.18 percent. This doesn't look that bad considering the strategy had market exposure of 2,084 out of 9,063 trading days (in market 23 percent of the time).
:D:D:D See my post: 3 > 2 > 1

Been there done that.

I tested the following, from 1993 to 2019, ignoring commissions, bid/ask:

1. Sell at open today, buy at close yesterday

2. Sell at close today, buy at close yesterday

3. Sell at close today, buy at close a week ago

4. Sell at close today, buy at close a month ago

5. Sell at close today, buy at close a year ago

6. Buy in 1993, sell in 2019

6 > 5 > 4 > 3 > 2 > 1
 
:D:D:D See my post: 3 > 2 > 1

I saw that post, but I was reading left-to-right and thought one would need help from one of
upload_2019-8-1_20-48-11.png

to trade them:D.
 
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