Simple swing trading ETF strategy: buy eod 2d highs

My favorite swing trading strategy is to simply buy / scale in to charts that end at a 2day high.

eg I bought 1000 uvxy eod fri, I'll buy more eod today if it closes >8.

Also trading BITI KOLD SQQQ
 
My favorite swing trading strategy is to simply buy / scale in to charts that end at a 2day high.

eg I bought 1000 uvxy eod fri, I'll buy more eod today if it closes >8.

Also trading BITI KOLD SQQQ
Why do not you backtest it? Or if you want, I can quickly code and backtest for you. Naked eye is cheating all the time. Too many strategies look good until they fail miserably at coded backtest
 
Why do not you backtest it? Or if you want, I can quickly code and backtest for you. Naked eye is cheating all the time. Too many strategies look good until they fail miserably at coded backtest

Calhoun has no track record data on his trades, no entry price, actual execution or final P/L. And be careful, or Calhoun will go ballistic on you and send his dolls to attack.
 
Why do not you backtest it? Or if you want, I can quickly code and backtest for you. Naked eye is cheating all the time. Too many strategies look good until they fail miserably at coded backtest

Great idea - test using volatile tickers eg SOXS SQQQ SOXL TQQQ UVXY TZA NIO DKNG SPCE CCL DAL AMD OXY MRO HAL TSLA

I don't have software to backtest, can someone run it?

Buy if current price ends within .2 of 2day high , sell if price gets .2 under pd low
 
Great idea - test using volatile tickers eg SOXS SQQQ SOXL TQQQ UVXY TZA NIO DKNG SPCE CCL DAL AMD OXY MRO HAL TSLA

I don't have software to backtest, can someone run it?

Buy if current price ends within .2 of 2day high , sell if price gets .2 under pd low
@KCalhoun

I coded it for you but need to double check...

"within .2" = within 0.2% ??
PD = prior day ??

Right now I have:
(1) Enter on close if close > 0.998 * max( today's high, yesterday's high )
(2) Exit on close if close < 0.998 * yesterday's low

Assuming I have it right, the results are a real mixed bag...

--
RealTest Code:

Import:
DataSource: Yahoo
IncludeList: OXY
SaveAs: OXY_Yahoo.rtd
StartDate: 1993-01-01
EndDate: Latest

Strategy: KCalhoun
EntrySetup: Close > 0.998 * max(High, High[1])
EntryTime: ThisClose
ExitRule: Close < 0.998 * Low[1]
ExitTime: ThisClose
 
Last edited:
@KCalhoun

I coded it for you but need to double check...

"within .2" = within 0.2% ??
PD = prior day ??

Right now I have:
(1) Enter on close if close > 0.998 * max( today's high, yesterday's high )
(2) Exit on close if close < 0.998 * yesterday's low

Assuming I have it right, the results are a real mixed bag...

--
RealTest Code:

Import:
DataSource: Yahoo
IncludeList: OXY
SaveAs: OXY_Yahoo.rtd
StartDate: 1993-01-01
EndDate: Latest

Strategy: KCalhoun
EntrySetup: Close > 0.998 * max(High, High[1])
EntryTime: ThisClose
ExitRule: Close < 0.998 * Low[1]
ExitTime: ThisClose

mixed result is expected
 
Since I didn't receive any corrections, I'll assume I interpreted the strategy correctly. Here are the results (2012-2022):

Ticker | Max Drawdown (%) | Sharpe
SOXS | -93 | -0.48
SQQQ | -87 | -0.63
SOXL | -69 | -0.09
TQQQ | -51 | +0.39
UVXY | -89 | -0.78
TZA | -85 | -0.42
NIO | -30 | +0.65
DKNG | -51 | -0.32
SPCE | -34 | +0.02
CCL | -36 | +0.01
DAL | -28 | +0.33
AMD | -33 | +0.51
OXY | -66 | -0.19
MRO | -42 | +0.07
HAL | -29 | +0.19
TSLA | -61 | +0.10

The mean of these sharpe values is -0.04; the standard deviation is 0.41. In other words, statistically speaking the resulting PLs are just random noise. There's nothing to the strategy, at least as originally stated. Sorry @KCalhoun.

I'll post the equity curve for one or two of the equities if someone asks for it.
 
Since I didn't receive any corrections, I'll assume I interpreted the strategy correctly. Here are the results (2012-2022):

Ticker | Max Drawdown (%) | Sharpe
SOXS | -93 | -0.48
SQQQ | -87 | -0.63
SOXL | -69 | -0.09
PLs are just random noise. There's nothing to the strategy, at least as originally stated. Sorry @KCalhoun.

Nice job;
 
Since I didn't receive any corrections, I'll assume I interpreted the strategy correctly. Here are the results (2012-2022):

Ticker | Max Drawdown (%) | Sharpe
SOXS | -93 | -0.48
SQQQ | -87 | -0.63
SOXL | -69 | -0.09
TQQQ | -51 | +0.39
UVXY | -89 | -0.78
TZA | -85 | -0.42
NIO | -30 | +0.65
DKNG | -51 | -0.32
SPCE | -34 | +0.02
CCL | -36 | +0.01
DAL | -28 | +0.33
AMD | -33 | +0.51
OXY | -66 | -0.19
MRO | -42 | +0.07
HAL | -29 | +0.19
TSLA | -61 | +0.10

The mean of these sharpe values is -0.04; the standard deviation is 0.41. In other words, statistically speaking the resulting PLs are just random noise. There's nothing to the strategy, at least as originally stated. Sorry @KCalhoun.

I'll post the equity curve for one or two of the equities if someone asks for it.

Thx for running the test, good to know
 
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