Sunday 3 June 2012

Week of 2012 JN 01

SPY fell by 3.2% this week, while my account fell 0.6% to its lowest value ever.  My loss-floor has fallen to -10.3%, but is expected to rise to perhaps -9.8% on Monday morning.

Euro news: The government of Spain has announced that they can continue as a going concern until October, but it has become increasingly apparent that Spain is lying its collective head off, so presumably their actual financial condition is dire.

US news: Friday’s non-farm payroll report was awful, so President Obama went on TV to reassure the public.  As usual, the market fell after the Obama speech.  The S&P 500 pierced its 200-day moving average, so I expect at least a one-day bounce next Monday, which hopefully will cause my robot to double-down on its bearish bet.

The last five months have been a nightmare for my trading system.  The market goes up, I lose money; the market goes down, I lose more money.  Some stock trader I am!  For reassurance, I look to the back-tests for last August.  If I had been using my latest TZA model last year, there would have been four losses in a row from April through July, totalling -2%, before the +19% win in August.  For TNA the results were more mixed: if somehow I had failed to get the +5.7% win in July, then results for April through July would have been -0.6%.  So there would have, could have, should have been several months in a row of “I just can’t win!”, followed by a big win.

On Monday, US markets were closed for Memorial Day.  The “post Memorial Day bounce” lasted all of one day.

Friday’s allocations:
Daily % gain
Max lossFinal
Sym  Buy Fri Mon Tue Wed Thu Fri Beg   End
SRTY 1  MA23 -1.0 14  -1.5 14  -0.8 -0.8%
TNA  MA29 -0.0 15  -0.9 30  -1.1 29  -3.5 29  -1.6 -1.6 -1.6%
SRTY 2  MA30 +0.0 15  +0.1 16  +1.4 15  -0.9 -1.0 +0.2%
TZA  MA30 -0.5 15  +0.7 16  -1.5 -1.4
SPY +5.3 +6.5 +5.0 +4.8 +2.1
me -7.5 -7.5 -8.4 -9.3 -8.1
floor -7.5 -9.2 -10.0 -10.4 -10.3

Stock-trading robot

Buy dateBuy priceSell dateSell priceAcct Profit
TNA MA 29 11:00 $50.48 $50.45 MA 31 10:00 MA 31 09:49 $46.42 $46.40 -1.6%
MA 30 11:00 $47.79 $47.81
SRTY 2 MA 30 13:00 $53.98 MA 31 15:00 $54.84 $54.87 +0.2%
TZA MA 31 11:00 $22.56 $22.60 (Not yet)

TNA: Bought on Tuesday near (what turned out to be) the high of the week.  Price went down and back up again, triggering a “buy-more” at 4pm, but the tranche-purchase was postponed until Wednesday 11am (for a much better price).  At Wednesday’s close, PPO was just above giving a “sell” signal.  From Thursday’s open the market just sank until it hit my stop.

SRTY 2 : Sold near Thursday’s close, just before its price went through the roof on Friday.  What can ya do?  The SRTY model has a hair-trigger “sell” signal and it triggered.

TZA: Bought Thursday.  Its price went down at Thursday’s close, then up at Friday’s open, but a “buy more” signal was not triggered because STDDEV was too high.  This will turn out to have been a good move if there is a reaction rally on Monday and so I end getting a better price on the second tranche.  Even if I had bought the tranche at 11am on Friday, my account would still have lost 0.3% this week.

Overall, the robot performed well this week.  I got the expected amounts of profit and loss, the buy-times and sell-times were correct (the model cannot predict stop-out times any more accurately), and the actual prices received were as close to the model prices as could reasonably be expected.  The main thing that went wrong was that Thursday’s max-loss recalculation for SRTY caused the stop price to go *down*, but stop prices should only ever go up.  I have adjusted the robot to pull latest quotes for both IWM and TZA during the same invocation of Opera, so they will differ by milliseconds instead of seconds.  Hopefully that will tighten up the stops a little.

Surfing the oscillations

Here are the last two weeks, showing how mean the stock market has been to me.  Three times the market went in one direction just far enough to convince me to hop on, then immediately reversed to make me lose money.  This sort of thing happens periodically and is a side-effect of using “average” model parameters that have typically worked well over the last four years (but those parameters have worked very badly for certain multi-month periods).

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