No problem.
Take your time.
No problem.
Take your time.
In my model, a bought Oversold trade is interrupted (returned to cash) when the signal falls back to oversold again.
This is a protection mechanism that allows not to be dragged into a continuously loosing position.
If, on the next day, the signal reverses back above the OS level, then the model moves again into a buy mode at the end of the next day.
In short: you need to consider these as two different trades.
Indeed. It is easier for me to use the EOD price, as I know this price by the time the model is published, before market opens. Also, I consider that the RT system allows - or will allow - traders to act before the close if they wish to do so.
This is my mistake: I hurried myself somehow and probably typed the wrong title in front of the trade return.
I cannot check this out again, as I discarded this temporary calculation.
So, the best is to disregard my small table by type of trades of XLE. My point was simply to show that there was a discrepancy in your calculations.
Pascal
Thanks for publishing this table: I did not take the time to do it myself, as I have been busy with the RT system.
This table makes sense.
If you want to trade only some signals of each XLX, I believe that it is important to dig a few more data:
1. On the signal correlation
XLX are all part of the S&P500 group, which means that they are probably highly correlated. How correlated are for example the Bought Oversold signals of each component? Is it interesting to trade them all, to concentrate on the first three signals for example or to trade the most volatile of the these XLX.
2. On the XLX and 20DMF Correlation
Each XLX model is based on the weighted MF of each stock that is included into the XLX component. The model is somewhat different from the 20DMF, which is mainly a sector based model.
It could be interesting to see if for each component, the Bought OS or Shorted OB signals are issued concurrently, earlier or later than the 20DMF signal. Is it then better to wait for a 20DMF confirmation signal or to already invest some money in the XLX, before having a market confirmation?
3. On the XLX and your combo Correlation
You can do the same work with your own combo strategy.
A comment on GDX
On a final note, we can see that GDX EOD is performing poorly for Buy/Short signals. This is due to the whipsawing character of the ETF on an EOD base. The RT signal works much better, especially combined to the LT/ST edge calculation for each trade.
Thank you for your work.
Pascal
Pascal,
Thanks for your reply.
Meanwhile I have continued with my work on the XLX models.
I have added extra filters following a detailed analysis of all the trades. These filters will look at the state of the 20DMF before each trade is made. If the trade is statistically not beneficially, I do not make the trade.
In the same way I have searched for correlation effects with bear/bull situations. If the 50MA is above the 20MA for an instrument, I call this instrument in "bull" situation. Under certain bull/bear situations certain trades are also statistically better or worse.
It is amazing how efficient the trades can be improved by adding these filters. The number of trades are reduced (less fees and taxes) and the draw-down per model improves also.
After applying stop-loss strategy (as described in my last paper), the results are even better for most of the models. It is notable that not all models improve at first sight with applying stop-loss. Because I need to know the average risk of each trade before making the trade, I need a stop-loss strategy for my risk based position sizing technique.
Beside the Combo-MF model, I see that XLB, XLF, XLI, XLK and XLY are looking promising.
I agree with you concerning the GDX model. Trading the EOD signals is not interesting. For this model I will wait until automatic RT signals are available.
Now I will continue my back tests in search for the optimum position sizing parameters for these selected models (Combo-MF + XLB + XLF + XLI + XLK + XLY). I am going to test if it makes sense to trade three, four, five or six models simultaneously. Maybe only trading the strongest three models at a certain time will give better performance. This I will learn from the test I will perform now.
Below are the details for the different models before and after applying the filters. The final table are the results after applying my stop-loss strategy. In these tables the trades are made at the open after a signal change using single ETFs. No transaction costs (fees and taxes) are calculated for these results.
My final strategy will calculate the transaction costs and will use, when applicable, leverage and margin. More details will follow.
PdP
PDP,
Good work!
Are you using all the XLX trades or only the strongest (BOS or SOB?)
Pascal
Last edited by Pascal; 07-23-2012 at 03:13 AM.
As my new back tests are showing now, I will be using 5 of the 9 sub-components of the S&P sectors: XLB, XLF, XLI, XLK & XLY besides my Combo-MF.
Finding valid ETFs for these sub-components is easy except for XLY. XLY is the Consumer Discretionary Select Sector SPDR Fund. Stock-Encyclopedia.com gives UGE and UCC as double ETFs for respectively Consumer Goods and Consumer Services. I am a bit puzzled which one to choose: UGE or UCC
Can anyone advice?
PdP
pdp,
pascal, paul duncan, or someone else could probably advise better, but it looks to me like the composition of UCC http://finance.yahoo.com/q/hl?s=UCC+Holdings is more similar to XLY http://finance.yahoo.com/q/hl?s=XLY+Holdings than UGE http://finance.yahoo.com/q/hl?s=UGE+Holdings
lisa
Lisa,
Thanks for the reply. Indeed, UCC looks better in terms of composition. I will use UCC for my back-tests.
I hope to report my progress soon.
PdP
UCC is not so good to trade. Certain days, there is no volume at all. I think that the quotes for UCC that I get from Reuters (I use MetaStock EOD) are not reliable for UCC.
For the XLY model, I will use the single ETF XLY for my back tests.