Tom, I have used the information on the ERX Chart and took 36 data points and plugged them in my Cash Limiter Vortex AIM Excel Spread.
I have taken the position that I knew nothing of this stock and its future behaviour. I used a CER of 50/50 and $ 20000 start capital.
Here are the parameters I set arbitrarily according to my standard approach for unknown stocks:
Buy/Sell Holding zone = 10%
Trading Cost = 1 %/Trade
Yield on Cash = 2% Compounded every trade.
Cash Limiting 50%. . . this means that at every buy 50% of the Reserve is used (the standard aggression I use is rather high, so the Cash Burn was limited to preserve cash a bit.
Buy Aggression Factor = 0,75
Sell Aggression Factor = 0,5
[This means that Sells do not produce enough cash to build up the Reserve for aggressive Buys. As an afterthought on this rather horizontal average behaviour I might have better used the same aggression factors for selling and buying but I assumed I knew nothing about the future so I set the agression as I usually do]
The Results
1-11-2008
PV Start = $ 20000
10-11-2010
PV End = $ 34169
Net Profit = $ 14169 . . . . (expenses already subtracted)
Trading Cost = $2095
Interest Earned = $ 546
Run time = 738 days
Time Averaged Investment= $ 6935
ROTAI Yield = 101 %/yr
The average investment has been only about 35% of the $ 20000
start capital and the cash has earned its own interest, so the cash is considered as a seprate safe investment so it is not included in the Capital at Risk. This makes the yield of the invested capital rather high. . .indicating a rather effective Portfolio Result
This without any attempt at "fudging" to set the parameters at optimum values on the basis of future knowlegde. A lovely equity to AIM!
*********************************************
From the bove position I did a little bit of optimization by making small alterations to the aggression parameters, and against my expactation the local optimum is very close to the actual results:
The optimum Hold Zones = 10 % as assumed at the start.
The Buy Aggression Factor optimum is 0,77 instead of 0,75
The Sell Aggression Factor optimum is 0,50 as assumed.
The optimum ROTAI = 116%
**********************************
Now I set the system back to initial results(With the ROTAI=101 %)
and the Cash Burn NOT restricted to 50% of Cash Residue. This means that at the first price-dip from the start the $ 10000 Reserve is almost fully used up. . .due to the high Buy Aggression factor:
Results with High Cash Burn Rate(See note 1):
R0TAI Yield reduces to 57 %/yr.
From this it is clear that I might as well use a lower Buy Aggression and use no restriction on the cash Burn Rate.
I will try that.
Now the option to use even more restriction on the Cash Burn Rate. Logic tells me that for this case more cash would available for the dip on March 1st, 2009 at a price of 15.
Cash Burn at 25%
ROTAI = 98 %
Cash Burn at 30%
ROTAI = 102
Cash burn at 38%
ROTAI = 105,14 as maximum
Obviously with back testing like this one might likely be able to get a much higher yield than one will get with assumed best values for the parameters. The use of back testing has limited value as the consensus is that stock prices hardly ever repeat their historical pattern. The best I can think of for myself is to use a historical pattern for a reasonably short period back, do the back testing, then optimise the parameters. Then after a number of trades have been executed redo the back testing with the new prices and optimise again. In this way one would get approximately the right settings as long as the prices are not vary wildly. If they do then do not execute a weird trade advice but analyse first what is happening . . .”Is the weird price change explainable?”
Note 1
Having the Cash Burn restricted to 50% this means that I could reduce the Buy Aggression to a value so that only 50% of the Reserve is used up in the forst trade, without the Cash Burn being restricted.
I will try that but this does not mean that the Yield would then be the same because the trade point price differentials are erratically distributed. I will report the results.
AI
