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Thomas,
By combining the usage of PeakBars/TroughBars and Equity, you can Plot the effects (including compounding).
// Perfect Profit, using Zig SetTradeDelays(0, 0, 0, 0);
amount = Param("ZigZag-Amount", 1, 0.1, 1.5, 0.1 );
Buy = Cover = TroughBars(Close, amount) == 0; BuyPrice = CoverPrice = Close;
Sell = Short = PeakBars(Close, amount) == 0; SellPrice = ShortPrice = Close;
Plot(Close, "Close", colorLightGrey, styleBar); Plot(Zig( Close, amount ), "Zig", colorDarkGrey, styleThick); Plot(Equity(), "Perfect Profit", colorBlue, styleLeftAxisScale);
// Strategy Profit fast = MA(Close, 5); slow = MA(Close, 25);
Buy = Cover = Cross(fast, slow); BuyPrice = CoverPrice = Close;
Sell = Short = Cross(slow, fast); SellPrice = ShortPrice = Close;
Plot(Equity(), "Strategy Profit", colorGreen, styleLeftAxisScale);
If you wanted to make use of the perfect profit value, then you could keep just the perfect profit signals above and add custom backtester code to store ~~~Equity in a composite (e.g. ~PerfectProfit). Then run your actual strategy to generate a new ~~~Equity.
Mike
--- In amibroker@xxxxxxxxxxxxxxx, Thomas Ludwig <Thomas.Ludwig@xxx> wrote: > > Mike, > > in spite of my critical remark I'm actually using zig, too, to calculate ME. > Something simple like > > amount = Param("ZigZag-Amount", 1, 0.1, 1.5, 0.1 ); > > zz0 = Zig( c, amount ); > up=zz0>Ref(zz0,-1); > down=zz0<Ref(zz0,-1); > Longprofit=IIf(up,zz0-Ref(zz0,-1),0); > Longprofit=Cum(Longprofit); > Shortprofit=IIf(down,Ref(zz0,-1)-zz0,0); > Shortprofit=Cum(Shortprofit); > > if( ParamToggle("Long AND Short Trades?", "No|Yes", 0 ) ) > PP=Longprofit + Shortprofit; > else PP=Longprofit; > > It's not a "perfect" calculation of Perfect Profit but - as you've put it - > still a reasonable measure. > > Regards > > Thomas > > On 26.10.2009, 22:10:11 Mike wrote: > > A valid point. > > > > You would still be compounding based on the Zig pivot points. And, > > depending on what value you used for Zig, the difference might be small. > > But, true, over the long run there would likely be a difference due to > > compounding. > > > > Though, given that the calculation is meant solely as a benchmark, it's > > probably still a reasonable measure (and perhaps a less discouraging one) > > to compare against. > > > > It is unrealistic to think that we could possibly capture every single > > pivot. But, getting pretty close to a larger Zig value... maybe, just > > maybe ;) > > > > Mike > > > > --- In amibroker@xxxxxxxxxxxxxxx, Thomas Ludwig Thomas.Ludwig@ wrote: > > > On 20.10.2009, 08:47:38 Mike wrote: > > > > In "The Evaluation and Optimization of Trading Strategies", Robert > > > > Pardo describes Perfect Profit as "buying at every valley and selling > > > > at every peak". > > > > > > > > He suggests that Correlation between Equity Curve and Perfect Profit > > > > (CECPP) "is an excellent sole evaluation measure" (i.e. fitness > > > > function). > > > > > > > > Independant of fitness function, he further suggests that model > > > > efficiency can be measured by expressing Net Profit as a ratio of > > > > Perfect Profit; (Net Profit / Perfect Profit) * 100 with a value of 5 > > > > or greater being very good. > > > > > > > > What you describe in your note sounds very much like his model > > > > efficiency measure. > > > > > > > > If you simplify the idea a bit, using minimum price movements, you end > > > > up with Zig instead of Perfect Profit. > > > > > > Yes, but that doesn't include compounding. So that seems to be a little > > > bit too much simplification ;-) > > > > > > Greetings, > > > > > > Thomas > > > > > > > Mike > > > > > > > > --- In amibroker@xxxxxxxxxxxxxxx, "Steve Dugas" <sjdugas@> wrote: > > > > > Hi - For years I have been calculating stats for the reg line > > > > > alongside stats for the equity curve. But lately I have been > > > > > wondering about the value of the regression line because, in real > > > > > life there are volatile periods where the market has more to give, > > > > > and less volatile periods where there just isn't as much available. > > > > > Would it be better to shoot for capturing a consistent % of what is > > > > > available rather than just a consistent %? I was thinking about how > > > > > to account for this, the best I have come up with is to replace the > > > > > reg line with a "perfect system eq line", i.e. one that looks ahead > > > > > to the next day and pre-positions itself so that it wins every day. > > > > > Then scale it down to see how the system eq line fits against the > > > > > "perfect shape". Anyone have any thoughts whether this might be a > > > > > better approach? Thanks! > > > > > > > > > > Steve > > > > > > > > > > > > > > > ----- Original Message ----- > > > > > From: "aarbee60" <rajbakshi@> > > > > > To: amibroker@xxxxxxxxxxxxxxx > > > > > Sent: Monday, October 19, 2009 8:02 PM > > > > > Subject: [amibroker] Re: Is the Walk forward study useful? > > > > > > > > > > > In terms of getting significantly different results by shifting IS > > > > > > and OOS windows, could it be the result of using ObjFun like > > > > > > CAR/MDD where the result would be different if the CAR and/or MDD > > > > > > changes significantly at the beginning or end of the IS window. In > > > > > > this case, as the IS or OOS window is shifted the ObjFun changes > > > > > > dramatically giving rise to the behaviour noted in the earlier > > > > > > posts of this thread. > > > > > > > > > > > > Curtis Faith in his "Way of the Turtle" refers to this behaviour in > > > > > > the context of designing more robust metrics. He has devised a > > > > > > couple of metrics that make a lot of sense. RAR% (Regressed Annual > > > > > > Return percentage) instead of CAR uses the beginning and ending > > > > > > values of linear regression line instead of those of the equity > > > > > > curve. > > > > > > > > > > > > For example if at the beginning of the IS or OOS window, the equity > > > > > > curve had a downturn and a significant upturn before the end of > > > > > > that window the CAR would be significantly higher. In the same case > > > > > > if the Linear Regression line was used, the CAR value would be > > > > > > less. In general, the RAR% value is less sensitive to equity > > > > > > changes at the beginning and end of the test. This is why Curtis > > > > > > Faith refers to it as a more Robust measure of performance. > > > > > > > > > > > > Anyone has any views on above. Would be very interested to hear. > > > > > > > > > > > > Cheers > > > > > > Raj Bakshi > > > > > > > > > > > > --- In amibroker@xxxxxxxxxxxxxxx, "Mike" <sfclimbers@> wrote: > > > > > >> Hi Ton, > > > > > >> > > > > > >> I agree that the rule of thumb is subjective. So far, I've been > > > > > >> willing to live with it. > > > > > >> > > > > > >> It appears that you and I have different expectations of IS/OOS > > > > > >> window sizes. I treat the calculation of walk forward window sizes > > > > > >> as a second pass optimization, similar to a simple moving average > > > > > >> (SMA) crossover system. > > > > > >> > > > > > >> - There are two variables (e.g. IS length/OOS length vs. fast > > > > > >> SMA/slow SMA) > > > > > >> - An optimal combination is desired > > > > > >> - We use a fitness function to measure optimal (e.g. OOS:IS ratio > > > > > >> vs. CAR/MDD) > > > > > >> > > > > > >> This is how I try to satisfy your Aronson quote "Each strategy > > > > > >> will have its own best values for IS/OOS periods". > > > > > >> > > > > > >> Upon finding an optimal CAR/MDD using fast SMA/slow SMA, we should > > > > > >> theoretically be able to trade that same optimal combination of > > > > > >> fast SMA/slow SMA over different time periods and expect to get a > > > > > >> somewhat stable CAR/MDD (subject to changing market conditions). > > > > > >> > > > > > >> I would not expect combinations of fast SMA/slow SMA to be stable > > > > > >> relative to each other. Looking at a 3-D graph for this crossover > > > > > >> system will reveal peaks and valleys. Taking a single slice of > > > > > >> that graph (i.e. holding slow SMA constant and varying only fast > > > > > >> SMA) will reveal a rising and falling wave. > > > > > >> > > > > > >> So, I would expect exactly the same in the IS/OOS experiment you > > > > > >> describe. You are simply taking a slice of the 2 variable > > > > > >> optimization graph (holding IS constant and varying OOS). I would > > > > > >> expect a rising and falling wave representing the peaks and > > > > > >> valleys that would appear on the full 3-D graph. > > > > > >> > > > > > >> If I optimize the ratio of OOS:IS using IS length/OOS length, then > > > > > >> I expect to get a somewhat consistent OOS:IS ratio (subject to > > > > > >> market changes) when using that same optimal IS length/OOS length > > > > > >> over different data ranges. I don't expect to get a stable OOS:IS > > > > > >> ratio using a fixed IS length and variable OOS length. > > > > > >> > > > > > >> Mike > > > > > >> > > > > > >> --- In amibroker@xxxxxxxxxxxxxxx, "Ton Sieverding" > > > > > >> <ton.sieverding@> > > > > > >> > > > > > >> wrote: > > > > > >> > Thanks for your patience Mike -) > > > > > >> > > > > > > >> > 1. I know Pardo disagrees with Aronson. And yes I am also using > > > > > >> > Pardo's rule of thumb. But a rule of thumb without a scientific > > > > > >> > explanation is still a rule of thumb and therefore subjective. > > > > > >> > The result of this is when taking 1/8 in stead of 1/3, I am > > > > > >> > getting a completely different results. That's what Aronson > > > > > >> > tells me. So I do not understand why Pardo disagrees with > > > > > >> > Aronson ... Of course I should ask him. And I will ... > > > > > >> > > > > > > >> > 2. Here you are telling me what Aronson says : "Each strategy > > > > > >> > will have its own best values for IS/OOS periods". But trying to > > > > > >> > find the best values is empirical and therefore without having a > > > > > >> > 'good theory' why your are getting these values is highly > > > > > >> > subjective. Pardo is not giving me this good theory and Aronson > > > > > >> > tells me this good theory does not exist ... > > > > > >> > > > > > > >> > 3. With regard to our topic, it's not so important which > > > > > >> > objective function you are using for the WalkFoward. In general > > > > > >> > I use the CAR/MDD. But whatever OF gives you the same random > > > > > >> > WalkForward results. Where of course by definition you should > > > > > >> > use a return/risk related OF ... > > > > > >> > > > > > > >> > 4. The way I am analyzing the WalkForward result is simple. I am > > > > > >> > calculating the differences between the IS and OOS results in > > > > > >> > percentages from OOS. Then I am taking the average and standard > > > > > >> > deviation of all these percentages. This gives me an idea about > > > > > >> > the average IS/OOS error as well as the spread around this > > > > > >> > average. For the same AFL using the same Symbol you should do > > > > > >> > the WalkFoward in the way I mentioned in my previous email and > > > > > >> > calculate the above average/stdev relation. In order to get a > > > > > >> > stable WalkForward result being independent of the IS/OOS ratio, > > > > > >> > the average/stdev relation should be more or less stable. It's > > > > > >> > not. It's highly dependent on the IS/OOS ratio you are using ... > > > > > >> > > > > > > >> > BTW ... To get things straight, I am not throwing WalkFoward out > > > > > >> > of the window. I am just trying to believe in what I am using. > > > > > >> > And it's getting more and more difficult for me ... > > > > > >> > > > > > > >> > Regards, Ton. > > > > > >> > > > > > > >> > > > > > > >> > > > > > > >> > > > > > > >> > ----- Original Message ----- > > > > > >> > From: Mike > > > > > >> > To: amibroker@xxxxxxxxxxxxxxx > > > > > >> > Sent: Monday, October 05, 2009 11:09 AM > > > > > >> > Subject: [amibroker] Re: Is the Walk forward study useful? > > > > > >> > > > > > > >> > > > > > > >> > Ton, > > > > > >> > > > > > > >> > 1. Pardo disagrees with Aronson (and Bandy). Pardo suggests > > > > > >> > that a OOS to IS ration of 25% - 35% is best, but that a good > > > > > >> > rule of thumb for empirical testing is 1/8 to 1/3. > > > > > >> > > > > > > >> > 2. Yes, I suspect that each strategy will have its own best > > > > > >> > values for IS/OOS and that other values will appear as useless. > > > > > >> > It is up to us to try and find the best values. > > > > > >> > > > > > > >> > With respect to your comment: "I am getting results that show > > > > > >> > a random pattern", my question remains; What are you measuring? > > > > > >> > In other words, what values appear random - your fitness value? > > > > > >> > CAR? Something else? > > > > > >> > > > > > > >> > 3. I have done very much as you ask, except that I also varied > > > > > >> > my IS period. I mostly kept my ratios within Pardo's suggested > > > > > >> > 1/8 to 1/3, but went as low as 1/12 and as high as 1/2 just to > > > > > >> > be sure. > > > > > >> > > > > > > >> > For example IS=1 year, IS=2 years, IS=3 years giving > > > > > >> > > > > > > >> > IS1yr+OOS6mth, IS1yr+OOS3mth, IS1yr+OOS1mth > > > > > >> > IS2yr+OOS12mth, IS2yr+OOS6mth, IS2yr+OOS3mth > > > > > >> > IS3yr+OOS18mth, IS3yr+OOS12mth, IS3yr+OOS6mth > > > > > >> > > > > > > >> > IS2yr+OOS6mth produced the most consistent CAR, even though a > > > > > >> > weighted UPI was used as the fitness function for the actual > > > > > >> > walk forward. > > > > > >> > > > > > > >> > I do not have a strong opinion as to whether or not there > > > > > >> > really is a relationship between IS and OOS sizes. I found that > > > > > >> > Pardo's rule of thumb was as good a starting place as any. I was > > > > > >> > happy that my values (25%) coincided with what he advised. But, > > > > > >> > had my studies suggested a ratio outside of Pardo's range, I > > > > > >> > would have still gone with what my results suggested, despite > > > > > >> > Pardo's advice. > > > > > >> > > > > > > >> > Mike > > > > > >> > > > > > > >> > --- In amibroker@xxxxxxxxxxxxxxx, "Ton Sieverding" > > > > > >> > <ton.sieverding@> > > > > > >> > > > > > > >> > wrote: > > > > > >> > > Hi Mike, > > > > > >> > > > > > > > >> > > What I am saying is : > > > > > >> > > > > > > > >> > > 1. That according to David Aronson "There is no theory that > > > > > >> > > > > > > >> > suggests what fraction of the data should be assigned to > > > > > >> > training ( IS ) and testing ( OOS )." and that "Results can be > > > > > >> > very sensitive to these choices ... ". I assume that he knows > > > > > >> > where he is talking about ... > > > > > >> > > > > > > >> > > 2. That when I am doing WalkFoward tests following the > > > > > >> > > advice of > > > > > >> > > > > > > >> > Howard Bandy, Robert Pardo AND Van Tharp, I am getting results > > > > > >> > that show a random patron when changing the OOS en IS periods. > > > > > >> > So my conclusion is that WalkFoward is a subjective test ... > > > > > >> > > > > > > >> > > Therefore I have serious problems using WalkFoward tests. If > > > > > >> > > you > > > > > >> > > > > > > >> > can help me to get things done in an objective way then I will > > > > > >> > be delighted to know how you want to do that. But for sure Van > > > > > >> > Tharp did not help me ... > > > > > >> > > > > > > >> > > Please do a simple WF test with OOS=1year and > > > > > >> > > IS=1month...12months. > > > > > >> > > > > > > >> > So creating WF results for OOS1y+IS1m, OOS1y+IS2m etc. And see > > > > > >> > what you are getting. This is purely random. The result says > > > > > >> > nothing to me ... > > > > > >> > > > > > > >> > > Regards, Ton. > > > > > >> > > > > > > > >> > > > > > > > >> > > > > > > > >> > > ----- Original Message ----- > > > > > >> > > From: Mike > > > > > >> > > To: amibroker@xxxxxxxxxxxxxxx > > > > > >> > > Sent: Monday, October 05, 2009 9:29 AM > > > > > >> > > Subject: [amibroker] Re: Is the Walk forward study useful? > > > > > >> > > > > > > > >> > > > > > > > >> > > Ton, > > > > > >> > > > > > > > >> > > Are you saying that you have not found an IS/OOS pair that > > > > > >> > > works > > > > > >> > > > > > > >> > well? What measure are you using to judge "stability" of the > > > > > >> > walk forward process (i.e. what measure are you using to judge > > > > > >> > the process as random)? > > > > > >> > > > > > > >> > > After testing with multiple IS periods, and with multiple > > > > > >> > > OOS > > > > > >> > > > > > > >> > periods, I was able to identify "fixed" window lengths that > > > > > >> > proved more consistent than the others tested. > > > > > >> > > > > > > >> > > I reached this conclusion by charting a distribution curve > > > > > >> > > of CAR > > > > > >> > > > > > > >> > for the OOS results. My fitness function is currently based on > > > > > >> > UPI, and thus my walk forward is driven by that value. However, > > > > > >> > ultimately my interest is in how consistent CAR would be which > > > > > >> > is why I used that for evaluating the goodness of fit for the > > > > > >> > IS/OOS period lengths. > > > > > >> > > > > > > >> > > In my case, over a 13 year period, a 2 year IS and 6 month > > > > > >> > > OOS (for > > > > > >> > > > > > > >> > a total of 26 OOS data points) produced the most normal looking > > > > > >> > distribution of CAR results (i.e. central peak, smallest > > > > > >> > standard deviation). Excluding the results from all of 1999 and > > > > > >> > the first half of 2000 (during which results were abnormally > > > > > >> > strong), the distribution curve looks even better. > > > > > >> > > > > > > >> > > Also, have you tried working with different fitness > > > > > >> > > functions? > > > > > >> > > > > > > >> > Perhaps your fitness function doesn't adequately identify the > > > > > >> > "signal" and thus misguides the walk forward, regardless of > > > > > >> > IS/OOS window lengths. > > > > > >> > > > > > > >> > > I am in the process of running a new walk forward over the > > > > > >> > > last 7.5 > > > > > >> > > > > > > >> > years using Van Tharp's System Quality Number (SQN) as my > > > > > >> > fitness function. I have kept the same 2 year IS/6 months OOS > > > > > >> > for a total of 15 OOS data points. My system strives to generate > > > > > >> > a minimum average of 2 trades per day, so each IS period > > > > > >> > generally has 1000 or more trades from which to calculate the > > > > > >> > fitness. > > > > > >> > > > > > > >> > > It has not run to completion yet. But, for the periods that > > > > > >> > > have > > > > > >> > > > > > > >> > produced results, the results look promising (at least with > > > > > >> > respect to the SQN of the OOS relative to the SQN of the IS, I > > > > > >> > have not yet created the distribution of CAR for OOS). > > > > > >> > > > > > > >> > > Assuming that the remainder of the results are equally > > > > > >> > > strong, I > > > > > >> > > > > > > >> > will walk forward further back in history to get the full 26 > > > > > >> > data points to compare against the results produced using my UPI > > > > > >> > fitness. If the CAR distribution is more normal using SQN as > > > > > >> > fitness, then I will officially start using SQN for generating > > > > > >> > optimal values for my next live OOS. > > > > > >> > > > > > > >> > > If you are willing to share, I would be curious to hear if > > > > > >> > > SQN as a > > > > > >> > > > > > > >> > fitness function was able to produce a more stable walk forward > > > > > >> > for you, and what measure you are using to judge "stable". > > > > > >> > > > > > > >> > > Mike > > > > > >> > > > > > > > >> > > --- In amibroker@xxxxxxxxxxxxxxx, "Ton Sieverding" > > > > > >> > > > > > > >> > <ton.sieverding@> wrote: > > > > > >> > > > Hi Howard, > > > > > >> > > > > > > > > >> > > > I still am struggling with the following sentence from > > > > > >> > > > David > > > > > >> > > > > > > >> > Aronson : "The decision about how to apportion the data between > > > > > >> > the IS and OOS subsets is arbitrary. There is no theory that > > > > > >> > suggests what fraction of the data should be assigned to > > > > > >> > training ( IS ) and testing ( OOS ). Results can be very > > > > > >> > sensitive to these choices ... ". Because this is exactly what I > > > > > >> > am seeing. WalkFoward results are more then sensitive to the > > > > > >> > IS/OOS relation and in many cases a pure random story. I am > > > > > >> > getting more and more the feeling that WalkForward is not the > > > > > >> > correct or better objective way to test trading systems. With > > > > > >> > all respect to Robert Pardo's idea's about this topic and what > > > > > >> > you are writing in QTS ... > > > > > >> > > > > > > >> > > > Regards, Ton. > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > ----- Original Message ----- > > > > > >> > > > From: Howard B > > > > > >> > > > To: amibroker@xxxxxxxxxxxxxxx > > > > > >> > > > Sent: Monday, October 05, 2009 12:48 AM > > > > > >> > > > Subject: Re: [amibroker] Re: Is the Walk forward study > > > > > >> > > > useful? > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > Greetings all -- > > > > > >> > > > > > > > > >> > > > My point of view on the length of the in-sample and > > > > > >> > > > out-of-sample > > > > > >> > > > > > > >> > may be a little different. > > > > > >> > > > > > > >> > > > The logic of the code has been designed to recognize some > > > > > >> > > > pattern > > > > > >> > > > > > > >> > or characteristic of the data. The length of the in-sample > > > > > >> > period is however long it takes to keep the model (the logic) in > > > > > >> > synchronization with the data. There is no one answer to what > > > > > >> > that length is. When the pattern changes, the model fits it less > > > > > >> > well. When the pattern changes significantly, the model must be > > > > > >> > re-synchronized. The only person who can say whether the length > > > > > >> > is correct or should be longer or shorter is the person running > > > > > >> > the tests. > > > > > >> > > > > > > >> > > > The length of the out-of-sample period is however long the > > > > > >> > > > model > > > > > >> > > > > > > >> > and the data remain in sync. That must be some length of time > > > > > >> > beyond the in-sample period in order to make profitable trades. > > > > > >> > It could be a long time, in which case there is no need to > > > > > >> > modify the model at all during that period. There is no general > > > > > >> > relationship between the length of the in-sample period and the > > > > > >> > length of the out-of-sample period -- none. There is no general > > > > > >> > relationship between the performance in-sample and the > > > > > >> > performance out-of-sample. The greater the difference between > > > > > >> > the two, the better the system has been fit to the data over the > > > > > >> > in-sample period. But that does not necessarily mean that the > > > > > >> > out-of-sample results are less meaningful. > > > > > >> > > > > > > >> > > > You can perform some experiments to see what the best > > > > > >> > > > in-sample > > > > > >> > > > > > > >> > length is. And then to see what the typical out-of-sample length > > > > > >> > is. Knowing these two, set up a walk forward run using those > > > > > >> > lengths. After the run is over, ignore the in-sample results. > > > > > >> > They have no value in estimating the future performance of the > > > > > >> > system. It is the out-of-sample results that can give you some > > > > > >> > idea of how the system might act when traded with real money. > > > > > >> > > > > > > >> > > > It is nice to have a lot of closed traded in the > > > > > >> > > > out-of-sample > > > > > >> > > > > > > >> > period, but you can run statistics on as few as 5 or 6. Having > > > > > >> > fewer trades means that it will be more difficult to achieve > > > > > >> > statistical significance. The number 30 is not magic -- it is > > > > > >> > just conventional. > > > > > >> > > > > > > >> > > > I think it helps to distinguish between the in-sample and > > > > > >> > > > > > > >> > out-of-sample periods this way -- in-sample is seeing how well > > > > > >> > the model can be made to fit the older data, out-of-sample is > > > > > >> > seeing how well it might fit future data. > > > > > >> > > > > > > >> > > > Ignore the television ads where person after person > > > > > >> > > > exclaims > > > > > >> > > > > > > >> > "backtesting!" as though that is the key to system development. > > > > > >> > It is not. Backtesting by itself, without going on to walk > > > > > >> > forward testing, will give the trading system developer the > > > > > >> > impression that the system is good. In-sample results are always > > > > > >> > good. We do not stop fooling with the system until they are > > > > > >> > good. But in-sample results have no value in predicting future > > > > > >> > performance -- none. > > > > > >> > > > > > > >> > > > There are some general characteristics of trading systems > > > > > >> > > > that > > > > > >> > > > > > > >> > make them easier to validate. Those begin with having a positive > > > > > >> > expectancy -- no system can be profitable in the long term > > > > > >> > unless it has a positive expectancy. Then going on to include > > > > > >> > trade frequently, hold a short time, minimize losses. Of course, > > > > > >> > there have been profitable systems that trade infrequently, hold > > > > > >> > a long time, and suffer deep drawdowns. It is much harder to > > > > > >> > show that those were profitable because they were good rather > > > > > >> > than lucky. > > > > > >> > > > > > > >> > > > There is more information about in-sample, out-of-sample, > > > > > >> > > > walk > > > > > >> > > > > > > >> > forward testing, statistical validation, objective functions, > > > > > >> > and so forth in my book, "Quantitative Trading Systems." > > > > > >> > > > > > > >> > > > http://www.quantitativetradingsystems.com/ > > > > > >> > > > > > > > > >> > > > Thanks for listening, > > > > > >> > > > Howard > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > On Sun, Oct 4, 2009 at 10:56 AM, Bisto <bistoman73@> > > > > > >> > > > wrote: > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > Yes, I believe that you should increase the IS period > > > > > >> > > > > > > > > >> > > > as general rule is not true "the shortest the best" trying > > > > > >> > > > to > > > > > >> > > > > > > >> > catch every market change because it's possible that a too short > > > > > >> > IS period produces a too low number of trades with no > > > > > >> > statistical robustness --> you will find parameters that are > > > > > >> > more likely candidated to fail in OS > > > > > >> > > > > > > >> > > > try a longer IS period and let's see what will happen > > > > > >> > > > > > > > > >> > > > I read an interesting book on this issue: "The evaluation > > > > > >> > > > and > > > > > >> > > > > > > >> > optimization of trading strategies" by Pardo. Maybe he repeated > > > > > >> > too much times the same concepts nevertheless I liked it > > > > > >> > > > > > > >> > > > if anyone could suggest a better book about this issue it > > > > > >> > > > would > > > > > >> > > > > > > >> > be very appreciated > > > > > >> > > > > > > >> > > > Bisto > > > > > >> > > > > > > > > >> > > > --- In amibroker@xxxxxxxxxxxxxxx, "Gonzaga" <gonzagags@> > wrote: > > > > > >> > > > > Oh, sorry, I am lost in translation ... ;-) > > > > > >> > > > > Yes I meant trades of my IS period. > > > > > >> > > > > I've got about 70 trades in my IS period, three months. > > > > > >> > > > > BUT, I buy stocks in a multiposition way.This means, > > > > > >> > > > > that my > > > > > >> > > > > > > >> > hole capital divides among several stocks purchased > > > > > >> > simultaneously. > > > > > >> > > > > > > >> > > > > So, in my statistics, I use to average my trades. When I > > > > > >> > > > > use > > > > > >> > > > > > > >> > maxopenpositions=7, I use to average my results every 7 trades. > > > > > >> > > > > > > >> > > > > Considering that, my trades in three months are not 70, > > > > > >> > > > > but > > > > > >> > > > > > > >> > less ( not exactly 70/7, but less than 70) > > > > > >> > > > > > > >> > > > > If I use maxopenposition=1, which is, invest all my > > > > > >> > > > > capital > > > > > >> > > > > > > >> > every trade, in three months I would have about 29 trades. > > > > > >> > > > > > > >> > > > > So I suppose I have to increase the IS period.. isn`t > > > > > >> > > > > it? > > > > > >> > > > > > > > > > >> > > > > --- In amibroker@xxxxxxxxxxxxxxx, "Bisto" <bistoman73@> > > > > > > wrote: > > > > > >> > > > > > What do you mean with "I don't have many buyings and > > > > > >> > > > > > > >> > sellings"? > > > > > >> > > > > > > >> > > > > > If you have less than 30 trades in an IS period, IMHO, > > > > > >> > > > > > you > > > > > >> > > > > > > >> > are using a too short period due to not statistical robustness > > > > > >> > --> WFA is misleading, try a longer IS period > > > > > >> > > > > > > >> > > > > > Bisto > > > > > >> > > > > > > > > > > >> > > > > > --- In amibroker@xxxxxxxxxxxxxxx, "Gonzaga" > > > > > >> > > > > > <gonzagags@> > > > > > >> > > > > > > >> > wrote: > > > > > >> > > > > > > Thanks for the answers > > > > > >> > > > > > > To Keith McCombs : > > > > > >> > > > > > > > > > > > >> > > > > > > I use 3 months IS test and 1 month step, this is, 1 > > > > > >> > > > > > > month > > > > > >> > > > > > > >> > OS test. My system is an end-of day-system, so I don't have many > > > > > >> > buyings and sellings.. > > > > > >> > > > > > > >> > > > > > > Perhaps I should make bigger the IS period? > > > > > >> > > > > > > > > > > > >> > > > > > > anyway, my parameter behaves well in any period. Of > > > > > >> > > > > > > course > > > > > >> > > > > > > >> > it is an optimized variable, but it doesn't fail in ten years, > > > > > >> > in none of those ten years, over 500 stocks.. a very long > > > > > >> > period.. > > > > > >> > > > > > > >> > > > > > > So, couldn't it be better, on the long run, than the > > > > > >> > > > > > > >> > parameters optimized with the WF study? > > > > > >> > > > > > > >> > > > > > > (In fact, I am using it now, the optimized variable) > > > > > >> > > > > > > That's my real question.. > > > > > >> > > > > > > > > > > > >> > > > > > > To dloyer123: > > > > > >> > > > > > > I haven't understood the meaning of the Walk Forward > > > > > >> > > > > > > >> > Efficency, and seems interesting. > > > > > >> > > > > > > >> > > > > > > can you explain it better, please..? > > > > > >> > > > > > > > > > > > >> > > > > > > > > > > > >> > > > > > > > > > > > >> > > > > > > --- In amibroker@xxxxxxxxxxxxxxx, "dloyer123" > > > > > >> > > > > > > <dloyer123@> > > > > > >> > > > > > > >> > wrote: > > > > > >> > > > > > > > I have had similar experiences. I like to use WFT > > > > > >> > > > > > > > to > > > > > >> > > > > > > >> > estimate what Pardo call's his "Walk Forward Efficency", or the > > > > > >> > ratio of the out of sample WF profits to just optimizing over > > > > > >> > the entire time period. > > > > > >> > > > > > > >> > > > > > > > A good system should have as high a WFE as > > > > > >> > > > > > > > posible. > > > > > >> > > > > > > >> > Systems with a poor WFE tend to do poorly in live trading. > > > > > >> > > > > > > >> > > > > > > > If you have a parm set that works well over a long > > > > > >> > > > > > > > period > > > > > >> > > > > > > >> > of live trading, then you are doing well! > > > > > > > > > > > > ------------------------------------ > > > > > > > > > > > > **** IMPORTANT PLEASE READ **** > > > > > > This group is for the discussion between users only. > > > > > > This is *NOT* technical support channel. > > > > > > > > > > > > TO GET TECHNICAL SUPPORT send an e-mail directly to > > > > > > SUPPORT {at} amibroker.com > > > > > > > > > > > > TO SUBMIT SUGGESTIONS please use FEEDBACK CENTER at > > > > > > http://www.amibroker.com/feedback/ > > > > > > (submissions sent via other channels won't be considered) > > > > > > > > > > > > For NEW RELEASE ANNOUNCEMENTS and other news always check DEVLOG: > > > > > > http://www.amibroker.com/devlog/ > > > > > > > > > > > > Yahoo! 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