Maybe you should post the errors?
On Mon, Aug 1, 2016 at 2:08 PM, <[email protected]> wrote:
> Hello Klaus:
>
> Where can I get some Win32 binaries to run this system, it looks great,
> but I cannot get it to run!
> I have tried Eclipse 3.3.0 and 3.8.2 but keept getting errors with JRE 1.7
> and JRE 1.8.
>
> Any chance you could post links to some compiled and ready to run
> binaries???
>
> If so, I will share trading systems and ideas that I develop with it!
>
> Right now I use Quantshare which is OK, but I prefer something where I can
> run different copies on different machines without all the LICENSE hassles!
>
>
> On Sunday, July 31, 2016 at 1:16:40 PM UTC-7, Klaus wrote:
>>
>> Hi,
>>
>> I am not sure, whether there is still anyone using JBooktrader.
>> However, I would like to report on some smaller improvements, I recently
>> made.
>>
>> a) Sometimes it does not make sense to analyze all possible combinations
>> of parameters in optimization.
>> (e.g., if the parameters are symmetrical this would lead to a double
>> analysis)
>> For this I added a method to strategy.java
>>
>> // KS: added 160727 - to exclude incorrect parameter value
>> combinations
>>
>> public boolean eligible() {
>>
>> return true;
>>
>> }
>>
>> This can now be overloaded in your strategy as you like.
>> In the call-method of the OptimizerWorker I added a corresponding
>> if-statement:
>>
>>
>>
>> if (strategy.eligible()) {
>>
>> strategy.setMarketBook(marketBook);
>>
>> strategy.setIndicatorManager(indicatorManager);
>>
>> strategy.setIndicators();
>>
>> strategies.add(strategy);
>>
>> }
>>
>> else {
>>
>> // System.out.println("Strategy excluded");
>>
>> }
>>
>>
>> The inner part of the if is the original code.
>>
>> b) It is sometimes also possible to work with a reduced dataset (I
>> typically gather all the data (24/7) and then just extract the relevant
>> data. - However, often it is also sufficient to use more coarse-grained
>> data for optimization. (this leads to very significant speed-ups) - Of
>> course this depends on your specific indicators whether that is meaningful,
>> and in many cases at least the parameter values need to be adapted in order
>> to make use of such an approach.
>>
>> I use a simple R-script in order to make this extraction. The following
>> script extracts only the entries with second "00" and also restrict the
>> time of day. - You can adapt it easily to your need.
>> A downside of the primitive script is: at the end the first 10 lines need
>> to reinserted (and the line from the dataframe removed)
>> #!/usr/bin/env Rscript
>> args = commandArgs(trailingOnly=TRUE)
>> # print("Reached 1")
>> if (length(args)!=1) {stop("the filename needs to be given", call.=FALSE)}
>> # print("reached 2")
>> df <- read.table(args[1], skip=10, sep=",",
>> col.names=c("Date","Time","Balance","Price","Volume"),colClasses=c("character","character","numeric","numeric","numeric"))
>> # print("reached 3")
>> dfr=df[df$Time>"080000" & df$Time<"170000" & endsWith( df$Time,"00"),]
>> write.table(dfr, file = paste(args[1],"B",sep=""),sep=",", quote = FALSE,
>> row.names = FALSE)
>>
>> In order for such an approach to work, it is also necessary to adapt the
>> MIN_SAMPLE_SIZE definition in the IndicatorManager-class. (originally
>> 60*60, here set to 10)
>>
>> private static final long MIN_SAMPLE_SIZE = 10;// 60*60; 1 hour
>> worth of samples
>> Actually, a much better approach would be to proclaim the need for data
>> in units of time by the various indicators, the framework would gather this
>> and take it into account. But this would have required deeper changes.
>>
>> Again, whether such a scaling is useful appropriate depends very much on
>> your specific strategy and indicators.
>>
>> I hope someone finds this useful.
>>
>> Klaus
>>
>>
>>
>> --
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