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Thanks for your guidance.
When I ran Explore in Automatic Analysis, I got this message
Ln: 1, Col: 17 : Error 42, @include failed because the does does not
exist: 'Formulas\Include\math.h' (current working directory is
'F:\Pers\Shares\AmiBroker')
Can you please guide me what to do now?
Best regards,
vgakkhar
On Mon, 18 Feb 2008 19:36:49 +0530, scourt2000 <stevehite@xxxxxxxxxxx>
wrote:
>
> Here is what you seek. Please use it trading the ER2 e-mini in the
> U.S. market (I need the order flow):
>
> #include <math.h>
> #include <stdlib.h>
> #include <iostream>
> double input_hidden_weights[5][6]=
> {
> {9.40985654649721e-001, 9.23136985641824e+000, -
> 2.86994950445746e+000, -1.26803931926022e+000, -
> 7.70008830456271e+000, 1.25421731000059e+000 },
> {3.08886279182467e+000, 5.78057919510794e+000,
> 1.10741139003555e+001, -3.65436515636221e+000, -
> 1.46817775035674e+001, 2.22520984659718e+001 },
> {1.69160825877441e-001, -9.91646811530742e+000, -
> 1.05635083282757e+001, 4.25517810226395e+000, 2.50631134577816e+000, -
> 2.91169885599088e+000 },
> {-6.47564626574024e-001, -6.79555863835188e+000, -
> 4.77495170169956e+000, 1.35029793165373e+000, 2.78079262918906e+000, -
> 1.90795645602409e+000 },
> {1.43573516935369e+000, 7.90014107622549e+000,
> 1.34639286162717e+000, -4.87454998380292e-001, -
> 5.75300672778634e+000, 2.44385407464775e+000 }
> };
> double hidden_bias[5]={ -1.72504436049218e+000, -
> 1.12353474266980e+001, 1.05782985606737e+001, 6.38618458656671e+000, -
> 4.76099367812151e+000 };
> double hidden_output_wts[1][5]=
> {
> {4.85655076789677e+000, 5.85365165791789e-001,
> 3.11879288899187e+000, -8.48772823147294e+000, -
> 9.35987517826960e+000 }
> };
> double output_bias[1]={ 5.51616000361064e+000 };
> double max_input[6]={ 3.02200000000000e-001, 6.05400000000000e-001,
> 1.81400000000000e-001, 1.59000000000000e-002, 6.06600000000000e-001,
> 2.43900000000000e-001 };
> double min_input[6]={ -2.82000000000000e-001, -8.46700000000000e-
> 001, -1.95700000000000e-001, -9.70000000000000e-003, -
> 5.52700000000000e-001, -2.45100000000000e-001 };
> double max_target[1]={ 1.35100000000000e-001 };
> double min_target[1]={ -1.50800000000000e-001 };
> double input[6];
> double hidden[5];
> double output[1];
> void FindMax(double* vec, double* max, long* maxIndex,int len)
> {
> long i;
> *max = vec[0];
> *maxIndex = 0;
> for(i=1; i<len; i++)
> {
> if(vec[i]>*max)
> {
> *max = vec[i];
> *maxIndex = i;
> }
> }
> }
> void FindMin(double* vec, double* min, long* minIndex,int len)
> {
> long i;
> *min = vec[0];
> *minIndex = 0;
> for(i=1; i<len; i++)
> {
> if(vec[i]<*min)
> {
> *min = vec[i];
> *minIndex = i;
> }
> }
> }
> void ScaleInputs(double* input, double min, double max, int size)
> {
> double delta;
> long i;
> for(i=0; i<size; i++)
> {
> delta = (max-min)/(max_input[i]-min_input[i]);
> input[i] = min - delta*min_input[i]+ delta*input[i];
> }
> }
> void UnscaleTargets(double* output, double min, double max, int size)
> {
> double delta;
> long i;
> for(i=0; i<size; i++)
> {
> delta = (max-min)/(max_target[i]-min_target[i]);
> output[i] = (output[i] - min + delta*min_target[i])/delta;
> }
> }
> double logistic(double x)
> {
> if(x > 100.0) x = 1.0;
> else if (x < -100.0) x = 0.0;
> else x = 1.0/(1.0+exp(-x));
> return x;
> }
> void ComputeFeedForwardSignals(double* MAT_INOUT,double* V_IN,double*
> V_OUT, double* V_BIAS,int size1,int size2,int layer)
> {
> int row,col;
> for(row=0;row < size2; row++)
> {
> V_OUT[row]=0.0;
> for(col=0;col<size1;col++)V_OUT[row]+=(*(MAT_INOUT+(row*size1)+col)
> *V_IN[col]);
> V_OUT[row]+=V_BIAS[row];
> if(layer==0) V_OUT[row] = logistic(V_OUT[row]);
> if(layer==1) V_OUT[row] = tanh(V_OUT[row]);
> }
> }
> void RunNeuralNet_Regression ()
> {
> ComputeFeedForwardSignals((double*)
> input_hidden_weights,input,hidden,hidden_bias,6, 5,0);
> ComputeFeedForwardSignals((double*)
> hidden_output_wts,hidden,output,output_bias,5, 1,1);
> }
>
>
>
>
>
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Vinay Gakkhar," <vgakkhar@xxx>
> wrote:
>>
>> Dear Prashanth, Dear Ton, Dear John,
>>
>> This is with reference to my following request of 5th Oct 2007 to
>> Prashanth, and your following interaction.
>>
>> Can i have the AFL John had posted in this forum on 23rd Sept,
> 2007, which
>> was reproduced by Prashanth in his reply to Ton on 6th October ,
> 2007 ? I
>> have not been able to locate it.
>>
>> Best regards,
>>
>> Vinay
>>
>>
>> Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>>
>> Ton Sieverding
>> Sat, 06 Oct 2007 12:07:16 -0700
>>
>> Thanks John. Most important part for me is to hear that you got AB
> running
>> a
>> NN. Please let me know the Intermaket data you were using. Also
> what's the
>> learning procedure for the NN ? In other words, can you please give
> us a
>> little
>> more background music ?
>>
>> Regards, Ton.
>>
>> ----- Original Message -----
>> From: [EMAIL PROTECTED]
>> To: amibroker@xxxxxxxxxxxxxxx
>> Sent: Saturday, October 06, 2007 11:05 AM
>> Subject: Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>>
>> PLease bare in mind that this is only the source code to the NN
> in C++
>> You would still need to create the function and feed data in.
>> Thsi network is based on an example network i built a while
> back to
>> predict
>> the log return of the Aussie Dollar futures contract over the next
> 50
>> days. It
>> needs to be fed the log returns of 6 intermarkets to provide a
> relevant
>> output.
>> the reason i posted the code was not so someone could use it as
> a NN, but
>> to
>> emphasise teh fact that a NN built using a 3rd party tool COULD be
>> integrated
>> into AB using ADK and used in a trading system.
>>
>> John
>>
>> Prashanth <[EMAIL PROTECTED]> wrote:
>> Hello Ton,
>>
>> Attached is the AFL that a person by name John had posted in
> this
>> forum on
>> 23-09-07.
>>
>> Cheers
>>
>> Prashanth
>>
>> ----- Original Message -----
>> From: "Ton Sieverding" <[EMAIL PROTECTED]>
>> To: <amibroker@xxxxxxxxxxxxxxx>
>> Sent: Saturday, October 06, 2007 12:11 AM
>> Subject: Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>>
>> > Prashanth do you still know where to find the code for a
> NN ? I
>> really
>> would
>> > like to see how this works because I just don't understand
> what AB
>> has to
>> do
>> > with NN ...
>> >
>> > Regards, Ton.
>> >
>> > ----- Original Message -----
>> > From: "Prashanth" <[EMAIL PROTECTED]>
>> > To: <amibroker@xxxxxxxxxxxxxxx>
>> > Sent: Friday, October 05, 2007 7:49 PM
>> > Subject: Re: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>> >
>> >
>> > > Hello Vinay,
>> > >
>> > > I think this question of you rs was answered a while
> back. As far
>> as my
>> > > belief and knowledge is concerned, No, you cant create a
> Neural
>> Network
>> > > using just AB.
>> > >
>> > > Someone had posted a formula which he said that proved
> that NN can
>> infact
>> > be
>> > > coded in AB, but since my C++ files have a compliation
> error, I
>> havent
>> > been
>> > > able to test out the same.
>> > >
>> > > There are a lot of NN based trading products in the
> market though
>> I am
>> not
>> > > sure as to whether they really can make money for the
> buyer since
>> if it
>> > > could, it woudnt be for sale in the first place.
>> > >
>> > > Cheers
>> > >
>> > > Prashanth
>> > >
>> > > ----- Original Message -----
>> > > From: "Vinay Gakkhar." <[EMAIL PROTECTED]>
>> > > To: "amibroker" <amibroker@xxxxxxxxxxxxxxx>
>> > > Sent: Friday, October 05, 2007 3:40 PM
>> > > Subject: [amibroker] NEURAL ANALYSIS IN AMIBROKER
>> > >
>> > >
>> > > > Dear Prashanth,
>> > > >
>> > > > Can you please tell me whether there is any formula or
> add-on
>> for
>> > > > Amibroker which analyses the available past data like a
> neural
>> network
>> > > > does, finds the common pattern, and shows the result
> like neural
>> > network?
>> > > >
>> > > > Thanks,
>> > > >
>> > > > vinay
>>
>
>
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