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Reg. Contributing

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Dexter Moser

Reg. Contributing

Hi,

I am new to Quantlib. I have heard a lot about contributing to open-source projects. But i do not have any prior experience.As i will be graduating soon , in order to find a good job, i need to improve my skills and develop unique skills like volunteering in open-source project. I have good knowledge about the financial products and quantitative methods. Having tried the examples, i got interested in contributing to the project.

Are there any "To-do" lists according to the difficulty level.

or any documents to help the new contributors like me.

Thanks in advance.

Regards,

dmoser

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Luigi Ballabio

Re: Reg. Contributing

Dexter,
apologies for the delay. I've seen you've been suggested some docs to
get familiar with the library, so I won't go through it again. What
kind of experience do you have?

Later,
Luigi

On Mon, 2011-07-11 at 11:19 -0400, Dexter Moser wrote:

> I am new to Quantlib. I have heard a lot about contributing to
> open-source projects. But i do not have any prior experience.As i will
> be graduating soon , in order to find a good job, i need to improve my
> skills and develop unique skills like volunteering in open-source
> project. I have good knowledge about the financial products and
> quantitative methods. Having tried the examples, i got interested in
> contributing to the project.
>
>
> Are there any "To-do" lists according to the difficulty level.
>
>
> or any documents to help the new contributors like me.

--

A programming language is low-level when its programs require attention
to the irrelevant.
-- Alan Perlis

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Dexter Moser

Re: Reg. Contributing

Luigi,

I am a financial student with interest in programming. I have experience with C++. That is the reason i choose to go on with Quantlib.

I want to get good with the design patterns, Boost libraries, financial methods.

Thanks,

Mounika

On Mon, Jul 18, 2011 at 7:38 AM, Luigi Ballabio <[hidden email]> wrote:

Dexter,
apologies for the delay. I've seen you've been suggested some docs to
get familiar with the library, so I won't go through it again. What
kind of experience do you have?

Later,
Luigi

On Mon, 2011-07-11 at 11:19 -0400, Dexter Moser wrote:
> I am new to Quantlib. I have heard a lot about contributing to
> open-source projects. But i do not have any prior experience.As i will
> be graduating soon , in order to find a good job, i need to improve my
> skills and develop unique skills like volunteering in open-source
> project. I have good knowledge about the financial products and
> quantitative methods. Having tried the examples, i got interested in
> contributing to the project.
>
>
> Are there any "To-do" lists according to the difficulty level.
>
>
> or any documents to help the new contributors like me.

--

A programming language is low-level when its programs require attention
to the irrelevant.
-- Alan Perlis

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欧阳鹏

Re: Reg. Contributing

Luigi,

I am PHD candiate student in science. I have the similar case with Dexter.

I have some experience with numerical programming on fortran and Python. I also used some scientific C++ code to do simulation under Linux environment. I am familiar with solving differential equation numerically, and know some basics about Monte Carlo.

I know C++ main features , but lacks real large project design experience. I also hope I could contribute the Quantlib Project along with improving me working skills. I have already seen a small part of src codes, and it is very organized, and confirm me interest in contributing Quantlib.

Best wishes,

Yangpeng

在 Jul 20, 2011，3:50 PM， Dexter Moser 写道：

Luigi,

I am a financial student with interest in programming. I have experience with C++. That is the reason i choose to go on with Quantlib.
I want to get good with the design patterns, Boost libraries, financial methods.

Thanks,
Mounika

On Mon, Jul 18, 2011 at 7:38 AM, Luigi Ballabio <[hidden email]> wrote:

Dexter,
apologies for the delay. I've seen you've been suggested some docs to
get familiar with the library, so I won't go through it again. What
kind of experience do you have?

Later,
Luigi

On Mon, 2011-07-11 at 11:19 -0400, Dexter Moser wrote:
> I am new to Quantlib. I have heard a lot about contributing to
> open-source projects. But i do not have any prior experience.As i will
> be graduating soon , in order to find a good job, i need to improve my
> skills and develop unique skills like volunteering in open-source
> project. I have good knowledge about the financial products and
> quantitative methods. Having tried the examples, i got interested in
> contributing to the project.
>
>
> Are there any "To-do" lists according to the difficulty level.
>
>
> or any documents to help the new contributors like me.

--

A programming language is low-level when its programs require attention
to the irrelevant.
-- Alan Perlis

------------------------------------------------------------------------------
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Learn 10 ways to better secure your business today. Topics covered include:
Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
security Microsoft Exchange, secure Instant Messaging, and much more.
http://www.accelacomm.com/jaw/sfnl/114/51426210/_______________________________________________
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urun dogan

Re: Reg. Contributing

In reply to this post by Luigi Ballabio

Hi Luigi,
I am a post-doc doctoral researcher in Germany. My main researc focus is machine learning/artificial intelligence techniques. I am a develor of Shark machine learning library. This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?

Thanks a lot for your help.

Best regards
Ueruen Dogan

On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:

Grześ Andruszkiewicz

Re: Reg. Contributing

Hi Luigi,

I guess I am in similar situation here :) Currently I am a PhD student
in Mathematical Finance, but previously I have been working as a
software developer for investment banks.

I would also like to contribute to QuantLib, so that I can get my head
around the library, learn all the patterns you are using etc.

Grzegorz

On 20 July 2011 21:29, urun dogan <[hidden email]> wrote:

> Hi Luigi,
> I am a post-doc doctoral researcher in Germany. My main researc focus is
> machine learning/artificial intelligence techniques. I am a develor of Shark
> machine learning library. This library is implemented by C++ . I am really
> interested in contributing to quant lib because I find find finsnce
> chalenging and interesting. I am open to implement some machine learning
> techniques to quant lib also it is absolutelly ok for me to implement other
> things. Is there any todo list? Are there any ideas for starting?
>
> Thanks a lot for your help.
>
> Best regards
> Ueruen Dogan
>
> On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
>
> ------------------------------------------------------------------------------
> 10 Tips for Better Web Security
> Learn 10 ways to better secure your business today. Topics covered include:
> Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
> security Microsoft Exchange, secure Instant Messaging, and much more.
> http://www.accelacomm.com/jaw/sfnl/114/51426210/
> _______________________________________________
> QuantLib-dev mailing list
> [hidden email]
> https://lists.sourceforge.net/lists/listinfo/quantlib-dev
>
>

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Luigi Ballabio

Re: Reg. Contributing

Hi all,
nice to see so much interest. Unfortunately you'll have to wait a bit
for me to reply properly, as I'm about to go in vacation for a week
without internet access. Hopefully, when I come back I'll have a few
ideas about what you might do...

Later,
Luigi

On Thu, 2011-07-21 at 07:49 +0100, Grześ Andruszkiewicz wrote:

> Hi Luigi,
>
> I guess I am in similar situation here :) Currently I am a PhD student
> in Mathematical Finance, but previously I have been working as a
> software developer for investment banks.
>
> I would also like to contribute to QuantLib, so that I can get my head
> around the library, learn all the patterns you are using etc.
>
> Grzegorz
>
> On 20 July 2011 21:29, urun dogan <[hidden email]> wrote:
> > Hi Luigi,
> > I am a post-doc doctoral researcher in Germany. My main researc focus is
> > machine learning/artificial intelligence techniques. I am a develor of Shark
> > machine learning library. This library is implemented by C++ . I am really
> > interested in contributing to quant lib because I find find finsnce
> > chalenging and interesting. I am open to implement some machine learning
> > techniques to quant lib also it is absolutelly ok for me to implement other
> > things. Is there any todo list? Are there any ideas for starting?
> >
> > Thanks a lot for your help.
> >
> > Best regards
> > Ueruen Dogan
> >
> > On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
> >
> > ------------------------------------------------------------------------------
> > 10 Tips for Better Web Security
> > Learn 10 ways to better secure your business today. Topics covered include:
> > Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
> > security Microsoft Exchange, secure Instant Messaging, and much more.
> > http://www.accelacomm.com/jaw/sfnl/114/51426210/
> > _______________________________________________
> > QuantLib-dev mailing list
> > [hidden email]
> > https://lists.sourceforge.net/lists/listinfo/quantlib-dev
> >
> >

--

Debugging is twice as hard as writing the code in the first place.
Therefore, if you write the code as cleverly as possible, you are,
by definition, not smart enough to debug it.
-- Brian W. Kernighan

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improve internal communications as well as offer faster, more efficient ways
to interact with customers and streamline customer service. Learn more!
http://www.accelacomm.com/jaw/sfnl/114/51426253/
_______________________________________________
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Kim Kuen Tang

Re: Reg. Contributing

In reply to this post by urun dogan

Hi urun,

Am 20.07.2011 22:29, schrieb urun dogan:

Hi Luigi,
I am a post-doc doctoral researcher in Germany. My main researc focus is machine learning/artificial intelligence techniques. I am a develor of Shark machine learning library.

Just my 2 cent.
Since you are involved in the development of the shark machine you definitely know how to use machine learning to classify and to predict observations. If this is the case you should try to get involved into designing and implementing (alpha-) strategies for trading and backtesting.

Regards,
Kim

This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?

Thanks a lot for your help.

Best regards
Ueruen Dogan

On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
------------------------------------------------------------------------------
10 Tips for Better Web Security
Learn 10 ways to better secure your business today. Topics covered include:
Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
security Microsoft Exchange, secure Instant Messaging, and much more.
http://www.accelacomm.com/jaw/sfnl/114/51426210/
_______________________________________________
QuantLib-dev mailing list
[hidden email]
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urun dogan

Re: Reg. Contributing

Hi Kim,

Hi urun,

Am 20.07.2011 22:29, schrieb urun dogan:

Hi Luigi,
I am a post-doc doctoral researcher in Germany. My main researc focus is machine learning/artificial intelligence techniques. I am a develor of Shark machine learning library.

Just my 2 cent.
Since you are involved in the development of the shark machine you definitely know how to use machine learning to classify and to predict observations. If this is the case you should try to get involved into designing and implementing (alpha-) strategies for trading and backtesting.

I have significant amount of knowledge on classification, regression and model selection techniques. I made a small research on " (alpha-) strategies for trading and backtesting" . They are quite interesting. Is there a group implementin these techniques in quant-lib? If yes where can I found contact details of members? If no, should I start by my own?

Best regards
Ürün

This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?

Thanks a lot for your help.

Best regards
Ueruen Dogan

On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
------------------------------------------------------------------------------
10 Tips for Better Web Security
Learn 10 ways to better secure your business today. Topics covered include:
Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
security Microsoft Exchange, secure Instant Messaging, and much more.
http://www.accelacomm.com/jaw/sfnl/114/51426210/
_______________________________________________
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[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-dev

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Dirk Eddelbuettel

Re: Reg. Contributing

On 27 July 2011 at 01:20, urun dogan wrote:
|
|
| Hi Kim,
|
|
| Hi urun,
|
| Am 20.07.2011 22:29, schrieb urun dogan:
|
|
| Hi Luigi,
| I am a post-doc doctoral researcher in Germany. My main researc focus
| is machine learning/artificial intelligence techniques. I am a develor
| of Shark machine learning library.
|
| Just my 2 cent.
| Since you are involved in the development of the shark machine you
| definitely know how to use machine learning to classify and to predict
| observations. If this is the case you should try to get involved into
| designing and implementing (alpha-) strategies for trading and backtesting.
|
|
| I have significant amount of knowledge on classification, regression and model
| selection techniques. I made a small research on " (alpha-) strategies for
| trading and backtesting" . They are quite interesting. Is there a group
| implementin these techniques in quant-lib? If yes where can I found contact
| details of members? If no, should I start by my own?

Are you familiar with R ?

I wrapped parts of QuantLib into RQuantLib a long time ago, extended it a
little more during Google Summer of Code with one student, and am still
maintaining RQuantLib. It could always do with more contributions. We now
have much nicer interfaces from R to/from C++ using a package Rcpp which grew
out of the initial RQuantLib work. (And it even uses some Boost.Python alike
magic for easy wrapping, though that is not ready for inheritance and all
that). But I tend to spend so much time with Rcpp and related packages that
I never get back to RQuantLib...

R may be a more suitable environment for classification, regression, model
selections, ... all the way to machine learning. And yes, there is even
interest in Shark which a friend started to wrap for R -- but then that
stopped when the Shark team told us that they were in the middle of a
rewrite.

Anyway, just a thought for your consideration.

Cheers, Dirk

|
| Best regards
| � rün
|
|
|
|
|
|
| This library is implemented by C++ . I am really interested in
| contributing to quant lib because I find find finsnce chalenging and
| interesting. I am open to implement some machine learning techniques to
| quant lib also it is absolutelly ok for me to implement other things.
| Is there any todo list? Are there any ideas for starting?
|
| Thanks a lot for your help.
|
| Best regards
| Ueruen Dogan
|
| On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]>
| wrote:
|
| ------------------------------------------------------------------------------
| 10 Tips for Better Web Security
| Learn 10 ways to better secure your business today. Topics covered include:
| Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
| security Microsoft Exchange, secure Instant Messaging, and much more.
| http://www.accelacomm.com/jaw/sfnl/114/51426210/
|
| _______________________________________________
| QuantLib-dev mailing list
| [hidden email]
| https://lists.sourceforge.net/lists/listinfo/quantlib-dev
|
|
|
|
|
| ----------------------------------------------------------------------
| ------------------------------------------------------------------------------
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| Take our quick survey online. Come on, we don't ask for help often.
| Plus, you'll get a chance to win $100 to spend on ThinkGeek.
| http://p.sf.net/sfu/slashdot-survey
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| [hidden email]
| https://lists.sourceforge.net/lists/listinfo/quantlib-dev

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Kim Kuen Tang

Re: Reg. Contributing

In reply to this post by urun dogan

Hi Kim,

Hi urun,

Am 20.07.2011 22:29, schrieb urun dogan:

Hi Luigi,
I am a post-doc doctoral researcher in Germany. My main researc focus is machine learning/artificial intelligence techniques. I am a develor of Shark machine learning library.

Just my 2 cent.
Since you are involved in the development of the shark machine you definitely know how to use machine learning to classify and to predict observations. If this is the case you should try to get involved into designing and implementing (alpha-) strategies for trading and backtesting.

I have significant amount of knowledge on classification, regression and model selection techniques. I made a small research on " (alpha-) strategies for trading and backtesting" . They are quite interesting. Is there a group implementin these techniques in quant-lib?

Difficult to say. As far as i know there is nobody planing to implement a backtesting framework in quantlib.

If yes where can I found contact details of members?

If no, should I start by my own?

Hmmm, i remember seeing a webinar from mathwork showing how to use a neural network for risk controlling energy trading.
Perhaps you can try to implement a neural network in ql and use this tool to forecast energy prices.
Just a suggestion.

Best regards
Ürün
This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?

Thanks a lot for your help.

Best regards
Ueruen Dogan

On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
------------------------------------------------------------------------------
10 Tips for Better Web Security
Learn 10 ways to better secure your business today. Topics covered include:
Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
security Microsoft Exchange, secure Instant Messaging, and much more.
http://www.accelacomm.com/jaw/sfnl/114/51426210/
_______________________________________________
QuantLib-dev mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-dev

urun dogan

Re: Reg. Contributing

Dear All;

Hi Kim,

Hi urun,

Am 20.07.2011 22:29, schrieb urun dogan:

Hi Luigi,
I am a post-doc doctoral researcher in Germany. My main researc focus is machine learning/artificial intelligence techniques. I am a develor of Shark machine learning library.

Just my 2 cent.
Since you are involved in the development of the shark machine you definitely know how to use machine learning to classify and to predict observations. If this is the case you should try to get involved into designing and implementing (alpha-) strategies for trading and backtesting.

I have significant amount of knowledge on classification, regression and model selection techniques. I made a small research on " (alpha-) strategies for trading and backtesting" . They are quite interesting. Is there a group implementin these techniques in quant-lib?

Difficult to say. As far as i know there is nobody planing to implement a backtesting framework in quantlib.

If yes where can I found contact details of members?

If no, should I start by my own?

Hmmm, i remember seeing a webinar from mathwork showing how to use a neural network for risk controlling energy trading.
Perhaps you can try to implement a neural network in ql and use this tool to forecast energy prices.
Just a suggestion.

I have implemented several feedforward neural network methods, recurrent neural network methods, support vector machines and so on. I think this line of implmentation can be beneficial to some people.
I am reading some documents/papers about algorithmic trading and I think these methods can be also used in algorithmic trading. To put such kind of methods in quantlib is very interesting for me.
I have three questions. First one is: Where can I find some data like energy trading data or finance data? The second one is ehich methods are the state of art nethods for this kind of tasks? The third one is
which methods have more priority than others? I mean what are the industry requirement? Does quantitative developers/analysers/traders need very fast and accurate methods, e.g. Neural networks, conventional
linear regression methods or accurate but slow methods e.g SVMs, Gaussian Process?

Best regards
Urun

This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?

Thanks a lot for your help.

Best regards
Ueruen Dogan

On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
------------------------------------------------------------------------------
10 Tips for Better Web Security
Learn 10 ways to better secure your business today. Topics covered include:
Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
security Microsoft Exchange, secure Instant Messaging, and much more.
http://www.accelacomm.com/jaw/sfnl/114/51426210/
_______________________________________________
QuantLib-dev mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-dev

Amir Ahmed Ansari-2

Re: Reg. Contributing

I doubt people would be willing to leave the trading of billions of dollars to a neural network/SVM whose inputs and outputs they don't fully understand. Then again, the way people in the investment management industry blindly rely on tools would suggest people can do anything :) It would be great to get some insight from an actual practitioner.

From: urun dogan <[hidden email]>
To: Kim Kuen Tang <[hidden email]>
Cc: [hidden email]; [hidden email]
Sent: Friday, July 29, 2011 6:57 PM
Subject: Re: [Quantlib-dev] Reg. Contributing

Dear All;

Hi Kim,

Hi urun,

Am 20.07.2011 22:29, schrieb urun dogan:

Hi Luigi,
I am a post-doc doctoral researcher in Germany. My main researc focus is machine learning/artificial intelligence techniques. I am a develor of Shark machine learning library.

Just my 2 cent.
Since you are involved in the development of the shark machine you definitely know how to use machine learning to classify and to predict observations. If this is the case you should try to get involved into designing and implementing (alpha-) strategies for trading and backtesting.

I have significant amount of knowledge on classification, regression and model selection techniques. I made a small research on " (alpha-) strategies for trading and backtesting" . They are quite interesting. Is there a group implementin these techniques in quant-lib?

Difficult to say. As far as i know there is nobody planing to implement a backtesting framework in quantlib.

If yes where can I found contact details of members?

If no, should I start by my own?

Hmmm, i remember seeing a webinar from mathwork showing how to use a neural network for risk controlling energy trading.
Perhaps you can try to implement a neural network in ql and use this tool to forecast energy prices.
Just a suggestion.

This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?

Thanks a lot for your help.

Best regards
Ueruen Dogan

On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
------------------------------------------------------------------------------
10 Tips for Better Web Security
Learn 10 ways to better secure your business today. Topics covered include:
Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
security Microsoft Exchange, secure Instant Messaging, and much more.
http://www.accelacomm.com/jaw/sfnl/114/51426210/
_______________________________________________
QuantLib-dev mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-dev

urun dogan

Re: Reg. Contributing

These are very good points. Actually recently I heard many machine learning researchers who were hired from finance industry. I do not know what are they doing in jobs. Although I know that in algoritmic trading people use some machine learning techniques I have also similar serious concerns that are pointed in the previous e-mail. As said before it would be really great if some practitoners share their experience and opinions.

Best regards
Urun

On 29 Jul 2011 16:30, "Amir Ahmed Ansari" <[hidden email]> wrote:
> I doubt people would be willing to leave the trading of billions of dollars to a neural network/SVM whose inputs and outputs they don't fully understand. Then again, the way people in the investment management industry blindly rely on tools would suggest people can do anything :) It would be great to get some insight from an actual practitioner.
>
>
> From: urun dogan <[hidden email]>
> To: Kim Kuen Tang <[hidden email]>
> Cc: [hidden email]; [hidden email]
> Sent: Friday, July 29, 2011 6:57 PM

> Subject: Re: [Quantlib-dev] Reg. Contributing
>
>
> Dear All;
>
>
>
>>
>>>
>>>
>>>Hi Kim,

>>>
>>>
>>>>
>>>>Hi urun,
>>>>
>>>>Am 20.07.2011 22:29, schrieb urun dogan:
>>>>Hi Luigi,
>>>>>I am a post-doc doctoral researcher in Germany. My
> main researc focus is machine learning/artificial
> intelligence techniques. I am a develor of Shark
> machine learning library.
> Just my 2 cent.
>>>>Since you are involved in the development of the shark
> machine you definitely know how to use machine learning to
> classify and to predict observations. If this is the case
> you should try to get involved into designing and
> implementing (alpha-) strategies for trading and
> backtesting.
>>>>
>>>
>>>I have significant amount of knowledge on classification,
> regression and model selection techniques. I made a small
> research on " (alpha-) strategies for trading and backtesting"
> . They are quite interesting. Is there a group implementin
> these techniques in quant-lib?
> Difficult to say. As far as i know there is nobody planing to implement a backtesting framework in quantlib.
>>
>>If yes where can I found contact details of members?
>>If no, should I start by my own?
>>>
> Hmmm, i remember seeing a webinar from mathwork showing how to use a neural network for risk controlling energy trading.
>>Perhaps you can try to implement a neural network in ql and use this
> tool to forecast energy prices.
>>Just a suggestion.
>>
>
> I have implemented several feedforward neural network methods, recurrent neural network methods, support vector machines and so on. I think this line of implmentation can be beneficial to some people.
> I am reading some documents/papers about algorithmic trading and I think these methods can be also used in algorithmic trading. To put such kind of methods in quantlib is very interesting for me.
> I have three questions. First one is: Where can I find some data like energy trading data or finance data? The second one is ehich methods are the state of art nethods for this kind of tasks? The third one is
> which methods have more priority than others? I mean what are the industry requirement? Does quantitative developers/analysers/traders need very fast and accurate methods, e.g. Neural networks, conventional
> linear regression methods or accurate but slow methods e.g SVMs, Gaussian Process?
>
> Best regards
> Urun
>
>
>
>>>>
>>>>
>>>>
>>>>This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?
>>>>>Thanks a lot for your help.
>>>>>Best regards
>>>>>Ueruen Dogan
>>>>>On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
>>>>>
>>>>>
> ------------------------------------------------------------------------------
> 10 Tips for Better Web Security
> Learn 10 ways to better secure your business today. Topics covered include:
> Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
> security Microsoft Exchange, secure Instant Messaging, and much more. http://www.accelacomm.com/jaw/sfnl/114/51426210/
>>>>>
> _______________________________________________
> QuantLib-dev mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-dev
>>>>
>>>
>>
>
> ------------------------------------------------------------------------------
> Got Input? Slashdot Needs You.
> Take our quick survey online. Come on, we don't ask for help often.
> Plus, you'll get a chance to win $100 to spend on ThinkGeek.
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Amir Ahmed Ansari-2

Re: Reg. Contributing

While we wait for the practitioners, let us try and hypothesize what exactly someone would be looking for in an algorithmic trading system. I happened to read a news story some weeks back and it talked about how someone created their own hedge fund company. This guy is a real game changer in the algorithmic trading space and one of his key insights was that market momentum tends to have a certain inertia. So, this tells us that one of the jobs an ATS (algorithmiic trading system) would do is look for momentum. Another off the top of the hat requirement is looking for arbitrage opportunities. These are particularly relevant for commodities and foreign exchange. Does this give anyone more ideas???

From: urun dogan <[hidden email]>
To: Amir Ahmed Ansari <[hidden email]>
Cc: Kim Kuen Tang <[hidden email]>; "[hidden email]" <[hidden email]>; "[hidden email]" <[hidden email]>
Sent: Friday, July 29, 2011 7:54 PM
Subject: Re: [Quantlib-dev] Reg. Contributing

Best regards
Urun

> Subject: Re: [Quantlib-dev] Reg. Contributing
>
>
> Dear All;
>
>
>
>>
>>>
>>>
>>>Hi Kim,

urun dogan

Re: Reg. Contributing

Note: All following comments may be wrong. I have a very limited and basic knowledge of finance. I find these topics really interesting and I want to contribute quantlib.But firstly, I want to know whether my very basic understanding is right or wrong.

I am open to any comment even if they are harsh because improving my understanding and skills is very important for me.I will appreciate your help very much.

So here are my questions and comments

I did not get what this momentum means exactly? I have only one guess that is If a a value of "something" is increasing, it will increase some more time and vice versa. If this is the case I will consider as a memory effect. Because many of the stochastic models assume that markets are markovnian but in reality theyare not. The reason that many people are making this assumption is simple to analyse and it is computationally feasible to make this kind of simulation studies.

About arbitrage opportunities: I know that ATS systems deal with such cases and indeed they are succesfull but this means we have a high frequency data. Also we need to analyse data which contains some delay. Imagine Japaneye yen - US dollar relation.

On Fri, Jul 29, 2011 at 5:17 PM, Amir Ahmed Ansari <[hidden email]> wrote:

While we wait for the practitioners, let us try and hypothesize what exactly someone would be looking for in an algorithmic trading system. I happened to read a news story some weeks back and it talked about how someone created their own hedge fund company. This guy is a real game changer in the algorithmic trading space and one of his key insights was that market momentum tends to have a certain inertia. So, this tells us that one of the jobs an ATS (algorithmiic trading system) would do is look for momentum. Another off the top of the hat requirement is looking for arbitrage opportunities. These are particularly relevant for commodities and foreign exchange. Does this give anyone more ideas???

From: urun dogan <[hidden email]>
To: Amir Ahmed Ansari <[hidden email]>
Cc: Kim Kuen Tang <[hidden email]>; "[hidden email]" <[hidden email]>; "[hidden email]" <[hidden email]>
Sent: Friday, July 29, 2011 7:54 PM

Subject: Re: [Quantlib-dev] Reg. Contributing

These are very good points. Actually recently I heard many machine learning researchers who were hired from finance industry. I do not know what are they doing in jobs. Although I know that in algoritmic trading people use some machine learning techniques I have also similar serious concerns that are pointed in the previous e-mail. As said before it would be really great if some practitoners share their experience and opinions.

Best regards
Urun

On 29 Jul 2011 16:30, "Amir Ahmed Ansari" <[hidden email]> wrote:
> I doubt people would be willing to leave the trading of billions of dollars to a neural network/SVM whose inputs and outputs they don't fully understand. Then again, the way people in the investment management industry blindly rely on tools would suggest people can do anything :) It would be great to get some insight from an actual practitioner.
>
>
> From: urun dogan <[hidden email]>
> To: Kim Kuen Tang <[hidden email]>
> Cc: [hidden email]; [hidden email]
> Sent: Friday, July 29, 2011 6:57 PM

> Subject: Re: [Quantlib-dev] Reg. Contributing
>
>
> Dear All;
>
>
>
>>
>>>
>>>
>>>Hi Kim,
>>>
>>>
>>>>
>>>>Hi urun,
>>>>
>>>>Am 20.07.2011 22:29, schrieb urun dogan:
>>>>Hi Luigi,
>>>>>I am a post-doc doctoral researcher in Germany. My
> main researc focus is machine learning/artificial
> intelligence techniques. I am a develor of Shark
> machine learning library.
> Just my 2 cent.
>>>>Since you are involved in the development of the shark
> machine you definitely know how to use machine learning to
> classify and to predict observations. If this is the case
> you should try to get involved into designing and
> implementing (alpha-) strategies for trading and
> backtesting.
>>>>
>>>
>>>I have significant amount of knowledge on classification,
> regression and model selection techniques. I made a small
> research on " (alpha-) strategies for trading and backtesting"
> . They are quite interesting. Is there a group implementin
> these techniques in quant-lib?
> Difficult to say. As far as i know there is nobody planing to implement a backtesting framework in quantlib.
>>
>>If yes where can I found contact details of members?
>>If no, should I start by my own?
>>>
> Hmmm, i remember seeing a webinar from mathwork showing how to use a neural network for risk controlling energy trading.
>>Perhaps you can try to implement a neural network in ql and use this
> tool to forecast energy prices.
>>Just a suggestion.
>>
>
> I have implemented several feedforward neural network methods, recurrent neural network methods, support vector machines and so on. I think this line of implmentation can be beneficial to some people.
> I am reading some documents/papers about algorithmic trading and I think these methods can be also used in algorithmic trading. To put such kind of methods in quantlib is very interesting for me.
> I have three questions. First one is: Where can I find some data like energy trading data or finance data? The second one is ehich methods are the state of art nethods for this kind of tasks? The third one is
> which methods have more priority than others? I mean what are the industry requirement? Does quantitative developers/analysers/traders need very fast and accurate methods, e.g. Neural networks, conventional
> linear regression methods or accurate but slow methods e.g SVMs, Gaussian Process?
>
> Best regards
> Urun
>
>
>
>>>>
>>>>
>>>>
>>>>This library is implemented by C++ . I am really interested in contributing to quant lib because I find find finsnce chalenging and interesting. I am open to implement some machine learning techniques to quant lib also it is absolutelly ok for me to implement other things. Is there any todo list? Are there any ideas for starting?
>>>>>Thanks a lot for your help.
>>>>>Best regards
>>>>>Ueruen Dogan
>>>>>On 18 Jul 2011 13:40, "Luigi Ballabio" <[hidden email]> wrote:
>>>>>
>>>>>
> ------------------------------------------------------------------------------
> 10 Tips for Better Web Security
> Learn 10 ways to better secure your business today. Topics covered include:
> Web security, SSL, hacker attacks & Denial of Service (DoS), private keys,
> security Microsoft Exchange, secure Instant Messaging, and much more. http://www.accelacomm.com/jaw/sfnl/114/51426210/
>>>>>
> _______________________________________________
> QuantLib-dev mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-dev
>>>>
>>>
>>
>
> ------------------------------------------------------------------------------
> Got Input? Slashdot Needs You.
> Take our quick survey online. Come on, we don't ask for help often.
> Plus, you'll get a chance to win $100 to spend on ThinkGeek.
> http://p.sf.net/sfu/slashdot-survey
> _______________________________________________
> QuantLib-dev mailing list
> [hidden email]
> https://lists.sourceforge.net/lists/listinfo/quantlib-dev