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Today's Topics:
1. Re: Black Vega (Luigi Ballabio)
2. Re: Black Vega (Luigi Ballabio)
3. Re: thread safe session handling via TSS (Riccardo Ghetta)
4. [ quantlib-Patches-3582579 ] Differential Evolution
improvement (SourceForge.net)
----------------------------------------------------------------------
Message: 1
Date: Mon, 26 Nov 2012 16:39:44 +0100
From: Luigi Ballabio <[hidden email]>
Subject: Re: [Quantlib-dev] Black Vega
To: Peter Caspers <[hidden email]>
Cc: "[hidden email]"
<[hidden email]>
Message-ID:
<[hidden email]>
Content-Type: text/plain; charset=ISO-8859-1
Yes, you're correct. I'll fix it.
Luigi
On Mon, Nov 12, 2012 at 11:49 AM, Peter Caspers <[hidden email]> wrote:
> Hi,
>
> in blackformula.cpp , blackFormulaStdDevDerivative(...) the limit case
> stdDev == 0.0 seems to be treated false, lines 307ff
>
> if (stdDev==0.0) {
> if (forward>strike)
> return discount * forward;
> else
> return 0.0;
> }
>
> should be
>
> if (stdDev==0.0) return 0.0;
>
> because \phi(x) -> 0 whenever |x| -> \infty, right ?
>
> Thanks
> Peter
>
>
> ------------------------------------------------------------------------------
> Everyone hates slow websites. So do we.
> Make your web apps faster with AppDynamics
> Download AppDynamics Lite for free today:
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> https://lists.sourceforge.net/lists/listinfo/quantlib-dev
>
------------------------------
Message: 2
Date: Mon, 26 Nov 2012 17:59:06 +0100
From: Luigi Ballabio <[hidden email]>
Subject: Re: [Quantlib-dev] Black Vega
To: Peter Caspers <[hidden email]>
Cc: "[hidden email]"
<[hidden email]>
Message-ID:
<CAJkxnzcCc4NfhELqv9XHxVQo2Bgu1PoHCW+_9BMuhJ=pLJz=[hidden email]>
Content-Type: text/plain; charset=ISO-8859-1
Fixed, thanks.
Luigi
On Mon, Nov 26, 2012 at 4:39 PM, Luigi Ballabio
<[hidden email]> wrote:
> Yes, you're correct. I'll fix it.
>
> Luigi
>
>
> On Mon, Nov 12, 2012 at 11:49 AM, Peter Caspers <[hidden email]>
wrote:
>> Hi,
>>
>> in blackformula.cpp , blackFormulaStdDevDerivative(...) the limit case
>> stdDev == 0.0 seems to be treated false, lines 307ff
>>
>> if (stdDev==0.0) {
>> if (forward>strike)
>> return discount * forward;
>> else
>> return 0.0;
>> }
>>
>> should be
>>
>> if (stdDev==0.0) return 0.0;
>>
>> because \phi(x) -> 0 whenever |x| -> \infty, right ?
>>
>> Thanks
>> Peter
>>
>>
>> ------------------------------------------------------------------------------
>> Everyone hates slow websites. So do we.
>> Make your web apps faster with AppDynamics
>> Download AppDynamics Lite for free today:
>> http://p.sf.net/sfu/appdyn_d2d_nov
>> _______________________________________________
>> QuantLib-dev mailing list
>> [hidden email]
>> https://lists.sourceforge.net/lists/listinfo/quantlib-dev
>>
------------------------------
Message: 3
Date: Mon, 26 Nov 2012 18:07:13 +0100
From: Riccardo Ghetta <[hidden email]>
Subject: Re: [Quantlib-dev] thread safe session handling via TSS
To: Luigi Ballabio <[hidden email]>
Cc: Ferdinando Ametrano <[hidden email]>,
"[hidden email]"
<[hidden email]>
Message-ID: <[hidden email]>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Well, Singleton returns an instance ... perhaps we could mix the two
solutions at this level ...
What about changing a little the default ?
Instead of defaulting to a single session per application, default to a
single session per thread (via TSS).
When the user registers a sessionId function (via setSessionIdFunc),
switch to lock+map.
If you want, I'll try to concoct an implementation along these lines.
I am a bit uncomfortable, however, with a sessionId-based solution.
IMO is inherently fragile: one must ensure than no one will modify the
same session from different threads.
So the application must be single-threaded, or use some other method to
avoid trashing the singletons.
This even when Singleton is using locks, as in Mortoray implementation.
A lock in this case protects only the mapping id-singleton, not the
singleton data.
Consider this example, with a default sessionId(), i.e. one returning
always 0:
thread 1 calls
Settings::instance().evaluationDate()= Date(1, Jan, 2012);
meanwhile thread 2 calls
Settings::instance().evaluationDate()= Date(15, Jan, 2012);
Settings::instance() can be accessed by one thread at time, but
afterward both threads have a reference to the same instance, so no one
knows really what value will have the evaluation date.
To avoid this race you have to lock the entire sequence, or associate a
session to a single thread, perhaps via thread storage :).
Riccardo
-------- Original Message --------
Subject: Re: [Quantlib-dev] thread safe session handling via TSS
From: Luigi Ballabio <[hidden email]>
To: Riccardo Ghetta <[hidden email]>
CC: "[hidden email]"
<[hidden email]>, Ferdinando Ametrano
<[hidden email]>
Date: Monday, November 26, 2012 16:21:14
> It might be reasonable. But as mortoray argued, one might want to
> switch between the two possibilities without recompiling; especially
> those that don't compile the library and get it packaged from a Linux
> distribution. If we provide such a switch, linking libboost_thread
> would be required anyway. What do you think?
>
> A future possibility would be to rework mortoray's patch so that the
> pluggable function returns the instance directly instead of an integer
> id; in such an implementation, your technique would just provide a
> particular function. However, that's not backward compatible...
>
> Luigi
>
>
> On Tue, Oct 23, 2012 at 3:43 PM, Riccardo Ghetta <[hidden email]> wrote:
>> Not directly, no.
>> I've looked at mortoray patch. Unfortunately that scheme is not compatible
>> with thread storage; having a per-thread instance makes all the
>> sessionId/sessionIdFunc machinery useless. In a way, is implicitly handled.
>> Likewise for the instances_ map.
>>
>> On the other hand, perhaps I can rework the tss patch to avoid including
>> boost thread headers in singleton.hpp, if we don't want to force quantlib
>> users to compile with boost:thread.
>> That should preserve the main qualities of the above patch, i.e. being
>> thread-safe and not requiring libboost_thread, plus the added safety,
>> simplicity and performance of tss.
>>
>> it might be a reasonable solution ?
>> Ciao,
>>
>> R
>>
>>
>> -------- Original Message --------
>> Subject: Re: [Quantlib-dev] thread safe session handling via TSS
>> From: Luigi Ballabio <[hidden email]>
>> To: Riccardo Ghetta <[hidden email]>
>> CC: [hidden email], Ferdinando Ametrano
>> <[hidden email]>
>> Date: Tuesday, October 23, 2012 12:10:59
>>> Riccardo,
>>>
>>> I just had a look at your patch. Is there any chance that it can
>>> be made to work together with the pending patch at
>>>
>>> <https://github.com/mortoray/quantlib/commit/dbf6b23429b21cccb0982d6f3e5c13f5860842e1>?
>>> (Yes, we have stuff all over the place and it's not easy to find it.
>>> Our bad.)
>>>
>>> About the contributor agreement: in the past we used something like
>>> the document I'm attaching. You can scan the signed document and send
>>> it to me and Ferdinando (whose address is in cc).
>>>
>>> Thanks,
>>> Luigi
>>>
>>>
>>> On Fri, Oct 19, 2012 at 3:22 PM, Riccardo Ghetta <[hidden email]> wrote:
>>>> Hi,
>>>> I've just posted a patch to enable thread safe session handling. It
>>>> should also solve bug 3441748.
>>>> The company I work for, Thema Consulting SA (www.themaconsulting.ch),
>>>> uses QuantLib in its MasterFinance product and has other patches we like
>>>> to contribute back (as soon they're cleared by management/legal).
>>>>
>>>> BTW, is the contributor agreement needed ? Where should be sent ?
>>>> I searched the mailing list, but without luck.
>>>>
>>>> Ciao,
>>>> Riccardo Ghetta
>>>> Thema Consulting SA
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Everyone hates slow websites. So do we.
>>>> Make your web apps faster with AppDynamics
>>>> Download AppDynamics Lite for free today:
>>>> http://p.sf.net/sfu/appdyn_sfd2d_oct
>>>> _______________________________________________
>>>> QuantLib-dev mailing list
>>>> [hidden email]
>>>> https://lists.sourceforge.net/lists/listinfo/quantlib-dev
>>
------------------------------
Message: 4
Date: Mon, 26 Nov 2012 14:13:54 -0800
From: SourceForge.net <[hidden email]>
Subject: [Quantlib-dev] [ quantlib-Patches-3582579 ] Differential
Evolution improvement
To: SourceForge.net <[hidden email]>
Message-ID:
<[hidden email]>
Content-Type: text/plain; charset=UTF-8
Patches item #3582579, was opened at 2012-11-01 15:38
Message generated for change (Comment added) made by fenixcitizen
You can respond by visiting:
https://sourceforge.net/tracker/?func=detail&atid=312740&aid=3582579&group_id=12740
Please note that this message will contain a full copy of the comment thread,
including the initial issue submission, for this request,
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Category: None
Group: None
Status: Closed
Resolution: Accepted
Priority: 5
Private: No
Submitted By: Mateusz Kapturski (fenixcitizen)
Assigned to: Luigi Ballabio (lballabio)
Summary: Differential Evolution improvement
Initial Comment:
Hi All,
I have come across the new implementation of Differential Evolution that
appeared in QuantLib HEAD source code recently. I decided to improve it
slightly. I took performance very seriously as the DE implementation should be
light in order to avoid unnecessary time overhead.
The most significant change is that I use DiffEvolConfiguration object that
defines the behavior of the algorithm. The reason is that it makes the
implementation more flexible. There are dozens of DE variants... I tried to be
in line with current QuantLib optimization interface.
Important changes:
1) DE Optimizer consumes configuration object that defines its behavior - as I
mentioned, the number of variations of the DE algorithm is huge. This approach
makes it possible to extend the implementations in the future.
2) Constraints that define search space are not the part of the algorithm itself
- this is why additional upperBound and lowerBound functions were added to
Constraint object. NonhomogeneousBoundaryConstraint to define box constraints
was added too. The other aspect is if the bounds are going to be valid for
emerging populations - practical advise is that it should as for certain
parameters, new populations seem to diverge. On the other hand, it adds some
additional overhead. General observation is that it is always possible to
improve performance for a given objective function. One needs to find
appropriate DE configuration only.
3) I added three different crossover types: normal, binomial and exponential
(the name for the first crossover type comes from the fact that assuming
binomial crossover, the number of mutants taken into account in a given
population converges in distribution to normal variable for growing problem
size)
4) There are 6 methods available in this implementation. However, it is possible
to go further and implement various base element types, differences of a given
size, various weights distributions for the differences etc. Implemented
approaches are the most common used in practice as the more complicated
recombination procedure, the higher computation cost is.
5) For ModFourthDeJong objective function as I was able to find a point for
which the objective function value is 8.86549 which is significantly lower than
12.3724219287 :
DE type: bestMemberWithJitter
Crossover type: normal
Apply Bounds: true
CrossoverProb: 0.25
NumOfPopulationMembers: 500
PrintFullInfo: false
StepsizeWeight: 0.2
MaxIterations
Point: [ 0.299015; 0.352861; -0.0306954; -0.349516; 0.202407; 0.111475;
0.0783742; -0.0640798; 0.284987; -0.00386122; 0.134481; -0.174184; -0.0188605;
0.217705; 0.0557937; 0.176954; -0.0757169; 0.219995; -0.079788; -0.142831;
-0.129607; 0.135615; -0.152286; 0.0420379; -0.193061; 0.0582583; -0.0617313;
-0.238126; -0.11224; -0.069721 ]
Objective function value: 8.86549
However, this is the best result only. Usually, the algorithm was stuck in
several local minimas - most of them in [10;15] range. Further investigation is
needed.
6) I have problem with Griewangk function too. I am not able to find fully
successful method although the objective function value oscillated around 0.1
which is not bad. It needs to be verified.
I find the bestMemberWithJitter method the most successful and this is the only
reason I set it as default method to be used. Hope it helps. I am happy to
answer your questions. In case my patch does not work properly, please use
changed files directly.
Kind regards,
Mateusz Kapturski
----------------------------------------------------------------------
Comment By: Mateusz Kapturski (fenixcitizen)
Date: 2012-11-26 14:13
Message:
Hi Luigi,
thank you for your amendments. The logic has not changed and it works for
me. All tests passed.
However, I had to change Makefile.am file in ql/math/optimisation directory
and put -std=c++0x flag as you used Initializer list (feature from c++11).
I compile QL using gcc. I wonder, if other users may experience similar
problems. Is there a simple way to use this flag in the whole project? I
tried to compile it using VS2010 and VS2012 but both failed (initializer
lists are still missing in VS).
Regards,
Mateusz
----------------------------------------------------------------------
Comment By: Luigi Ballabio (lballabio)
Date: 2012-11-21 01:26
Message:
Mateusz,
I've added your code to the repository. I've made a few refactorings
to make it more in line with the style we've been using in the library, so
you might want to check that everything still works. In particular:
- I've replaced the use of boost::random with our mersenne-twister
generator;
- I've turned the configuration class into an inner class;
- I've removed setters, which don't play well with observability;
- I've removed pointer data members;
- plus some minor cleanup.
Thanks,
Luigi
----------------------------------------------------------------------
Comment By: https://www.google.com/accounts ()
Date: 2012-11-12 07:24
Message:
Hi Mateusz,
good that the adaptive method seems to add some value to your implemetation
;-)
When I run the test cases, 4 out of 5 pass now. However, for the
ModFourthDeJong objective function, I get 12.0945 instead of your 10.964.
Maybe this is due to the fact that I'm using a different boost version
(1.47.0) and that boost's MT impementation has changed, but I don't know if
it's worth investgating on this issue or rather exclude the ModFourthDeJong
test case for now (because both values are valid).
Ralph
----------------------------------------------------------------------
Comment By: Mateusz Kapturski (fenixcitizen)
Date: 2012-11-11 13:35
Message:
Hi Ralph, Luigi
you were right - self adapting method is quite successful. I have already
added it to my implementation. All tests are passed now. I would be
grateful if you double check my results. I think this is a stable version
that can go to QL trunk. QL users have much more options now.
Recent changes/remarks:
1) Crossover self-adaptation is a separate option - it was very easy to
implement it that way.
2) User can decide if DE should use fixed seed or not (as discussed
earlier)
3) Adaptation is performed on the population member basis as stated in the
paper.
4) Additional rotation was added to the self-adaptive method to improve its
performance.
5) Extracted some logic into separate private methods.
6) Original Griewangk function is usually defined on [-600, 600]^n box and
my DE implementation is successful on this search domain.
----------------------------------------------------------------------
Comment By: https://www.google.com/accounts ()
Date: 2012-11-08 00:23
Message:
Hi Mateusz,
thank you for your reply. The adaptive method can be found here (section
V):
Brest, J. et al., 2006,
"Self-Adapting Control Parameters in Differential Evolution: A Comparative
Study on Numerical Benchmark Problems."
( A link which worked for me is
http://150.214.190.154/docencia/sf1/Brest06.pdf)
And yes, the adaptive method always found the minimum of the Griewanck
function when I played around with it.
Ralph
----------------------------------------------------------------------
Comment By: Mateusz Kapturski (fenixcitizen)
Date: 2012-11-07 14:44
Message:
Hi Ralph,
thank you for your remarks.
1) Fixing the seed for reproducibility is a great idea. I simply forgot to
do it. I tested my implementation against current time as seed to be
perfectly sure that results are reliable. I added an optional config param.
One may want "increase randomness" using the useFixedSeed_=false parameter.
Therefore, both options are available now.
2) This is a philosophical aspect. I used Boost as it was just easier for
me and I find it a reliable tool. It does not add external dependency as QL
already uses Boost libraries. The question is if there is value added if we
change it. In my view - not significant. If you would like to change it,
just go for it.
3) I see your point now with respect to ModFourthDeJong. My random results
were connected with your first observation - after fixing the seed, I
obtained stable minimum equal to 10.409792. I have already amended the test
case.
4) The adaptive method is not implemented yet but it can be easily added.
Could you provide more details on the method as I could not find it in the
literature. The most important aspects are: how many differences are taken
into account and how are weights applied to it? Was crossover important
aspect for this method? And last practical question: Was the adaptive
strategy successful for every chosen seed in your implementation? Griewangk
objective function is probably the last major issue to resolve now.
Thanks
Mateusz
----------------------------------------------------------------------
Comment By: https://www.google.com/accounts ()
Date: 2012-11-07 00:42
Message:
Hi Mateusz,
I have some remarks/questions concerning your DE implementation:
1. You are using time(0) for the seed in the generation of the initial
population (differentialevolution.cpp, line 27). Wouldn't a fix seed be
better for reproducability, in the sense that the same data yield the same
result?
2. As a part of QuantLib, shouldn't one choose QuantLib's random number
generator instead of boost's?
3. For the ModFourthDeJong you mention that you find a lower minimum than
the previous implementation. But that's not the point. If you take a look
at the function, you see the uniform random part, i.e. the functional
minimum is f(0) <= 30*Expectation(uniform) = 15. Therefore you'll get
different realizations for different random numbers, which is ok as long as
the minimum found is below 15.
4. For the Griewangk function, the adaptive method in the current DE
implementation succeeds to find the minimum f(0) = 0. Is the adaptive
method implemented (or implementable) in your code as well?
Thanks,
Ralph
----------------------------------------------------------------------
Comment By: Mateusz Kapturski (fenixcitizen)
Date: 2012-11-06 16:15
Message:
Hi Luigi,
I have a habit of constant auto forrmatting when coding in Eclipse...
Unfortunately, the autoformat profile cannot be adjusted to QL style
easily. I removed unnecessary changes in order to make the patch more
readable.
Mateusz
BTW. Is it possible to use other external tool (e.g. vim or emacs) to
format source code file in line with QL style? First line in each QL file
specifies autoformat options, doesn't it?
----------------------------------------------------------------------
Comment By: Luigi Ballabio (lballabio)
Date: 2012-11-06 00:29
Message:
Mateusz,
thanks for the contribution. However, the patch is made practically
unreadable by the fact that you re-indented the files (for instance, the
Constraint class shows as completely changed, whereas you only actually
added the lowerBound and upperBound methods).
May you reformat the files so that they match the original indentation, and
therefore so that the patch only contains the actual differences? This
might seem picky on my part, and I know I'm asking some work; but on the
one hand, as I said, the patch (and the diffs from version-control, once
your changes get in) would be made more clearly readable, and on the other
hand, having a consistent format in the library sources makes it easier to
see the context.
Thanks,
Luigi
----------------------------------------------------------------------
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