I am new to quantlib, but I have relatively good understanding of C++. To put my question in some sort of context, I can inform you that I am actually trying to implement the portfolio CVA calculation method proposed by Giovanni Cesari (see link below) for a simple portfolio consisting of one interest rate swap (as a starting point).
I working with the Cheyette (quasi-Gaussian) interest rate model. The model has been implemented as a "new" stochastic process class and the simulated paths stored/generated as a multipath class.
However, as Cesari's method is based on LS-Monte Carlo, I need to write a code that can generate the resulting cash flow sequence from an interest rate swap under each scenario. I do not know if there is some efficient way to do this in quantlib, but I have a feeling that there is. I guess one should be able let the scenarios generated, populate Quantlib quotes which are linked to an instance of the quantlib term structures class. Hopefully I can use this together with the swap class in order to obtain the realized cash flows (basically the floating leg, as the fixed leg is deterministic) from the swap.
Any idea of how this can be done will be highly appreciated!
Link to Cesari's presentation (see page 21 to 26): http://sfi.epfl.ch/files/content/sites/sfi/files/shared/Swissquote%20Conference%202010/Cesari_talk.pdf
Related
I'm looking to auto-generate a Bill Of Materials (BOM) in draw.io by using object ID's. This is because my plans contain many of the same or similar components making it difficult to visually count. So, ultimately I'd like to auto-generate a parts list. Firstly is this possible in draw.io? Secondly what would be the best method of execution?
Currently I'm converting my diagram to PDF and then using the find function to count the number of instances of the part number.
A point in the right direction would be most welcome.
Is there a way to output the final tableau in python with docplex library? If not, is there a work around?
I want to use dual simplex method to solve linear programming problem with newly added constraints. So, I would need to access the final tableau to decide which variable to exit the basis, without having to re-solve the problem from scratch.
This sort of low level interaction cannot be done at the docplex level. In order to do this you can use Model.get_cplex() to get a reference to the underlying engine object. With this you can then get additional information. You can find the reference documentation for this class here. You probably want to look at the solution, solution.basis, solution.advanced properties. This should give you all the information you need.
Note that the engine works with an index oriented model in which every variable or constraint is just a number. You can convert docplex variable objects by using Model.get_var_by_index().
I also wonder whether you may want drop docplex and instead directly use the CPLEX Python API. You can find documentation of this here.
I'm a newbie in FFT and I was asked to find a way to analyse/process a particular set of data collected by oil drilling rigs.
There is a lot of noise in the collected data due to rig movements (up & down with tides and waves for example).
I was asked to clean the collected data up with FFT=>filtering=>IFFT.
I use C++ and the FFTW 3.3.3 library.
An example is better than anything else so :
I have a DB with, for example, the mudflow (liters per minutes). The mudflow is collected every 5 seconds, there is a timestamp in the DB for every measure (ex. 1387411235).
So my IN_data for my FFT is a couple of timestamp/mudflow (ex. 1387456630/3955.94, 1387456635/3954.92, etc...)
Displaying theses data really looks like a noisy sound signal and relevant events may be masked by the noise.
Using examples found on the Internet I can manage to perform FFT but my lack of knowledge and understanding is a big problem as I've never worked on signal processing and Fourier Transforms.
I don't really know how to proceed to start with this job, which version of FFTW routine to use (c2c, r2c, etc...), if there is any pre-data-processing and/or post-processing to do.
There are a lot of examples and tutorials that I've read on the internet but I'm french (sorry for my mistakes here) and it doesn't always make sense to me especially with OUT_data units, OUT_data type, In and Out data array size, windowing (what is that by the way), to put it in a nutshell I'm lost...
I suppose that my problem would be pretty straightforward for someone used to FFTW but for me it's very complicated right now.
So my questions :
What FFTW routine to use in both ways (FFT & IFFT) (what kind, type and size, of array for IN_data and OUT_data).
How to interpret the resulting array (what are the units that FFTW will return).
For now a short sample of what I've done is :
fftw_plan p;
p = (fftw_plan)fftw_plan_dft_1d(size,in,out,FFTW_FORWARD,FFTW_ESTIMATE);
fftw_execute(p);
fftw_destroy_plan(p);
with "in" and "out" as fftw_complex (the complex element of my In_data array is set to 1 for every data, don't really know why but the tutorial said to do that).
This code is based on an example found on the Internet but my lack of knowledge/understanding is a big drag and I was wondering if there was someone here who could give me explanations/workflow/insights/links on how to pull this out.
I'm in a trial period for my new job and I really want to implement this feature for my boss even if it means asking around for help, I've seen a lot of FFTW skilled posts here...
This is quite an ambitious project for someone who is completely new to DSP, but you can start by reading about the overlap-add method, which is essentially the method you need for your FFT-filter-IFFT approach to cleaning up this data. You should also check out the DSP StackExchange site dsp.stackexchange.com, where the theoretical background and application of frequency domain filtering is covered in several similar questions/answers.
Problem:
I have two strings, say, "Billie Jean" and "Thriller". I need to programmatically compare them and find how closely they are related. Those are both songs of the same artist, hence, they should give a higher score (probability, percentage etc) than say, "Brad Pitt" and "Jamaican Farewell".
One way of doing this is an open source Java tool named WikipediaMiner which compares using the Wikipedia data dump, checking links, descriptions etc.
Question:
Please suggest a better alternative, that uses any or all of Wikipepdia, DBpedia, Freebase and their cousins, or combines a different approach. I would really prefer open source software that can be downloaded and set up on a server (eg. Apache Mahout), rather than a paid web service.
It's not so much a matter of programming, but of data.
So it's not really a question for StackOverflow.
What you really want is to use WordNet I guess. That is really meant as a database for reasoning about the meaning of words. So for example, the data explicitely states that data mining is a form of data processing. And which is a physical entity...
You see, the reasoning will be only as good as your data is.
DBPedia may also include a mapping from WordNet to Wikipedia maybe?
You can't tell that "Thriller" is a song, not a music video or film genre or Lambchop album without additional context.
After you've identified what your items are, it's "simply" a matter of traversing the graph of connections in Freebase, MusicBrainz, or whatever other information sources you are using.
You'll need to decide how you're going to weight things for scoring though. Are two Michael Jackson songs more closely related because they share the same type or are they more closely related to the artist Michael Jackson because they're directly connect to him?
Because the open source geo-coders cannot begin to compare to Google's or even Yahoo's, I would like to start a project to create a good open source geo-coder. Just to clarify, a geo-coder takes some text (usually with some constraints) and returns one or more lat/lon pairs.
I realize that this is a difficult and garguntuan task, so I am wondering how you might get started. What would you read? What algorithms would you familiarize yourself with? What code would you review?
And also, assuming you were going to develop this very agilely, what would you want the first prototype to be able to do?
EDIT: Let's set aside the data question for now. I am going to use OpenStreetMap data, along with a database of waypoints that I have. I would later plan to include other data sets as well, and I realize the geo-coder would be inherently limited by the quality of the original data.
The first (and probably blocking) problem would be: where do you get your data from? (unless you are willing to pay thousands of dollars for proprietary sets).
You could build a geocoding-api on top of OpenStreetMap (they publish their data in dumps on a regular basis) I guess, but that one was still very incomplete last time I checked.
Algorithms are easy. Good mapping data, however, is expensive. Very expensive.
Google drove their cars all over the world, collecting this data among other things.
From a .NET point of view these articles might be interesting for you:
Writing Your Own GPS Applications: Part I
Writing Your Own GPS Applications: Part 2
Writing GIS and Mapping Software for .NET
I've only glanced at the articles but they've been on CodeProject's 'Most Popular' list for a long time.
And maybe this CodePlex project which the author of the articles above made available.
I would start at the absolute beginning by figuring out how you're going to get the data that matches a street address with a geocode. Either Google had people going around with GPS units, OR they got the information from some existing source. That existing source may have been... (all guesses)
The Postal Service
Some existing maps(printed)
A bunch of enthusiastic users that were early adopters of GPS technology who ere more than willing to enter in street addresses and GPS coordinates
Some government entity (or entities)
Their own satellites
etc
I guess what I'm getting at is the information was either imported from somewhere or was input by someone via some interface. As my starting point I would look at how to get that information. In an open source situation, you may be able to get a bunch of enthusiastic people to enter information.
So for my first prototype, boring as it would be, I would create a form for entering information.
Then you need to know the math for figuring out the closest distance (as the crow flies). From there, try to figure out how to include roads. (My guess is you would have to have data point for each and every curve, where you hold the geocode location of the curve, and the angle of the road on a north/south and east/west vector. You'd probably need to take incline into account, too to get accurate road measurements.)
That's just where I'd start.
But in all honesty, I wouldn't even start on this. Other programmers have done it already, I'm more interested in what hasn't already been done.
get my free raw data from somewhere like http://ipinfodb.com/ip_database.php
load it into a database, denormalizing for fast lookups
design my API
build it out as a RESTful web service
return results in varying formats: JSON, XML, CSV, raw text
The first prototype should accept a ZIP code and return lat/lon in raw text.