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7

I work with time series intensively, and I am experienced in Java and scripting languages such as MATLAB and R. I strongly suggest that you should cook up your own implementations in Java, and stop hunting for and relying on any off-the-shelf implementations. They are not reliable. One should be able to write std, corr, cov, ma, etc., easily by hand. Coding ...


4

That's the best question that nearly no one asks. I'm with you on Quantlib and Strata, haven't really seen a very good design around but I've seen quite a few bad ones. It is definitely doable and has big advantages in terms of testing, maintenance, scalability. The golden rule is that your objects must correspond to concepts. The core problem (in bad ...


3

There are two open source libraries that you should take a look at. Both feature a wide list of products and models. QuantLib. Written in C++ but usable in other languages such as Python. The library is developed for several years now. A feature that might come very handy is that there are toolboxes to implement derivative pricing libraries in Excel. Take a ...


3

Turns out Quantopian's empyrical package handles this exact use case Quantopian Empyrical Package


2

I suppose it will be difficult to provide a precise response as it is a fairly vague question and the reality is quite diverse. From my personal experience, the Quant I used to work with are using techno as R, Matlab combined with Visual Basic. Regarding more sophisticated tool coded in Java or C#, they are most of the cases inhouse frameworks. So the only ...


2

I currently use a combination of matplotlib and Oanda's FX API. Their API is REST based, and would essentially allow for any type of library to handle calculations. A python wrapper for the Oanda API is on github


2

Not that I know, and I'm in that business. Allegro is a ETRM provider, equivalent to Murex in the banking area, but, as far as I know, they don't provide any library outside their main system (which is not able to deal with any kind of exotic), and definitely nothing open source. Let me know if you find anything, because I would be glad to use it. Depending ...


1

There is no one definitive programming language to be used for this. As Attack68 stated, a library written mostly in Python while taking advantage of Python's fast libraries written in C would be a good choice for the following reasons: Again, as the comment stated there is a large community of Python programmers, plus the community supporting the ...


1

For Java you may try: https://github.com/signaflo/java-timeseries https://github.com/signaflo/java-timeseries/wiki/The-timeseries-package https://github.com/signaflo/java-timeseries/wiki/ARIMA-models https://github.com/Workday/timeseries-forecast Hope this helps!


1

Let me give you the perfect solution. Use Python. The charting, graphing and analysis can be done using the PyLab environment. You can integrate the code into R using the package called rPython. You can integrate it to C and many other languages. Python also comes with infinite more features. So instead of looking for a particular library, use Python.


1

Strata seems like a fairly well designed library, which is an open source library designed by OpenGamma. From their docs Strata allows financial systems developers to build or enhance existing applications with standardized, off-the-shelf market risk components. It provides all the core concepts and market risk functionality at the heart of the ...


1

Tablesaw is similar to Python's Pandas: https://github.com/jtablesaw/tablesaw


1

Here is library for time series modelling. There are exponential smoothing models (simple, double, triple) with maximum likelihood estimation and another time series utility classes: https://github.com/hawkular/hawkular-datamining http://www.hawkular.org/docs/components/datamining/index.html


1

You can try TimEL, a Java library I've been writing to evaluate expressions for time-series data.


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