Why do quants use c

This was part of my duties when I was working as a "quant dev". If you are interested in a more relaxed environment than a bank trading floor then hedge funds are a good answer. As an anecdotal data point, I was recently asked by a friend if I knew any Python developers who might be interested in a quant fund developer position as they're using Python exclusively for their entire trading system within a new quant fund.

You won't have trouble getting hired with those languages if you can pass the tricky interview questions. To begin learning either have a look at these QuantStart reading lists:. Join the QSAlpha research platform that helps fill your strategy research pipeline, diversifies your portfolio and improves your risk-adjusted returns for increased profitability.

Join the Quantcademy membership portal that caters to the rapidly-growing retail quant trader community and learn how to increase your strategy profitability. How to find new trading strategy ideas and objectively assess them for your portfolio using a Python-based backtesting engine.

How to implement advanced trading strategies using time series analysis, machine learning and Bayesian statistics with R and Python. Net or Java see my course on HPC. When each array element access checks the bounds and throws exceptions, you know you're leaking CPU cycles there. Possibility of invoking low-level CPU instructions e. What with all the headers, include directives, friend class declarations, and myriads of other redundant things.

Has hard-to-use libraries STL, Boost with very cryptic, global-level mechanisms. Navigation, refactoring, analysis - all are weaker or non-existent. This is going to be improved in the near future for both VS and standalone editing. Compiler errors are beyond cryptic. Clang attempts to fix it to some extent, but things are still cryptic, just not as abysmally bad as they were previously.

Improve this answer. Dmitri Nesteruk Dmitri Nesteruk 1, 17 17 silver badges 27 27 bronze badges. JIT will remove plenty of array bound checks. I also suspect haven't tested that OpenMP beats Java parallelization unless you handcraft it just the same as it beats.

Net's TPL. Show 9 more comments. Lliane Lliane 2, 13 13 silver badges 20 20 bronze badges. I wondered if there is any hidden reason I missed. Add a comment.

Jason Jason 1 1 silver badge 2 2 bronze badges. Latency is a key factor in QF application. It's a balance between suffering from memory leaks and having to have a system that may need to be tuned.

Something like this is more the relic of poorly profiled code. Security of Java also turned out to be vastly exhaggerated. Show 2 more comments. It is fast There are many libraries available also math and quant-oriented - and it is transparent what happens within these libraries which is sometimes not the case with proprietary higher language toolboxes and systems There are sophisticated free compilers which make it possible for academia and basically everybody to start exploring the language It is a hybrid with which you can - but need not - program in an object-oriented way The resulting code can run on its own but can also be connected to other programming systems There are few languages out there that have all of these characteristics - but there will finally be a transisiton at least towards C and Java This is already happening.

Is this on a subjective scale, taking into account personal bias? Perhaps that will catch up. Pete Wilson Pete Wilson 4 4 silver badges 13 13 bronze badges. Even if somehow And this is no critism. But it could explain your bias towards C. I remember every language at the beginning seemed to be build out of "counterintuitive rules".. Maybe you're thinking of C and extrapolating. Darren Cook Darren Cook 1, 1 1 gold badge 17 17 silver badges 26 26 bronze badges.

Sometimes templating can result in increased inlining, which can sometimes increase performance. There are also template metaprogramming techniques that can increase performance. Some of the most ideological arguments: 'Bound checks on every array element access.

An AAD-enabled version is also available. See the extensions page for details on bindings and ports to other languages. Appreciated by quantitative analysts and developers, it is intended for academics and practitioners alike, eventually promoting a stronger interaction between them. QuantLib offers tools that are useful both for practical implementation and for advanced modeling, with features such as market conventions, yield curve models, solvers, PDEs, Monte Carlo low-discrepancy included , exotic options, VAR, and so on.

The library could be exploited across different research and regulatory institutions, banks, software companies, and so on. The QuantLib license is a modified BSD license suitable for use in both free software and proprietary applications, imposing no constraints at all on the use of the library.

A few companies have committed significant resources to the development of this library; notably StatPro , a leading international risk-management provider, where the QuantLib project was born. Get QuantLib Head to our download page to get the latest official release, or check out the latest development version from our git repository.

Documentation Documentation is available in several formats from a number of sources. Need Help? Found a bug?