Momentum Strategies: Comparison of Programming Language Performance

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Publicat a:Journal of Trading vol. 11, no. 2 (Spring 2016), p. 49
Autor principal: Ceccon, Francesco
Altres autors: Thukral, Lovjit, Vergel Eleuterio, Pedro
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Pageant Media
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100 1 |a Ceccon, Francesco 
245 1 |a Momentum Strategies: Comparison of Programming Language Performance 
260 |b Pageant Media  |c Spring 2016 
513 |a Feature 
520 3 |a Given the increase in the popularity of algorithmic trading resulting from an increase in market participants, more considerations are now required to prototype a profitable trading strategy. Trading strategies, which require optimization of parameters based on linear or nonlinear relationships, cause an increase in complexity, which in turn increases computational run time. We find that C provides the best performance for prototyping quantitative trading strategies; however, it is the most time-consuming to implement. Among the languages that allow for faster development times, the difference between Cython and Julia is relatively small, so choice between them comes down to user preference and other factors. We find Julia to be the standout programming language due to its simplicity and high performance. 
651 4 |a United States--US 
653 |a Studies 
653 |a Programming languages 
653 |a Software engineering 
653 |a Financial services 
653 |a Program trading 
653 |a Growth models 
653 |a Java 
653 |a Algorithms 
653 |a Libraries 
653 |a C plus plus 
653 |a Optimization techniques 
653 |a Python 
700 1 |a Thukral, Lovjit 
700 1 |a Vergel Eleuterio, Pedro 
773 0 |t Journal of Trading  |g vol. 11, no. 2 (Spring 2016), p. 49 
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