Julia as a HPC Alternative for Quant Finance Interactive 2d & 3d Financial Plotting with plot.ly Python for Quant Finance - Success Stories from the Trading Floor Using Big Data for Trading Bond Futures & FX using the LLVM infrastructure, yield highly performing implementations that are nevertheless concise and easy to maintain.Ĭloud providers offer small and huge compute instances billed by the hour, clusters with 100 instances are instantiated in 10 minutes, Spark revolutionizes Big Data with its superior architecture compared to traditional Hadoop implementations. C++) without suffering a significant performance burden. Modern, high level Open Source progamming languages like Python, R and Julia allow the implementation of even the most complex financial algorithms at much faster speeds (compared to e.g. Powerful libraries allow, for example, to visualize in interactive D3.js fashion complex datasets with a single method call. Interactivity, collaboration, reproducability are nowadays easily accomplished with such tools. Tools like browser-based, interactive notebooks revolutionize how Quant Finance is conducted on a daily basis.
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