Quantitative research is rapidly expanding within the financial investment industry, and with it has come an increasing interest in and adoption of Jupyter notebooks. Bloomberg, a financial services provider, has partnered closely with the Jupyter community to develop JupyterLab and bqplot and has also made significant advancements in ipywidgets, all of which have greatly enriched the workflows of quantitative financial researchers and other data scientists.
Srinivas Sunkara and Cheryl Quah offer an overview of the modularity and extensibility of JupyterLab’s interface, the interactive visualizations provided by bqplot, and recent changes to ipywidgets to enable rendering of interactive widgets outside of notebooks. Srinivas and Cheryl illustrate how these projects create a rich environment for data analysis and financial research and discuss the dynamics of this successful collaboration between the open source community and an industry partner in driving advancements to Jupyter.
Srinivas Sunkara is a quant on the Quantitative Financial Research team at Bloomberg LP, where he works on developing financial models that apply machine learning techniques to various problems in finance. Srinivas is one of the main developers of bqplot, a Jupyter Notebook–based interactive plotting library, and contributes to other open source projects, including ipywidgets and traitlets.
Cheryl Quah is a senior software engineer at Bloomberg LP, where she develops applications to improve financial professionals’ research and investment workflows.
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