Financial Data Science Association

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ReFine Principles of Financial Data Science

About Data

  1. Data-driven: Be driven predominantly by real world observations to develop actionable, well-reasoned solutions.
  2. All Data may be useful: Insist on the open exploration of all types of data, information, and knowledge that might help define and reach better results.

About Teamwork

  1. Teamwork across degrees & disciplines: Encourage teamwork among researchers of various backgrounds and degree levels (Ph.D., M.Sc., M.A.) and pursue a solid cross-disciplinary approach that melds and contrasts techniques and statistical rigor for better outcomes.
  2. Anti-discrimination: Despise discrimination. Build a global community devoted to science and solving problems that will enrich society, make markets more transparent, and make enhanced use of all available resources.

About Science

  1. Support Science: Support scientific, data-driven research to push the boundaries of what is possible, develop new and interesting questions, and look to create opportunity for a better understanding of the world around us.
  2. Transparency: Endorse the sharing economy and spirit of openness and transparency through joint ownership of the FDS community, and broad global participation.
  3. Reproducible & Accurate: Demand highest scientific standards with data being processed at greatest accuracy and work be reproducible, at least by those with access to equivalent resources.
  4. Explain Variance: Aim to measure and reduce unexplained variance to ensure models are robust, useful and predictive.

About Society

  1. Enlighten Society: Create solutions aimed to benefit and enlighten society as a whole, leveraging finance and computer science for the broader good.
  2. Towards Sharing: Share at all times, ideas, algorithms, models, data, except where this would make future work difficult or less viable.

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