1 / 13

Big Data Workshop – Volatility o f Stocks

Big Data Workshop – Volatility o f Stocks. By: Nadav Lapidot and Adi Gilboa. Problem Description. Stocks exchange investments are becoming widely spread “Stocks will always go up eventually..” D o they really??. Possible uses. Educate the crowd Choose investments correctly

irish
Download Presentation

Big Data Workshop – Volatility o f Stocks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Big Data Workshop – Volatility of Stocks By: NadavLapidot and AdiGilboa

  2. Problem Description Stocks exchange investments are becoming widely spread “Stocks will always go up eventually..” Do they really??

  3. Possible uses Educate the crowd Choose investments correctly Asses stocks portfolio value in a long-term perspective Allow bad people to make even more money..

  4. Possible users The obvious Banks Investments companies Brokers The not so obvious Private (un-educated) investors Regulator

  5. Money making The obvious Banks Investments companies Brokers The not so obvious Investments consulting services (web site)

  6. Game Plan Get data online (Semi) real-time Parse Remove redundancies

  7. Game Plan Cont. So what’s the big deal? Evaluate coefficients Beta = 17 ? Use (simplified) statistical known algorithms

  8. Algorithm building blocks Web crawling ini data input Data Parsing Match parsing to data source (google, yahoo etc.) Define data structs Juggling between data updates and algorithm calculations

  9. Algorithm building blocks Distribution handling Generate a distribution function from a list of samples Generate a single sample from a distribution function Econometric calculations Asses coefficients using Autoregressive based algorithms Iterate on recent incoming data

  10. Variance Calculation

  11. Assessing variables

  12. (Current) System outputs Next k-years’ variance assessment Program keeps on running

  13. Algorithm alternatives Distribution handling Implementation improvements Coefficients assessment Improve statistical algorithms and work methods Web crawling Change “crawling target” for better data update rates

More Related