CyMetica | Public Company Hidden Relationship Discovery
Create Nasdaq, NYSE, OTCBB, ETF & Options datasets with
custom columns/feature labels for additional signal boosting
Rows contain stock symbols. Columns contain fundamental data and 1 year (2008 - 2014) of minute-by-minute price data for S&P 500 stocks or EOD data for all equities + up to 5 columns you can define, represented by keywords or concepts you choose. Dataset generation is based on public & private databases, an army of human curators and data triangulation.
What kind of things can be done with custom concept columns/features?
Create unique sectors or clusters based on concepts and hidden relationships and compare their gains to the S&P
Determine if price correlations have similar concept or keyword correlations
How do the concepts (or trends) correlate to stocks, options or ETFs?
Scores range from 0 to 1 and represent strength of known and hidden relationships between a concept and a stock, option or ETF. The score is calculated based on a series of algorithms that monitor data surrounding each company associated to the underlying security where each score is combined with scores from human curation teams. These concepts can then be factored or parameterized for exploring new signals or building new models.
Example use case:
Returns for Playstation, Helium, Korea, Shampoo, & Coffee in comparison to the S&P 500: (interactive)
Google Search Trends for Playstation, Helium, Korea, Shampoo, & Coffee