Custom Dataset Streams & APIs

(VAI cryptocurrency transaction enabled)

Advanced Natural Language Processing (NLP) & Sentiment Analysis for Smart Cryptocurrency Basket Trading

Create Cryptocurrency, Nasdaq, NYSE, OTCBB, ETF & Options datasets
with custom columns and engineered features

[ Sample training data 1 ]
[ Sample training data 2 ]
[ Data acquisition pipeline diagram ]

Rows contain symbols. Columns contain fundamental data and 1 year (2008 - 2014) of minute-by-minute price data for cryptocurrencies, S&P 500 stocks or EOD data for all equities and up to 5 columns you can define, represented by concepts or trends. 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
  • Examine symbiotic, parasitic and sympathetic relationships between equities
  • Automatically create baskets of stocks based on concepts, trends or keywords
  • Detach the custom columns and append them to other proprietary inhouse datasets
  • Select a Data Context (e.g. Biological, Chemical, GeoPhysical and others) to derive different signals
  • Use stock symbols as custom concept column labels and model cross-correlations between equities
  • Create features using trending terms anywhere on the internet

    How do the concepts or trends correlate to cryptocurrecies, stocks, options or ETFs?

    Scores range from 0 to 1 and represent strength of known and hidden relationships between a concept or trend and a cryptocurrency, 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 or trends can then be factored or parameterized for exploring new signals or building new models.

  • Enter 1 to 5 concepts or keywords
    example: Playstation, Helium, Korea, Shampoo, Coffee

    Trading Vehicle:   
    Data Context:
    Month:   Year:

    Example use case:

    Returns for Playstation, Helium, Korea, Shampoo, & Coffee in comparison to the S&P 500: (interactive)