Dataset Name: vectorspace_correlation_matrix_datasets_based_on_nlp_nlu
Data Starts at: 2018-12-08 00:00:00
Asset Class: Crypto,Equity
Data Update Frequency: intraday
Correlation Matrix Datasets based on NLP NLU
Vectorspace AI datasets are used to augment existing time-series datasets with NLP NLU relationship clustering to boost precision, accuracy, Sharpe or Sortino ratio.
Vectorspace AI offers over 100 billion different updating datasets with multiple data sources to choose from.Vectorspace AI's system consumes peer-reviewed scientific literature, news, market data, financial statements and press releases - all the usual inputs for a machine learning technology - to generate it's thematic 'Smart Baskets', Vectorspace AI's name for the basket of stocks created by the system.
These thematic Smart Baskets change depending on the inputs, which can be one input or multiple inputs. The algorithms work on a three day hold for long positions and a four day hold for short positions (the time period is a result of the back-testing) and the baskets are created when a double-digit stock price change is identified by the algorithm; Vectorspace AI's back-testing shows optimized results when an 11% stock price change occurs.
VectorSpace Smart baskets
Vectorspace context-controllable correlation matrix datasets can be used to create what we call 'Smart Baskets'. These are groups of assets such as equities or cryptocurrencies that share known and hidden relationships with one another. Detecting hidden relationships between equities, entities and global events based on sympathetic, symbiotic, parasitic or latent entanglement can result in unique opportunities connected to 'information arbitrage'.