Alphacat Introduces 15 New Product Offerings To Their ACAT Stores

A Hong-Kong based cryptocurrency price forecasting service, Alphacat, in its development report of the second half of November 2018, has revealed details about 15 new product additions to their ACAT Store. The new additions bring up the tally of product offerings to 39. Alphacat in the last month has begun to accept listings from third-party developers, who are now working both in cooperation with Alphacat, as well as independently. That is, all their ACAT Store applications will be developed either by their official development team, or third party teams integrated with the ACAT platform, or independently by third parties.

The report, according to Alphacat is an effort to ensure transparency and encourage communication with their customers.

These applications are distributed in 7 channel categories: Market Forecasting (6 new Apps), Technical Analysis (4 new Apps), Multi Data (9 new Apps), Asset Allocation (2 new Apps), Trading Tools (12 new Apps), Derivatives Market (5 new Apps), and Others (1 new App).

These 39 applications listed in the ACAT Store, have been developed by Alphacat Team in collaboration with the third parties, as well as those which have been developed entirely by third parties on their own. They also are encouraging more such developers to come forward, and participate in this project. In the case of developers, they will be supporting the those who are at the conceptual stages of product design, that who already have products listed in the store, those who already have products and are certified by Alphacat and those developers who are working in cooperation with the Alphacat Team.

Alphacat announced additional developer support for potential additions to their online marketplace, the ACAT Store, which has been made optimal for use on mobile devices. Derivatives markets were added in the updates, as well as new sources of raw data and data analysis.

After much research on its market forecasting tools, Alphacat has decided that its  PRNN-LSTM (Pipeline Recurrent Neural Network -Long Short-Term Memory) forecasting model “is currently the most suitable” for the core of its artificial intelligence forecasts.