HyperQuant Fintech Platform

anov996 (28)in #ico • 6 years ago

Multifunctional fintech platform for automated cryptotrading, asset management
and dApps creation.

HyperQuant is a multifunctional platform for automated crypto trading, asset
management and dApps creation that is based on the Fast Order Delivery protocol
and blockchain technologies. It is made by professional quant traders who know
capital management industry inside-out

HyperQuant is a professional platform for automated crypto trading, asset management and dApps creation that is based on the cutting-edge AI, Risk Management, Blockchain technologies and Fast Order Delivery protocol. It is made by professional quant traders who know capital management industry inside-out. All market participants from minor crypto investors to professional capital managers, VCs and hedge-funds will have access to a broad variety of intelligent solutions covering all aspects of crypto investment and crypto trading processes.

Cutting-edge technology

Hyper Fast
Fast Order Delivery protocol works hundreds of times faster than
similar solutions and provides the competitive advantage on
the market.
Hyper Smart
All the components of the platform are managed by an AI & Risk
management system. It constantly evolves through machine
learning with the help of accumulated Market Data. The system
does not only enhance the algorithms on the platform but also
minimizes the associated risks.
Hyper Secure
By using the power of immutable Ethereum blockchain and
cryptographic proofs of knowledge (Merkle proofs), we are
developing unique and transparent system. In this system, a
user can audit his/her operations and be sure that all the
trade deals have been actually made on the exchange. The
system itself is traffic and computationally efficient, so
even if it has 1,000,000,000 orders on a daily basis, proofs will
take only 1kb in size and require just 30 hashing operations.

A complex rating system is a right way for the development of the financial platform. A rating is the instrument’s potential in a certain period of time depending on the combination of quantitative and qualitative characteristics, expressed in a final digital mark. A rating can be calculated with the help of different statistical methods. In the world financial system the ratings are comprised by independent rating agencies — Moody’s, Standard and Poor’s as well as Fitch Ratings. They are used for evaluating the credit solvency of a company. Using such rating a potential investor can understand whether he/she should purchase the obligations of the firm and how reliable this investment is.

AI forms the investment rating based on its own analysis system. It can be shown to the user with any understandable graphic method. The investment success is analyzed using a wide range of criteria, exceeding the simple methods of risk-profitability evaluation.

In case of a rating mark going down — the neural network has an in-built alert system. If a user is performing risky actions, the trading result lowers or the portfolio element diversification is not high enough — the system displays a warning to the user. Similarly to a traffic light it varies depending on how critical the situation is. In the worst case scenario the system can block any access to the problematic element, thus avoiding the full investment loss.

In addition, a personal AI-based financial advisor will recommend how to configure bots and rebalance the crypto portfolios. Safety is also built in with an automated risk-management system and an easy-to-use visual bot constructor with built-in popular trading indicators making it ideal for investors to start making their own bots.

For developers and quant traders, HyperQuant can offer a professional quantitative framework that has many features including automating back-testing on historical market data, containing hundreds of trading indicators and ready-to-use algorithms. It also has tools to optimize trading strategies after they are launched and includes an open-source unified API protocol for all crypto exchanges.