HyperQuant – Innovative Platforms Use Algorithms and AI to Invest

Posted on

HyperQuant Logo

HyperQuant – Innovative Platforms Use Algorithms and AI to Invest

HyperQuant – We all know that in an unstable cycle, financial turmoil is only careful in portfolio management to protect capital from high inflation. Contemporary centralized financial systems have several disadvantages, namely a closed structure and transfer of funds to a lack of transparency in management, as a control strategy depends on the use of funds management teams, to some extent.

The creation of blockchain technology has created a new market, and blockchain technology can solve centralized system problems. But it also has its own, that the price and altcoin cryptocurrency volatility are a lot of problems, most sign holders cannot skillfully manage risk, many coins and altcoins are unreliable, and many cryptocurrency exchanges are limited in liquidity. HyperQuant is ready to solve this problem.

What is HyperQuant?

The HyperQuant blockchain is an automatic investment platform. Because HyperQuant’s investment process is simpler and more transparent for all market participants ranging from small and medium investors to professional capital managers of large capital investors. HyperQuant is a platform dedicated to creating highly efficient and fragmented financial services. This platform provides new opportunities for software development and algorithmic trading by providing a framework that quantifies system stability and reliability through risk management of artificial intelligence and advanced blockchain technology. HyperQuant applies a smart contract implementation mechanism. The HyperQuant system provides utilities for creating and developing algorithmic trading solutions. AI manages the ranking system and artificial intelligence, enabling it to manage various elements of the platform. The HyperQuant application includes services and solutions for retail and corporate system users.

HyperQuant Ecosystem

HyperQuant Ecosystem

The HyperQuant ecosystem is not only a financial tool that is very much needed today, but also a new place for global distribution. Advanced technology based on artificial intelligence developed rapidly and developed recently.

HyperQuant’s unique feature is the interaction between AI, blockchain technology, and users. This gives users the opportunity to create new products and entities for the platform, such as configuring the Megabot automatic trading system combination. The user creates a solution that contains configuration parameters, a combination of robot identification numbers, and other necessary system data that adds up to the value of the new entity itself.

How does HyperQuant Work?

The HyperQuant business model is based on an innovative approach to identifying important and necessary conditions for users. The concept of this business model relies on identifying high margin zones, assessing ways to gain market share and ensuring protection from competitors. The HyperQuant ecosystem creates an architecture that allows Pioneer technology to translate into real economic value. Services created in the HyperQuant ecosystem have tremendous growth potential.

HyperQuant uses trade robots to complete financial market trading operations through a series of algorithms. With the help of algorithmic trading systems it has several advantages, namely the fastest to make decisions and get things done with the speed of transactions not available for human use, automatic processing of market data and generating trade signals, and
The accuracy of trading signal processing makes it possible to prevent errors by regulating market demand.

Trade robots work strictly according to established algorithms, complete trading operations without emotion, and manage thousands of securities simultaneously. Cryptographic currency traders and token holders are vulnerable to emotions that lead to unreasonable decisions. Trading strategies apply to every market and have any assets at all times. The algorithm carefully enters the risk of uncertainty due to uncertainty, anger, fear, and hatred. The basis of this algorithm is the division of strategy classes.

There Are Several Classifications Of Trading Strategies And Models

  1. Trend Tracking Strategy
    The main objective of this strategy is to find complete trading operations for the purpose of favorable prices and profitable positions for the longest period of time. Trend tracking strategies are designed to capture large fluctuations in financial instruments. Strategy trends based on technical indicators are the most popular strategy. Technical indicators are functions based on statistical exchanges of indicator values, such as the price of trading instruments. The rules are open, and the calculated value indicators from this strategy are derived and compared with each other and with values formed by market prices.
  2. Anti-trend Strategy
    That is, based on the expectation of a major price change and the next position strategy is opened in the opposite direction. Suppose the price will return to the average price. Counter-trend strategies are often attractive for trading because they are bought at the lowest prices and sold at the highest prices.
  3. Pattern Recognition Strategy
    The purpose of this strategy is to classify objects from various categories. Distribute image recognition tasks that can identify new objects to a particular class. This strategy uses neural networks as a basis for education and is widely used to identify candlesticks. The candlestick pattern is a combination of candlesticks. Based on the appearance of the candlestick model, there are many candlestick models and assumptions about continuous price changes or vice versa. These assumptions are based on strategies introduced by technical analysis.
  4. Arbitration Strategy
    There are many types of arbitration strategies, namely cross-market arbitration, and statistical arbitration.
  5. Machine-based Learning Strategies
    The basis of machine learning is the modeling of historical data and the use of models to estimate future prices. Machine learning is a classification.

The Si HyperQuant Technology algorithm strategy is as follows:

  1. Smart Order Execution Strategy
    This strategy class is based on the order book work. HyperQuant software dynamically generates policies based on specific tasks.
    It is impossible to carry out orders at the same price first, all transactions will reach the desired price, but gradually reduce profits from prices. To reduce costs, institutional customers need to use a clever order execution strategy. Large market order execution can be divided into several steps and involves a combination of various strategies. HyperQuant platform users will be able to configure various fields of strategy, namely quote instruments, volume, minimum volume, maximum volume, maximum BBO distance, internal bidding rate, internal quote level, hedging, hedging and hedging settings.
  2. Market Formulation Algorithm
    Execution of market execution algorithms results in increased liquidity of trading instruments. This also leads to a decrease in the volatility of trading instruments. Providing liquidity is very important for the development of the trade industry. The largest stock markets such as the New York Stock Exchange, Nasdaq Stock Exchange, and Chicago Stock Exchange generally provide liquidity supply mechanisms. Market makers must support order quantities from bidirectional quotations and meet query periods of certain minimum requirements, all purchase orders are negotiated according to the data market.
  3. Risk Management
    Risk management is the process of adopting and implementing complex actions that aim to reduce the likelihood of adverse outcomes and minimize the possibility of loss. There are certain risks associated with each investment transaction and activity. In this case, the risk is the possibility of unexpected economic losses in an uncertain environment. Each trader is exposed to market risk, that is, the possibility that market interest rate fluctuations will cause changes in asset prices. There are other less known risks, namely operational, functional, selective, and liquidity risks.
  4. Hedging
    Hedging can be divided into short selling hedges and be buying hedging. Buying hedges are used when traders plan to buy assets in the future and try to reduce the risks associated with price increases. In the case of sales in commodity markets, the use of hedges to protect the risk of a price collapses in the future and implies that the seller sets a fixed price for himself.
  5. AI-based Financial Advisor
    Most investments fail because of wrong risk management and inadequate user control. To solve this problem, HyperQuant uses artificial intelligence based on data collected from HyperQuant platform users.
  6. Blockchain Based On Smart Contract Protocol
    The HyperQuant team developed an integration protocol that included a set of standard algorithmic strategies implemented as smart contracts.

TOKEN HyperQuant

HyperQuant issues utility tokens to create an internal economy in the platform ecosystem. By releasing HyperQuant Tokens (HQT), HyperQuant offers all users the opportunity to become revolutionary platform makers, enabling them to effectively manage their capital. Each HQT token holder will receive various levels of access to products and solutions based on the HyperQuant platform. The level of access and function in some products will depend on the number of tokens they have. Reflect the economic value of a human business by making entity developers on platforms such as trading robots.

Token Sale Details

  • Private sale: May – June 2018
  • Public pre-sale: July 2018
  • Ticker: HQT
  • Token type: ERC20
  • TGE Token Price: 1 HQT = 0.00028 ETH
  • 1 ETH = 3500 HQT
  • Fundraising Goal: 20 000 ETH
  • Total token supply: 200 000 000 HQT
  • Available for token sale: 35%
  • Country: Estonia
  • Accepting: ETH
  • Whitelist: Yes
  • KYC: Yes
  • Unsold tokens: Frozen for 2 years
  • Lock-up period: Team – 1 year after the Token Generation Event
  • Advisors: 6 months after the TGE
  • Bonus: 3 months after the TGE (each month 1/3 is unlocked)
  • Bonuses for institutional investors will be locked up to 6 months.

Token Distribution

  • Token Sale: 35%
  • Reserve fund: 39%
  • Team: 15%
  • Advisors & Partners: 9%
  • Bounty: 2%

HyperQuant Token Distribution


HyperQuant Roadmap

To know the latest information about HyperQuant project you can visit the link below:

Website: https://goo.gl/4Jc6yc
Whitepaper: https://hyperquant.net/en/wp/
Telegram: https://t.me/joinchat/AyLwZkMYopaGJkCck8S3Hw
Facebook: https://web.facebook.com/hyperquant.net
Twitter: https://twitter.com/hyperquant_net
Medium: https://medium.com/hyperquant
ANN Tread: https://bitcointalk.org/index.php?topic=2104362.0

BTT Profile: https://bitcointalk.org/index.php?action=profile;u=376156

ETH: 0xC7B643eA72a38091337E7CaB8E4cE1A144D3AA4B

Disclaimer: “I’m not a representative or a member of the HyperQuant team, I just give you the latest ICO info”