Crypto-Trading Strategy Marketplace “Signals” Launches Token Sale

Jared 5:43 am

Crypto trading innovators Signals Network have announced plans to develop a platform that will assist crypto traders with learning investment strategies through the use of advanced machine learning algorithms. The Prague-based start-up hopes to connect the trader community with data scientists on a simple user interface, together creating smarter trading strategies assembled by machine learning with only a few clicks.

 

Bringing Together Science with the Crypto-Trading Industry

One of the many impacts that blockchain technology is having is the enabling of start-ups to create their own crypto assets and to bind the value of the company to it. This new model of fundraising has seen a rapid increase in new crypto assets, directly leading to an expansion of cryptocurrency trading markets as it receives bigger influxes of traders and investors taking advantage of new opportunities.

 

Another trend that is gradually forcing traditional capital markets to evolve is the growing ability of computer and artificial intelligence to automate highly complex decision-making  processes. With digital data expanding rapidly and computational power reaching record heights, data science and machine learning techniques are creeping into many industries, with big potentials in cryptocurrency trading.

 

It was this intersection of opportunities that led to the founding ideas behind Signals, driving its mission to empower crypto traders with the data science community’s most sophisticated algorithms to allow them to optimize profits. Focusing on developing user-friendly tools, the Signals Platform ensure that anybody is able to create fully customizable trading robots without requiring any advanced technical knowledge. Hence, every trader will have full access to classic technical indicators to complex statistical models, advanced charting activities based on inputs using crowd wisdom and machine learning algorithms based on analyzing sentiment and monitoring media.

 

How Signals Will Work

To achieve its’ objective of open access for all traders to state-of-the-art machine learning algorithms, the Signals team will build a network open to data science developers and the crypto trading community. Traders will be able to use specific trading indicators from a range of technical analyses and crowd wisdom insights, feeding it historical data to build unique trading strategies. They will then be able to offer it on the platform for others to copy, therefore monetizing their strategies.

 

Watch the following video for a demonstration:

https://www.youtube.com/watch?v=KY2qu0zpq-Q&&feature=youtu.be

 

Signals has entered into partnership with French company iExec, a specialist in blockchain-based cloud computing, to enable quick processing of extreme amounts of data with complex algorithmic computations.

 

The Signals Token (SGN) Presale

Signals plans to release a public alpha version of its platform by the end of the year, featuring a Strategy Marketplace. Its native Signals Token (SGN) will be the currency used to pay for all the features of the platform, such as indicators, data sets or strategy leasing for copy-trading.

 

Each transaction made on the platform will result in the burning of a small amount of SGN, effectively creating a deflationary currency, with an expected increase in value due to a gradually shrinking supply against growing demand and use.

 

Signals will be offering up SGN tokens for sale during its Pre Sale which launched on November 22, 2017, with all participants eligible for a 30% bonus on all purchases. Approximately 2 million SGN will be offered up during this period, with more than 1.3 million SGN already sold at the current time.

 

After the presale, the public crowdsale will launch in December, putting up a further 73 million SGN at a base price of approximately $ 0.26. Contributions can be made with Ethereum. All interested participants must first register with a name, e-mail and an ETH wallet address.

To learn more about Signals, visit their website.

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