ABOUT OFNOG
OFNOG is an IT organization that was formed by a team of seasoned IT professionals from fortune 500 organizations like IBM, HP, HPE, AT&T background.
OFNOG is a unique crypto trading solution designed to simplify cryptocurrency trading through Artificial Intelligence (AI) and Deep Learning Technology to enable traders to trade more effectively and accurately. The OFNOG concept combines a complete suite of existing, as well as a host of proprietary.
OFNOG-developed applications, which will aid in laying out profitable cryptocurrency trading strategies for OFNOG platform users.
The OFNOG platform has an aim for the project to provide the highest level of accuracy, and as such, has based its operation on Artificial Intelligence and Deep Learning algorithms, which are the latest, cutting-edge methods in real time data scrapping, trending trend, and future price forecasting.
The OFNOG platform forecasting model will collect and analyze data from multiple market indicators in an effort to provide a clear overview of the market forces at work which in turn, will help users to come up with their own trading strategies.
All of the information collected is relayed in the form of a signal to the users, who can then elect to either place orders manually, or take advantage of the OFNOG's platform automated trading bot feature, that can both execute trades or pause them, in the event of losses.
The use of Artificial Intelligence and Machine Learning provides a much better alternative to mindless trading bots. As Artificial Intelligence takes a step closer to gaining maturity, platforms like OFNOG are working on combining AI and Deep Learning to cryptocurrency trading. Such a platform will be capable of monitoring the markets, collecting critical data, conducting in-depth analysis of the historic market trends and comparing them with fresh data sets to predict potential future price movements. Signals derived from such analytical processes can be readily used by traders to place orders on the relevant exchanges and reap profits. It also paves the way for further automation with bots.
OFNOG uses AI to analyze the cryptocurrency market data and trading trends and compares it with the existing scenario to create trading signals which can be used by traders on the platform to place their trades. By way of using OFNOG, even those who are new to cryptocurrencies gain access to the collective “wisdom” from months, if not years of trading trends. It will automatically increase the trader’s success rate and helps
him observe and learn the nuances of trading with time.
The OFNOG project also makes use of Deep Learning Technology which will make it capable of predicting the market outcomes with the highest accuracy, just like or even better than how a seasoned crypto-trader would do.
THE OFNOG TOKENS
The OFNOG token is a utility token which is native to the OFNOG cryptocurrency trading signals and automation platform. The OFNOG token is a ERC20 token created over Ethereum blockchain. The maximum cap for OFNOG token will be set at 500,000,000, to be distributed across multiple crowdsale stages. A portion of the tokens will be set aside to cover development, operations and marketing purposes.
OFNOG as written earlier, is a blockchain project created by a team of IT experts with experience in multiple Fortune 500 companies. They are using Artificial Intelligence (AI) and Deep Learning technology to introduce a certain degree of automation into the cryptocurrency trading process. With the use of these breakthrough technologies, they aim to lower the entry barrier for both newbies as well as experienced traders and enable them to execute profitable trades.
For More Information About OFNOG, Please Visit The Following;
WHITEPAPER: https://www.ofnog.io/pdf/ofnog-whitepaper.pdf
WEBSITE: https://www.ofnog.io
TWITTER: https://twitter.com/OFNOG1
FACEBOOK: https://www.facebook.com/OFNOG-1977265739191600/
YOUTUBE:
MEDIUM: https://medium.com/@ofnogltd/
My BTT Profile Link: https://bitcointalk.org/index.php?action=profile;u=1039613
Authored By: Haggaik
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