(I am not a financial advisor. This is not financial advice. Please DO YOUR OWN RESEARCH!)
Signals on YouTube
Signals is a marketplace of data science powered signals for trading crytocurrencies.
Problem
Cryptocurrency is just at the beginning of mass adoption, bringing with it a swab of new traders with limited knowledge. Couple this with a large amount of data generated by a rapidly growing market and it’s almost impossible to keep up with the latest developments in the market. This means the market can turn rapidly either leaving traders with massive losses, ‘bag holding’ crypto or missing profit opportunities all together.
Solution
Signals’ mission is to utilise machine intelligence in cryptocurrency trading to empower users with computational power and data science which will assist them in making smarter and faster trading decisions and maximise trading profits. The Signals Marketplaces provides:
• Trading algorithms based on technical analysis and machine learning which are suitable for traders without any programming skills.
• Precision trading based on data science. Based on historical data and computational power the platform is used to make precise and complex decisions assimilating many variables.
• Lightning speed trading decisions.
• Big data insights which would be impossible for any human to process on their own.
• Users can choose a number of indicators to include in a personalised trading model based upon technical analysis, deep learning and sentiment analysis based upon media monitoring.
• A platform built upon other blockchain services which integrate decentralised ‘supercomputer power’ providing access to big data computations at a rapid speed at an affordable cost.
• Indicators based on blockchain prediction markets giving users access to trading strategies augmented by crowd sourced wisdom.
• Programmers can develop new trading indicators and monetize these through the Signals marketplace.
• Users can train their trading model; back testing it against cryptocurrency exchanges to find the best settings for their selected strategy.
• The ability to automate trading or receive notification about trading opportunities and manually enter a trade yourself.
• Trading strategies can be adaptive, using the Signals data science algorithms to constantly re-learn and optimise settings based on new market trends to maximize profits.
• Share your trading strategy for other users to copy trade and receive payment in exchange. Alternatively, suers can copy trade the most successful traders within the Signals community and engage with other users to discuss trading strategies.
Current State of Product
Signals built their framework Alpha in Q2-Q4 2017 and conducted strategy back testing during the same period. They have just (24th January 2018) released their Strategy Marketplace Alpha which includes third party bot integration. As part of this due diligence I have used this platform and whilst functionality is limited (which is to be expected for an alpha) the potential is obvious.
Roadmap
Milestone 1: Q2-Q4 2017
Strategy Builder Framework private alpha, Strategy Builder UI Design, SGN Token presale Strategy Builder Framework private alpha
Milestone 2: Q1 2018
Strategy Marketplace alpha, SGN Token sale
Milestone 3: Q2 2018
Data Marketplace private alpha, Indicators Marketplace private alpha, Strategy Builder Framework update, Strategy Marketplace update
Milestone 4: Q3-Q4 2018
Features: Strategy Builder alpha, Indicators Marketplace alpha, Data Marketplace public alpha, Desktop App alpha, Machine Learning strategy optimization, Integration of decentralized supercomputers
Milestone 5: Q1-Q2 2019
Indicators Marketplace beta, Strategy Marketplace beta, Strategy Builder update, Mobile App
Milestone 6: Q3-Q4 2019
Strategy builder update, 0X trading protocol, Focus on Machine Learning
Team
The Signals team boasts over 20 machine learning, blockchain and trading experts.
CEO and Co-Founder – Pavel Nemec
Pavel was the CEO and Co-Founder of Famely in company with Pavel Volek (Signals CTO and Co-Founder). This company received seed funding in March 2014 and closed in June 2015. This startup allowed you to create your own digital magazine using data scooped from social networks, online magazines and other internet sources to pool content about you and any other person you choose. I couldn’t locate any further information about Pavel except for his involvement in Signals which makes it difficult to verify his work experience.
CTO and Co-Founder – Pavel Volek
As stated above, Pavel was a Co-Founder of Famely with Pavel Nemec in 2014. Prior to and since then Pavel worked as a full stack developer for several companies particularly focusing on UX design and front-end development. As with Nemec, there is not much other information available about Pavel Volek.
Algorithmic Trading Expert - Jan Budik
Jan has a Ph.D in algorithmic trading and 10 years of currency and commodity trading. Jan is a derivatives trader with Natland Group focusing on using trading algorithms to trade crude oil, gold and other commodities. His experience in this area dates back to 2012 when he worked at Brisk Capital as a trader focusing on short-term price fluctuations during day trading.
The Natland Group specialise in residential development and particularly focus on projects in early stages of development as well as companies in a ‘difficult economic situation’. They provide financial resources as well as team members to assist in project development. Although Signals isn’t disclosed on the Natland Group website as a current or past project it wouldn’t surprise me if they have a financial interest in this project.
Machine Learning Specialist – Michal Krajnansky
Michal has a Masters Degree in artificial intelligence and natural language processing. He has worked as a contractor and research specialist at Konica Minolta and programmer / developer at Semantic Visions.
Data Scientist – Zdenka Sedenka
Zdenka is currently working as a data scientist at Gauss Algorithmic as the Deputy Head of Research. She conducts time series analysis of financial markets and data processing.
Smart Contract Developer and Advisor – Josef Jelacic
Josef is the co-founder of Educasoft providing learning management solutions for the Central and Eastern Europe market. He has a Master Degree in Masters Informatics and his thesis addressed the leveraging of blockchain technology in enterprise particularly software development, IT governance methodologies and software auditing.
Cryptography and Security Expert – Jaroslav Sedenka
Jaroslav has a Ph.D in mathematics, cryptography and secure multiparty computation. He is currently a researcher at Nexa Technologies working on projects in the area of cryptography, security and machine learning.
Back-End Developer – Martin Solarik
Martin currently contracts to Moravia as a back-end developer working on automation of processes to speed up the delivery of localised sources. In my opinion Martin is an integral part of the Signals team in ensuring machine learning, data processing and trading algorithms link effectively with their automated trading platform.
Signals have not listed any advisors on their website.
Community
Medium 300 followers
Bitcointalk
Telegram 2,180 members
Twitter 6,641 followers
Facebook 4,464 followers
Reddit152 readers
LinkedIn374 followers, 15 employees listed on LinkedIn
YouTube188 subscribers
Token Metrics
Total tokens: 150M SGN
Hard cap (total): $18.5M
Soft cap: $2M
Pre-sale completed November 2017
Pre-sale discount: 30%
Pre-sale hard cap: $500,000 (1,969,482 SGN with 30% bonus)
Currency: Ethereum (ETH)
Token price: SGN prices will be determined by ETH/USD exchange rate at the day prior to the token pre-sale however due to the recent price increase of ETH their contribution will be pegged to the ETH value 24 hours prior to the start of the main sale. Compensation adjustments will be capped at 8% of the total token supply and all tokens related to these adjustments will be taken from the company reserve token pool.
Public sale: Commences 26th February 2018
Public sale period: Two weeks
Tokens available: ~73M
Unsold tokens: Burnt
Token Distribution
50% - token sale
20% - community rewards
18% - company reserve ***
10% - advisors and partners
2% - bounty program
*It is not specified if the company reserve is subject to a lock-up period.
Funding allocation has not been specified.
Signals (SGN) is an ERC20 token used by holders to assemble their trading models or rent and copy-trade other successful trading strategies within the Signals marketplace.
Things I Like
• Strong development team with recent and relevant experience in their particular fields
• Alpha release prior to public sale
Things I Don’t Like
• Funding allocation not specified
• Token lockup period for company reserve isn’t specified
• Reasonably long roadmap with no specific goals beyond beta platform
• Crowded marketplace with several other similar offerings (NAGA’s SwipeStox, Coinvest, Covesting etc)
• Limited information on co-founders beyond Signals and Famely
• Key development team members currently working on other projects
Will I Be Investing?
No. Whilst I think this is an exceptional concept that I’d consider using once available it is a complicated platform to develop and the roadmap is long without defining when a commercially available product will be available.
