In the world of trade and investment, the most powerful financial analytics are usually there are some reserved. TradeRiser is looking to disrupt this, by democratizing the analytical financial data and making it available to the masses. Researching the idea and exploration of financial market trading is a slow process. What is needed is a source of truth, it can give instant answers, to trade questions on a large scale. In particular how news and events affect assets around the world.
TradeRiser is an intelligent artificial Research Assistant, who can answer simple questions and complex trade questions. To train artificial intelligence we will utilize blockchain to build incentive systems, which will be supported and fed by data from a large network of analysts and quantitative researchers. Token-based economies called XTI will be introduced, to provide incentives to researchers, for data and their contribution to the platform.
After this second economy will be created, around the research market, where developers of quant models and content manufacturers will be able to reach consumers within the ecosystem. This community participation will help fulfill the objectives of democratization and simplify the analytics of financial data.
SPEED TRADERISER
Find investment and trade opportunities quickly
QUESTION
Have a question, just ask. TradeRiser handles natural language inquiries
STATISTICS
Use statistics to create and test optimal trading strategies without relying on software engineers and quants
NEWS
Intelligently analyzes news data and world events and their effects on cryptocurrency and traditional assets
ECOSYSTEM
Utilize blockchain to create a decentralized ecosystem of financial analysts
NOTIFICATION
Get signals and trade alerts.
VIDEO:
https://youtu.be/hQ-QMW4q_8s
PROBLEM
1. THE PROBLEM
1.1 Motivation - Simplify the analysis of financial data
The growth of the world wide web led to innovations in search engine technology.
This makes the web more accessible and scattered everywhere. But the analytical financial data,
have not enjoyed the same level of simplicity and accessibility around the world
the web. The growth of large data can not be stopped, financial companies and individuals alike enter
race to find trade opportunities. This task will only become more difficult as new data paths
found, humans will struggle to follow it. Disconnect this accessibility
and everywhere presents great opportunities, for systems that seek to democratize
analytic financial data.
1.2 Interfere with Human Intensive Research
TradeRiser is building an AI-based Research Assistant, which can answer simple and questions
complex trade questions. Financial professionals around the world spend a lot of time and
money in research trying to answer these trade questions. This type of research
usually time consuming, inefficient, vulnerable to information overload and requires a lot
labor. These problems are further compounded by the emergence of cryptocurrency
and financial professionals who want to trade it, in addition to traditional securities. Hurry up
cryptocurrency explosion has left many other technologies that catch up, individuals
traders need an easy way to analyze these asset classes.
1.3 Fewer Ideas Tested
The current platform relies on excellent technical knowledge to test trading ideas, and
because fewer entry barriers trade ideas tested. Every day a portfolio manager
have an investment idea and have to go to quant to build the model. That's a jam
in most financial services firms, and as a result, far fewer ideas are being tested. The same one
right from each merchant who wants to test the idea but does not have access to enough tools.
1.4 Time-Consuming
Quantitative research can be a very time consuming process, as it requires a lot
steps to complete, sometimes covering several days and hours. Other
congestion including the computation process due to the amount of data being analyzed.
1.5 Inefficiency
The research process requires data collection, data cleaning and data analysis, and
the final step is report generation. This is a very inefficient process.
1.6 Information Overload
With data being a new "oil" or a valuable resource, more analyst work
difficult in trying to process data. New paths of data continue to creep up
potentially can be utilized in financial research, especially unstructured data.
1.7 News and Events - Unstructured Data
It is well known that news and world events have an impact on financial markets,
It is for this reason that tools such as economic and income report calendars are
created. These tools allow merchants to follow and monitor events that impact, but there
is a basket of world events that have not been set for inclusion in the calendar,
which needs to be structured. Because traders stand struggling to maintain or protect data
from sources such as twitter, cryptocurrency news, weather data and even satellite data.
The entire universe of drug approval, economic reports, changes in monetary policy, and
political events and their impact on almost all types of financial assets necessary
domesticated and structured.
1.8 Solutions
TradeRiser solves this problem with its Immediate Assistant Finder
answer the trade questions that traders or investors have about financial markets.
The TradeRiser token mechanism will continue to track and compensate financial analysts for them
question data set, data validation, accuracy checks, suggestions, and examples
report generation. Financial analysts can contribute in these ways to help train us
studied the Engineer Assistant Researcher, and was compensated accordingly. XTI is
the basic mechanisms used to facilitate this ecosystem, and provide XTI holders with
direct participation in advancing our "single truth source" question and answer
system.
TradeRiser XTI
Token Distribution Name
250 million
Token Crowdsale
Distribution of funds
Roadmap
2014 to 2015
TradeRiser was established
2016 Q1 to 2016 Q3
Personal beta / alpha tests with merchants and asset managers
2017 Q1
Participate in the Accenture Fintech Innovation Lab London
2017 Q2 to 2017 Q3
UI redesign platform and improved functionality
2018 Q3
TradeRiser ICO
2018 Q3 - 2018 Q4 (June - Dec)
Developing Team and Market Data Provider Partnerships
2018 Q4 (Oct - Dec)
Launch training portal
2018 Q4 (Oct - Dec)
Launch Community TradeRiser Edition
2019 Q2 (Apr - June)
Dana Hedge and Financial Institutions Partnership
2019 Q4 and Beyond
Launch Research Marketplace and Enterprise Edition
TEAM
ADVISORS
PARTNER & SUPPORT
For more information can Click below:
Authors: YarisRiyadi1st
My Profile Bitcointalk : https://bitcointalk.org/index.php?action=profile;u=1756824;sa=summary
My ETH: 0x8B1820FB5829696cA5b595d09dF4e0F5757a97A7
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