TradeRiser - Decentralized Trade and Research Platform

The growth of the world wide web led to innovations in search engine technology. This makes the web more accessible and scattered everywhere. But financial data analytics, have not enjoyed the same level of simplicity and accessibility as seen on the internet. The growth of large data cannot be stopped, financial companies and individuals are equally in the race to find trading opportunities. This task will only be more difficult when new data is found, humans will struggle to follow it. This breakdown in accessibility and everywhere presents great opportunities, for systems that seek to democratize financial data analytics.

Many are involved in trading, as many have to undergo training courses. And others independently control the trade with trial and error. What is the problem?

As I said, there are two ways to learn how to trade on the stock exchange. The first is to take a course. The second is independent learning.
The main problem of the first training method is high costs. Professional training is worth a lot of money, this is not affordable for everyone. Because of their poverty, people are forced to go to the same amateurs who organize the same training course, but with less money. As a result, they receive knowledge and skills with questionable qualities, and their success wants to leave the best. Often, under the guise of "course training" scammers hide.

Let's move on to the second method. There are certain categories of people called self-taught. Why do many learn for themselves? The reason is simple. People are afraid to contact a dubious person, for fear of being cheated. But here their own shortcomings are hidden. Independent learning methods are connected with hours of theoretical material studies about trading on the exchange on the Internet. After self study, there is a trial and error period. Every experienced trader initially loses money, only after acquiring practical skills, he starts to profit. explanation of TradeRiser

TradeRiser is an intelligent artificial Research Assistant, who can answer simple and complex trading questions. To practice 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. A token-based economy called XTI will be introduced, to provide incentives to researchers, for their data and contributions to the platform.

TradeRiser solves this problem through its Research Assistant who can immediately answer trade questions that traders or investors have about financial markets.The TradeRiser token mechanism will continue to track and compensate financial analysts for question data sets, data validation, accuracy checks, suggestions, and sample report creation. Financial analysts can contribute in these ways to help train our Engine Research Researcher, and get the appropriate compensation.XTI is the underlying mechanism used to facilitate this ecosystem, and provides XTI holders with direct participation in advancing our "single source of truth" question and answer system.

Financial analysts such as freelancers or contractors, blockchain allows TradeRiser to make smart contracts with financial analysts for various parts of the job. Our commercial transactions and agreements will be carried out automatically, this will enforce the obligations of financial analysts in a contract. It provides an automated collaborative approach to data collection using a large variety of financial analysts. Smart contracts allow for various stages of work done by ç to be rewarded.

In an effort to bring as many financial analysts and ecosystems as possible, we want to reduce friction related to capital transfers between parties. Friction like cost clearing and counterparty risk will be eliminated using our XTI mechanism on blockchain.

One of the biggest challenges for TradeRiser is to make our Research Assistant model reach critical mass. In other words bring it somewhere, where it can answer most of the trade questions that users will have. This system needs to be trained on the vast universe of questions, events, and market data.

The first phase discusses how to obtain a set of data questions. This will be done by TradeRiser issuing the XTI token as compensation for the ongoing contribution to build the knowledge base from which the machine learning will be conducted. Once the critical mass is reached, carrying out phase two in attracting consumers of research to the platform will be easy. With both research consumers and content manufacturers now fully on the ecosystem, research consumers will now be able to reward content producers for their premium content and voting. This ongoing cycle will create a chain effect, thus attracting more contributors to the platform.

Platform Features

Community Edition: - It consists of many features that will be available to the community. They are as follows, Research Assistants are supported by community data feeds, ICO ratings, market condition analysis, ICO due diligence, investor portfolio analysis, direct trading, web and mobile applications.
Research Marketplace - Accessible to Token holders
Enterprise Edition: - This independent version can be accessed by financial institutions, hedge funds or companies. This includes our API.

Current Platform: Market Fit

The alpha / private beta version focuses on forex, commodities and indices, and will allow users to ask questions about economic calendar events, technical analysis, correlation and performance and more. This version has been built primarily for the purpose of demonstration and data retrieval.

Our goal is to turn this into a fully mature Research Assistant that will accompany all corners of the trade and investment space. So far it has been seen by major investment banks and technology vendors, and has received a lot of positive feedback

Token Information

Target at crowdsale: $ 23,000,000
The total is: 500,000,000 XTI
XTI Token Type: ERC20
The purchase method is accepted: BTC and ETH
Based on the Ethereum blockchain and the Ethereum smart contract

The XTI employee allocation will have a 24-month vesting period, with a 6-month cliff.

The allocation will be proportional to each employee's employment on the date of sale of the token.

Unsold tokens will be burned.

PRE - ICO

VALUE ROUND ....... 1 XTI = $ 0.07

ICO

ROUND VALUE ......... 1 XTI = $ 0.10

XTI Supply .............. XTI will have inventory with face value of USD 23,000,000.

XTI Refund

In certain cases, XTI may be returned to the platform participants. For example, use of a case may arise that will request a refund, but usually will follow a minimum period of 3 weeks before this happens.

Roadmap

2014 to 2015 .................... TradeRiser was established

2016 Q1 to 2016 Q3 .......... Beta / Alfa test personally with traders and asset managers.

2017 Q1 ................................... Participating in 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 the TradeRiser Community Edition

2019 Q2 (Apr - June) ................... Dana Hedge and Financial Institutions Partnership

2019 Q4 and Beyond .................. Launch the Research Marketplace and Enterprise Edition

For more information please visit the link below