maniecool: TradeRiser - Decentralized Trading and Research Assistant For Answering Trading Questions

Introducing TradeRiser
The growth of the world wide web led to innovations in search engine technology. This made the web more accessible and ubiquitous. However financial data analytics, has not enjoyed the same the level of simplicity and accessibility seen in the world wide web. The growth of big data cannot be stopped, financial firms and individuals alike are in a race to find trading opportunities. This task will only get harder as new avenues of data are discovered, human beings will struggle to keep up. This disconnect in accessibility and ubiquity presents a huge opportunity, to systems that seek to democratize financial data analytics.
TradeRiser is an artificially intelligent Research Assistant, that can answer simple and complex trading questions. To train the artificial intelligence we will be leveraging the blockchain to build an incentivization system, which will be supported and fed by data from a large network of quantitative analysts and researchers. A token based economy called XTI will be introduced, to incentivize researchers, for their data and contributions to the platform.
Solution
TradeRiser solves these problems through its Research Assistant that can immediately answer trading questions that a trader or investor has about the financial markets. TradeRiser’s token mechanism will keep track and compensate financial analysts for their datasets of questions, data validation, accuracy checking, suggestions and example report creation. The financial analysts can contribute in these ways to help train our machine learning Research Assistant, and be compensated accordingly. XTI is the underlying mechanism used to facilitate this ecosystem, and provides XTI holders with direct participation in advancing our “single source of truth” questioning and answering system.

What is TradeRiser?
TradeRiser is a artificially intelligent Research Assistant, that can answer basic and complex exchanging questions. To prepare the man-made brainpower we will use the blockchain to manufacture a boost framework, which will be bolstered and nourished by information from a substantial system of quantitative investigators and analysts. A token based economy called XTI will be presented, to boost analysts, for their information and commitments to the stage. Following this a second economy will be made, around an exploration commercial center, in which quant show engineers and substance makers will have the capacity to achieve purchasers inside the environment. This interest of the network will help satisfy the objective of democratizing and streamlining monetary information examination.
Problem to be solve by TradeRiser
Inspiration - Simplifying money related information investigation
The development of the internet prompted advancements in web crawler technology.This made the web more available and pervasive. Anyway money related information analytics,has not appreciated the same the level of effortlessness and openness found in the internet.
Disturbing Human Intensive Research
TradeRiser is building an AI based Research Assistant, that can answer both straightforward and complex exchanging questions.
Less Ideas Are Tested
Current stages depend on an awesome level of specialized know how to test exchanging thoughts, and because of the hindrances to section less exchanging thoughts are tried.
4 Time-Consuming
Quantitative research can be a unimaginably tedious process, as it requires numerous means with a specific end goal to be finished, some of the time spreading over a few days and hours. Different bottlenecks incorporate the computational procedure because of the measure of information being broke down.
Wastefulness
The examination procedure requires the information gathering, information cleaning and information investigations, and the last advance being report creation. This is an extraordinarily a wasteful procedure.
Data Overload
With information being the new "oil" or an important asset, the activity of examiners is all the moredifficult in endeavoring to process information. New roads of information are continually crawling up which can possibly be abused in money related research, particularly unstructured information.

Current Platform: Market Fit
TradeRiser has built an alpha/private beta version of the Research Assistant, this can be accessed on request or signing up at www.traderiser.com. The alpha/private beta version focuses on forex, commodities and indices, and will allow users to ask questions surrounding the economic calendar events, technical analysis, correlation and performance and more. This version has been built predominantly for demonstration purposes and data capturing.
Our intention is to transform this into powerful fully fledged Research Assistant that will accompany all corners of the trading and investing space. So far it has been seen by major investment banks and technology vendors, and has received a lot of positive feedback

Token

Target on crowdsale: $23,000,000
● Total in existence: 500,000,000 XTI
● XTI Token type: ERC20
● Purchase methods accepted: BTC and ETH
● Based on Ethereum blockchain and the Ethereum smart contract
Employee allocation of XTI will have a vesting period of 24 months, with a 6 month cliff.
Allocation will be proportional to the tenure of each employee by the date of token sale.
Unsold tokens will be burnt.
PRE - ICO
ROUND VALUE
1 XTI = $0.07
ICO
ROUND VALUE
1 XTI = $0.10
XTI Supply
XTI will have a supply with nominal value USD 23,000,000.
XTI Refunds
In certain cases, XTI may be refunded to platform participants. For example, use cases may arise that will necessitate a refund, but typically will follow a minimum period of 3 weeks before this takes place.
Roadmap
2014 to 2015
TradeRiser is founded
2016 Q1 to 2016 Q3
Private Beta/Alpha test with traders and asset managers
2017 Q1
Participated in the Accenture Fintech Innovation Lab London
2017 Q2 to 2017 Q3
Platform UI redesign and functionality improvement
2018 Q3
TradeRiser ICO
2018 Q3 - 2018 Q4 (June - Dec)
Growing The Team and Market Data Provider Partnerships
2018 Q4 (Oct - Dec)
Launch training portal
2018 Q4 (Oct - Dec)
Launch Community Edition of TradeRiser
2019 Q2 (Apr - June)
Hedge Fund and Financial Institution Partnerships
2019 Q4 and Beyond
Launch Research Marketplace and Enterprise Edition
Team