TRADERISER - Get Instant Answers To Trading Questions Without The Leg Work


A storm has hit the investment market which we are not going to recover from. Crypto investment is that storm. With strict capital controls in place by most countries to control the flow of money and charge high taxes, cryptocurrency gained usage in circumventing capital controls and taxes, leading to an increase in demand. Cryptocurrency has been able to present an easy to use digital alternative to fiat currencies. Offering frictionless transactions and inflation control, investors have been prudent enough to add these currencies in their diversified portfolios as an asset, as the size of the market does not represent a systemic risk. Cryptocurrency employs the use of cryptography that assures high-security processes and verifies transactions personal to each user. Hence, counterfeiting and anonymous transactions are impossible to achieve.

While this revolution is gaining wide acceptance, TradeRiser, an artificially intelligent Research Assistant, that can answer simple and complex trading questions has arrived.

Before I take you on this voyage, please check out this video presentation

Now that I have your attention, let’s get right to it.

What exactly is TRADERISER?

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.


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.

Why Blockchain?

The blockchain ledger is a publicly-verifiable record that can be used to confirm that both the financial analysts and content producers on our system have been compensated for their contributions. Research consumers looking for premium reports that is in the Research Marketplace section will also have the confidence that payments have gone towards the content producer for the selected reports, with a dependable system-of-record always available as an accounting of their usage

Financial analysts are like freelancers or contractors, the blockchain allows TradeRiser to create smart contracts with the financial analysts for various pieces of work. Our commercial transactions and agreements will be executed automatically, it will enforce the obligations that the financial analysts have in a contract. It provides an automated collaborative approach for data gathering using a large diverse pool of financial analysts. The smart contract allows for the different stages of work carried out by çto be rewarded.

Costs Cutting

In bid to bring as many financial analysts and onto the ecosystem, we want to reduce the friction associated with transferring capital between parties. Friction such as clearing costs and counterparty risks, will be eliminated by using our XTI mechanism on the blockchain.

Reaching Critical Mass

One of the biggest challenges of TradeRiser is getting our Research Assistant model to reach critical mass. In other words getting it to a place, in which it can answer the majority of trading questions it’s users will have. The system needs to be trained on a large universe of question, events and market data.

Phase one addresses the way to acquire the data set of questions. This will be done by TradeRiser issuing the XTI tokens as compensation for the ongoing contributions to building the knowledge base, from which the machine learning will be done from. Once critical mass has been reached, executing phase two in attracting research consumers onto the platform will be easy. With both the research consumers and content producers now fully on the ecosystem, the research consumers will now be able to reward the content producers for their premium content and voting. This ongoing cycle will create a chain effect, thus attracting more contributors to the platform.

Why the TradeRiser project is considered so special and promising:

Maximum speed

Each client of the platform will be able to find the best trading opportunities, get answers to their questions, all information is based on professional solutions;

Opportunity for questions

If you want to get information about the cryptocurrency and trading segment, just describe your situation on the platform, the multilingual interface will allow you to get a quick and convenient answer;


Use statistics to create and test optimal trading strategies without relying on software developers and other intermediaries. You will be able to use the statistical calculations of experienced traders;

Be aware of all the events

Get only the latest news. Intelligent analysis of news and world events data and their impact on cryptocurrencies and traditional assets will allow you to get all the necessary information;

Warning system

If you are just starting your way in the world of trading, the system will constantly notify you about the emergence of new information, statistics and other important data.

Problems faced by newcomers to the segment

It is necessary to consider a number of pressing troubles that have not yet been optimal solutions:

Difficulty in analyzing financial data

The growth of the world wide web has led to innovation in search engines. This made the Internet more accessible and simple. However, the analysis of financial data remains a complex process in which beginners find it difficult to understand.

Closed access to professional research

Often, even experienced professionals spend a lot of time to find the necessary data. But the platform uses artificial intelligence to analyze requests and quickly find appropriate answers.

Too few promising trading strategies and ideas tested

Many modern companies are based only on old, proven strategies. They do not try to discover new ways - this leads to a lack of information for new traders.

The complexity of the research

Getting high-quality financial analysis is associated with huge time costs, which is why today it is difficult to find a lot of quality information.

The maximum inefficiency

Existing services collect only superficial reports, the accuracy of which is not confirmed. This leads to the provision of poor quality information to customers.

Abundance of unverified news and researches

Project developers focus on checking the proposed information, it allows you to weed out irrelevant news.

Platform Features

Community Edition :- This is comprised of many features that will be available to the community. They are as follows, the Research Assistant powered by the community data feed, ICO ratings, market condition analysis, ICO due diligence, investor portfolio analysis, direct trading, web and mobile app.

Research Marketplace – Accessible to Token holders

Enterprise Edition :- This standalone version is accessible to financial institutions, hedge funds or corporations. This includes our API.

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 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.

The 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 Distribution and Fund Distribution

● 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.



1 XTI = $0.07



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.


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

Meet The Amazing Team


Be a part of this incredible project. Download the whitepaper for the full scoop.

Till next time…

For more information, please visit:



LightPaper :


Telegram Group:

Bitcointalk ANN:

Author: TheMichaelMatch

My BitcoinTalk Profile:;u=1326035

ETHEREUM Address: 0x76CC93E01A6D810a1C11bBC1054C37CB395F14C8

Disclaimer: This article was published in terms of the bounty campaign. I am not a project team member or its representative but a supporter of this incredible project.

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