What is TradeRiser Project?

TradeRiser is an artificially intelligent Research Assistant, that can answer simple and complex trading questions. TradeRiser aims to become a single source of truth, that can provide instantaneous answers, to trading questions at a large scale. Specifically how the news and events affect asset prices around the world.

TradeRiser is solving the enormousness time spent by traders and investing when researching and trading the financial and crypto markets. We are doing this by providing an AI Research Assistant that can instantly answer both simple and complex trading questions. We using the blockchain to build an ecosystem of workers and reviewers that carry out machine learning tasks.

TradeRiser Technology:
Blockchain

The network software known as the blockchain, store information across a network of computers making them not just decentralized but distributed. This means no central authority owns the system. This storage of information and the collaboration on the network is based on rules often known as a smart contract. The Ethereum network [3] is a platform that enables the creation of peer-to-peer applications based on smart contracts. This allows developers to create cryptographically enforceable relationships. Thus, XTI will use smart contracts to provide the network infrastructure it needs, namely incentivizing financial analysts, content producers, and research consumers to interact in our environment through the use of a token.

Natural Language Processing

Natural language processing (NLP) is defined as the automatic or semi-automatic processing of human language.[4] NLP is essentially multidisciplinary: it is closely related to linguistics. It also has links to research in cognitive science, psychology, philosophy and maths. Within computer science, it relates to formal language theory, compiler techniques, theorem proving, machine learning and human-computer interaction. Nowadays it’s generally thought of as a huge part of AI and machine learning. Our Research Assistant relies heavily on NLP to address financial data questions and for organising and classifying news event data.

Artificial Intelligence trained by a Decentralized System

Artificial intelligent systems rely on data in order to build models to provide a function. The more quality of data, the better the model gets. Many financial professionals and independent traders all over the world have a wealth of knowledge and data, much of which remains private or unexercised. As explained earlier many trading ideas are not explored due to the barriers of entry. Models learned on data from a network of decentralised expertise hold the promise of greatly improving usability, by powering more intelligent applications.

Questioning and Answering System for Financial Data

At the heart of our Research Assistant is a questioning and answering system. Questioning and answering is another strand of NLP, and its name suggests it is the process of asking questions and getting answers. Most questioning and answering systems today are akin to information retrieval and extraction systems.[4] These systems attempt to find specific answer to a specific question from a set of documents, or at least a short piece of text that contains the answer.

Artificial Intelligence Today

Current work in machine learning has shown that larger models can dramatically improve overall performance [5]. With the advent of deep learning, the field is rapidly expanding. With data being at the heart of machine learning crowdsourcing the questions and answers necessary to train models and incentivize participation via a token-based network will ensure a much larger model.

Participants

The ecosystem can be seen as follows :

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.

Contribution from Independent Quantitative Research Analysts

The financial analysts will voluntarily provide question data, perform sanity checks and more, in order to train our machine learning research assistant. This regular contribution will make the platform smart and smart.

Question Data Production

Our Research Assistant will be trained to highlight new market events and impactful news trends that may be of significance to its users, and while making topical recommendations, based on past individual user behavior. This helps to prioritize certain query topics on an individual user-level basis that have a higher likelihood of relevance. These functionalities will especially be used by the community of financial analysts as starting point to guide them on what other forms of question data to train TradeRiser on.

Contribution from Independent Analysts Research Producers

Phase two of the ecosystem focuses on the inclusion of content producers. Content producers will use analytics built into TradeRiser to create their own reports and commentary for the “Research Marketplace” section within the platform. Research consumers may choose to subscribe to this feature and be charged a variable fee of XTI relative to what content they consume.

Token Sales Details:
TradeRiser is also set to list their native token in the form of XTI coin. Research consumers will need to hold the XTI token to gain access the features of the research marketplace and community edition. Additionally, XTI token holders will have the benefit of higher voting power and greater access too.

Parameters Of The ICO

Pre-ICO – Period- May, 2018 till June 2018
ICO – Period- TBA
Ticker- XTI
Platform- Ethereum
Model- ERC20
Payment methods- BTC, ETH
Token supply- 500,000,000 XTI
Pre-ICO value- 1 XTI= $0.07
ICO round value- 1 XTI=$0.10
Crowdsale target- $23,000,000
Distribution Plan

Crowd sale- 50%
Founders, advisors and employees- 25%
Community ecosystem incentivization- 15%
Bounty and referrals- 5%
Strategic Partnerships and future development- 5%
For more information:

Website: https://www.traderiser.com/

Whitepaper: https://www.traderiser.com/sites/default/files/TradeRiser_WhitePaper.pdf

Telegram: https://t.me/joinchat/traderiser

Twitter: https://twitter.com/traderiser/

Facebook: hhttps://www.facebook.com/TradeRiser-157017521786333/

Author: tinhkhuat

Bitcointalk Profile: https://bitcointalk.org/index.php?action=profile;u=1885373