Pujie Crypto: Intelligent Artificial Research Assistant, Who Can Answer Simple Questions and Complex Trading Questions

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.

INTRODUCE TRADERISER

SPEED
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.

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PROBLEM

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 financial data analytics, have not enjoyed the same level of simplicity and accessibility across the web world. The growth of large data can not be stopped, financial companies and individuals alike are in the race to find trade opportunities. This task will only become more difficult as new avenues of data are found, humans will struggle to keep up. Decide on this accessibility and everywhere presents great opportunities, for systems that seek to democratize the analytics of financial data.

Interfere with Human Intensive Research

TradeRiser builds an AI-based Research Assistant, which can answer simple questions and 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 is usually time consuming, inefficient, vulnerable to information overload and requires a lot of manpower. These problems are exacerbated by the emergence of cryptocurrency and financial professionals who want to trade it, in addition to traditional securities. Rapid explosion of cryptocurrency has left many other technologies catching up, individual traders need an easy way to analyze these asset classes.

Fewer Ideas Tested

The current platform relies on excellent technical knowledge to test trade ideas, and because fewer entry barriers trade ideas are tested. Every day a portfolio manager has an investment idea and should go to quant to build a model. That's the bottleneck in most financial services firms, and as a result, far fewer ideas are being tested. The same is true of each merchant who wants to test ideas but does not have access to enough tools.

Time-Consuming

Quantitative research can be a very time consuming process, as it requires a lot of steps to complete, sometimes covering several days and hours. Other bottlenecks include the computation process due to the amount of data being analyzed.

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.

Information Overload

With data being a new "oil" or a valuable resource, the work of analysts is even more difficult in trying to process the data. New paths of data continue to creep up can potentially be exploited in financial research, especially unstructured data.

News and Events - Unstructured Data

It is well known that news and world events have an impact on financial markets, for this reason tools such as economic reporting calendars and income are created. These tools allow merchants to follow and monitor impacted events, but there is a basket of unregulated world events to be included 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 need to be tamed and structured.

Solution

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 their data question set, data validation, accuracy checks, suggestions, and sample reporting. Financial analysts can contribute in these ways to help us train our Engineer Assistant engine, and are compensated accordingly. XTI is the basic mechanism used to facilitate this ecosystem, and gives XTI holders with direct participation in advancing our "single truth source" to question and answer the system.

TradeRiser XTI

Token Distribution Name