# 2022-196

**Main objective**

The main objective is to implement “CryptoForeteller” to predict how the value of a crypto currency may change in the future. The main purpose of this is to give amateur as well as experienced crypto investors the opportunity to invest in crypto currency without any hesitation. The main objective here is to implement an application that can provide data with over 80% accuracy. Users can view the predicted values separately for each of these crypto currencies. Its predicted value as well as a trust score calculated by analyzing other users' opinions about the crypto currency can be obtained.



**Main Research questions**

One of the problems which most of the crypto researchers, traders and investors are facing today is selecting a good and reliable crypto currency project to invest out of more than 11,000 that exist. When defining a good and reliable currency there are many factors at stake. Initially investors will have to carry out a technical and fundamental analysis.Currently they will have to carry out the entire process manually by themselves or by paying someone else crypto currency price movements using charts and looking through the news related to the relevant coin/token along with the community ideas. Sometimes when that process is through it is too late because the predicted movement is already there.



**Individual research question**

* Wijethunga P.D.P. - Why community feedback is important for Cryptocurrency?
* Senavirathne D.R.E.S - Is cryptocurrency price movements predictable?





**Individual Objectives**

* Wijethunga P.D.P. - Generate and display a rate out of 10 by analyzing the community conversations, feedbacks and news using natural language processing and analyze whether it is good time to invest or sell the current holdings by using forecasted price and final overall score. This is being the complete sub objective two.
* Senavirathne D.R.E.S - Implement cryptocurrency price prediction using time series forecasting Methods along with feeding years of historical price movement data and training the system to be expert.
