A Predictive Model for the Global Cryptocurrency Market Minul Wimalagunaratne, Guhanathan Poravie Informatics Institute of Technology, Sri Lanka

The Cryptocurrency Market, 2017 1315 crypto-coins US $300 billion market cap The Dominance of Bitcoin Market Dominance: 56.5% All time high: $10500 24hr Trading Volume $12 billion

International Conference on Innovations in Infobusiness and Technology Background Extreme Volatility “In a short period of time, it [the cryptocurrency market] can reach all-time highs and crash, repeatedly, seemingly out of nowhere” (Bamburic, 2017) Key Stakeholders Miners Investors Traders International Conference on Innovations in Infobusiness and Technology

Significance of the Research A solution for predicting prices for Bitcoin as well as Altcoins, which takes into consideration technological methodologies and multiple market factors in the form of a hybrid approach. Talk about stake holders International Conference on Innovations in Infobusiness and Technology

Factors that can be used to predict the price of Cryptocurrency Public Perception Trading Information Historic Information Trading Volume: opening price, closing price, trading volume Historic price: patters in prices International Conference on Innovations in Infobusiness and Technology

Capturing the Public Perception through Sentiment Analysis Scraping blogs/ communities Social Media To capture the aspect of public perception. International Conference on Innovations in Infobusiness and Technology

Manipulating Trading Information Through Machine Learning Using trading volume Identify patterns in using historic price data Changes of price in Bitcoin affecting Altcoins International Conference on Innovations in Infobusiness and Technology

Proposed System API’s of Online Exchanges API’s of Social Media Machine learning Sentiment Analysis Prediction Price prediction of BTC and Altcoins International Conference on Innovations in Infobusiness and Technology

International Conference on Innovations in Infobusiness and Technology Thank You! Acknowledgments Special thanks to Mr. Guhanathan Poravie for the assistance and guidance provided. International Conference on Innovations in Infobusiness and Technology