Related papers: Predictive analysis of Bitcoin price considering s…
This paper analyzes correlations and causalities between Bitcoin market indicators and Twitter posts containing emotional signals on Bitcoin. Within a timeframe of 104 days (November 23rd 2013 - March 7th 2014), about 160,000 Twitter posts…
The growing prominence of cryptocurrencies has triggered widespread public engagement and increased speculative activity, particularly on social media platforms. This study introduces a novel classification framework for identifying…
The rapid growth of the stock market has attracted many investors due to its potential for significant profits. However, predicting stock prices accurately is difficult because financial markets are complex and constantly changing. This is…
The objective of this research is to examine how sentiment analysis can be employed to generate trading signals for the Foreign Exchange (Forex) market. The author assessed sentiment in social media posts and news articles pertaining to the…
This paper introduces CryptoAnalytics, a software toolkit for cryptocoins price forecasting with machine learning (ML) techniques. Cryptocoins are tradable digital assets exchanged for specific trading prices. While history has shown the…
Currently, there is no consensus on the real properties of Bitcoin. The discussion comprises its use as a speculative or safe haven assets, while other authors argue that the augmented attractiveness could end accomplishing money's…
Stock market forecasting is very important in the planning of business activities. Stock price prediction has attracted many researchers in multiple disciplines including computer science, statistics, economics, finance, and operations…
In this paper we give an elementary analysis of economics of Bitcoin that combines the transaction demand by the consumers and the supply of hashrate by miners. We argue that the decreasing block reward will have no significant effect on…
Bitcoin is a cryptocurrency attracting a lot of interest both from the general public and researchers. There is an ongoing debate on the question of users' anonymity: while the Bitcoin protocol has been designed to ensure that the activity…
The research delves into the capabilities of a transformer-based neural network for Ethereum cryptocurrency price forecasting. The experiment runs around the hypothesis that cryptocurrency prices are strongly correlated with other…
We study the dependency and causality structure of the cryptocurrency market investigating collective movements of both prices and social sentiment related to almost two thousand cryptocurrencies traded during the first six months of 2018.…
Bitcoin, with its ever-growing popularity, has demonstrated extreme price volatility since its origin. This volatility, together with its decentralised nature, make Bitcoin highly subjective to speculative trading as compared to more…
Bitcoin is the first and undoubtedly most successful cryptocurrecny to date with a market capitalization of more than 100 billion dollars. Today, Bitcoin has more than 100,000 supporting merchants and more than 3 million active users.…
Digital currencies have become popular in the last decade due to their non-dependency and decentralized nature. The price of these currencies has seen a lot of fluctuations at times, which has increased the need for prediction. As their…
In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin…
Bitcoin, one of the major cryptocurrencies, presents great opportunities and challenges with its tremendous potential returns accompanying high risks. The high volatility of Bitcoin and the complex factors affecting them make the study of…
This paper presents a large-scale analysis of the cryptocurrency community on Reddit, shedding light on the intricate relationship between the evolution of their activity, emotional dynamics, and price movements. We analyze over 130M posts…
We study the problem of predicting whether the price of the 21 most popular cryptocurrencies (according to coinmarketcap.com) will go up or down on day d, using data up to day d-1. Our C2P2 algorithm is the first algorithm to consider the…
As machine learning ascends the peak of computer science zeitgeist, the usage and experimentation with sentiment analysis using various forms of textual data seems pervasive. The effect is especially pronounced in formulating securities…
A main focus in economics research is understanding the time series of prices of goods and assets. While statistical models using only the properties of the time series itself have been successful in many aspects, we expect to gain a better…