Predicting Hourly Bitcoin Prices Based on Long Short-term Memory Neural Networks

2021 | International Conference on Business Informatics | Citations: 0

Authors: Schulte, Maximilian; Eggert, Mathias

Abstract: Bitcoin is a cryptocurrency and is considered a high-risk asset class whose pric ... Expand

Abstract: Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movement s and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 %. Collapse

Topics: Bitcoin Twitter Python Tether Google+

Methods: longitudinal research seasonal autoregressive integrated moving average with exogenous regressor artificial neural network descriptive statistic sentiment analysis

Emotional reactions and coping responses of employees to a cyber-attack: A case study

2021 | International Journal of Information Management | Citations: 0

Authors: Stacey, Patrick; Taylor, Rebecca; Olowosule, Omotolani; Spanaki, Konstantina

Abstract: Cybersecurity is a serious threat to information technology (IT) systems, with m ... Expand

Abstract: Cybersecurity is a serious threat to information technology (IT) systems, with most organisations now relying on their IT systems to function day-to-day. Therefore, it is crucial that organisations ensure they are protected. This research investigates the emotional and coping responses of employees towards a cyber-attack. Data was collected through an in-depth case study approach (24 semi-structured interviews) conducted at a global manufacturing company, along with primary observations and a corpus of secondary materials. Our data analysis applied a grounded approach which was then refined using an emotion theoretic lens with the application of Technology Threat Avoidance Theory (TTAT). Drawing on structural appraisal theory, our findings indicate the IT security team in the case study oscillated between positive problem-focused coping and negative emotionfocused coping. A key explanatory feature or turnaround mechanism that mediated this oscillation was senior management empathy and resource mobilization. Building on the analyses, a conceptual model is developed called the Transformation of Coping through Empathic Leadership (T-CEL). The research suggests the crucial role that senior management play in transforming the emotional and coping capabilities of employees through their intervention and support. The study extends the IS Security theoretical background through a TTAT-lens for the analysis of cyber-attack incidents. Collapse

Topics: IT security IT security threat IT workforce electronic mail pseudonymity

Methods: qualitative interview case study personal interview conceptual modelling theory development

Theories: appraisal theory technology threat avoidance theory technology acceptance theory

Cryptocurrency price prediction based on multiple market sentiment

2020 | HICSS | Citations: 0

Authors: Wang, Yu; Chen, Runyu

Abstract: With the rapid development of the Internet, cryptocurrencies have been gaining i ... Expand

Abstract: With the rapid development of the Internet, cryptocurrencies have been gaining increasing amounts of attention dramatically. As a digital currency, it is not only used worldwide for online payments, but also traded as an investment tool on the market. Therefore, the ability to predict the price volatility will facilitate future investment and payment decisions. However, there are many uncertainties in the price movement of cryptocurrencies, and the prediction is extremely difficult. Collapse

Topics: cryptocurrency social media Tether Ethereum Bitcoin

Methods: computational algorithm experiment deep learning support vector machine machine learning