Dek A. Cryptocurrency market agents' behaviour modelling

The thesis is focused on the cryptocurrency market agents’ behaviour modelling. The concepts of economy and society informatisation are considered in the research. The term “cryptoeconomy” is used for designating the emerging industry related to cryptocurrencies, distributed ledger technology, and strong cryptography. The main components of cryptoeconomy, including the public ledger, blockchain, consensus algorithms, smart contracts, digital money, and cryptocurrencies are considered. Several understudied research questions were identified. One of the questions is the estimation of mining electricity consumption. Miners' equipment selection decisions affect global network characteristics such as average transaction speed and fee, hashrate and associated electricity consumption, and the corresponding carbon footprint. Another insufficiently researched issue is the influence of information from social networks and subjective judgments on the decision-making of economic agents on the buying or selling of cryptocurrency, the expediency of mining under given conditions, the feasibility of investing in projects. The following tasks were solved in the thesis: the concepts of information economy were analyzed; the relationship between these concepts and cryptoeconomy was identified; the information sources that can be used to model the behaviour of cryptocurrency market agents were explored; the model of bitcoin mining electricity consumption was developed; the environmental impact of mining was evaluated; rationality of cryptocurrency experts and traders was studied by the means of “Guessing Game”; based on information obtained from the orders database and traders’ answers in the Guessing Game, behavioural patterns were identified; the model of bitcoin time series was improved by taking into the account factual and conceptual internet content. Keywords: behaviour modelling, cryptocurrency, bitcoin, mining, trading, experimental economics, behaviour finance, bitcoin electricity consumption, mining carbon footprint, neural networks, natural language processing, guessing game, clustering.