Evolution of bitcoin as a Financial Asset

The cryptocurrency market debate resumed in 2020 with renewed vigour as the price of Bitcoin surpassed late 2017 highs. This study aims to analyse possible factors of Bitcoin’s pricing at various cryptocurrency market development stages — before the 2017 price bubble, after and during the COVID-19 pandemic. The main method of analysis is a generalized autoregressive conditional heteroskedasticity model with conditional generalized error distribution (GARCHGED). Two groups of indicators are used as possible factors related to the Bitcoin dynamics. The first group consists of various quantitative indicators directly related to Bitcoin (the so-called internal factors) — the volume of exchange trade, the volume of transactions in the Bitcoin blockchain, the number of new and active wallets, hash rate, the sum of fees paid in the blockchain, as well as the dynamics of Google Trends search queries. The second group is the return on various financial assets — stock and bond indexes, commodities, and currency markets. The results of the analysis demonstrate the absence of a stable correlation between any of the factors under consideration and Bitcoin returns in all the periods that we focus on. In the period before the 2017 price bubble, the internal factors and Bitcoin returns showed generally co-directional dynamics, but the situation changed in 2018. In early 2021, the correlation between Bitcoin and traditional financial assets returns has increased significantly. We can conclude that Bitcoin is becoming a popular means of diversification as a high-risk asset, which, however, follows the pattern of a speculative bubble at the beginning of 2021. The increased demand for the need to invest in Bitcoin using various exchange-traded instruments (ETFs for cryptocurrencies) may soon lead to a further increase in the price of this cryptocurrency if such instruments are registered on the exchange.

Performance Analysis of Cryptographic Hash Functions Suitable for Use in Blockchain

A blockchain, or in other words a chain of transaction blocks, is a distributed database that maintains an ordered chain of blocks that reliably connect the information contained in them. Copies of chain blocks are usually stored on multiple computers and synchronized in accordance with the rules of building a chain of blocks, which provides secure and change-resistant storage of information. To build linked lists of blocks hashing is used. Hashing is a special cryptographic primitive that provides one-way, resistance to collisions and search for prototypes computation of hash value (hash or message digest). In this paper a comparative analysis of the performance of hashing algorithms that can be used in modern decentralized blockchain networks are conducted. Specifically, the hash performance on different desktop systems, the number of cycles per byte (Cycles/byte), the amount of hashed message per second (MB/s) and the hash rate (KHash/s) are investigated. The comparative analysis of different hashing algorithms allows us to choose the most suitable candidates for building decentralized systems type of blockchain.

A System Dynamics Model of Bitcoin: Mining as an Efficient Market and the Possibility of ‘Peak Hash’

The mining of bitcoin is modeled using a system dynamics model that represents both the mechanism of coin creation and the adjustment of the network hash rate based on the economic incentive of mining. The results show that the past evolution of the network hash rate can be explained, to a large extent, by an efficient market hypothesis applied to the mining of blocks. The possibility of a decreasing trend in the network hash rate from the halving event of May 2020 is exposed, implying that the network may be close to ’peak hash’ if the price of bitcoin and the revenues from transaction fees will be insufficient to cover the operational expenditures of mining.

ECCPoW: Error-Correction Code based Proof-of-Work for ASIC Resistance

Bitcoin is the first cryptocurrency to participate in a network and receive compensation for online remittance and mining without any intervention from a third party, such as financial institutions. Bitcoin mining is done through proof of work (PoW). Given its characteristics, the higher hash rate results in a higher probability of mining, leading to the emergence of a mining pool, called a mining organization. Unlike central processing units or graphics processing units, high-cost application-specific integrated circuit miners have emerged with performance efficiency. The problem is that the obtained hash rate exposes Bitcoin’s mining monopoly and causes the risk of a double-payment attack. To solve this problem, we propose the error-correction code PoW (ECCPoW), combining the low-density parity-check decoder and hash function. The ECCPoW contributes to the phenomenon of symmetry in the proof of work (PoW) blockchain. This paper proposes the implementation of ECCPoW, replacing the PoW in Bitcoin. Finally, we compare the mining centralization, security, and scalability of ECCPoW and Bitcoin.

IS BITCOIN BUSINESS INCOME OR SPECULATIVE FOOLERY? NEW IDEAS THROUGH AN IMPROVED FREQUENCY DOMAIN ANALYSIS

The present study addresses one of the most problematic phenomena: Bitcoin price. We explore the Granger causality for two relationships (Bitcoin price and trade transactions; Bitcoin price and investors' attractiveness) from a frequency domain perspective-based on unconditional and conditional data analysis. Accurately, this research empirically assesses the causal links between these variables unconditionally on the one hand and conditioning upon relevant control variables (recorded in literature) on the other hand. The observed outcomes reveal some differences with respect to the frequencies involved, highlighting the difficulty to reach clearer insights and better paths into this nascent crypto-currency. Beyond the nuances of short-, medium- and long-run frequencies, this paper confirms the extremely speculative nature of Bitcoin without overlooking its usefulness in economic reasons. The consideration of the Chinese market index, the hash rate, the monetary velocity and the estimated output volume has led to solid and meaningful findings connecting further Bitcoin to speculation.