Development of Friedrich von Hayekʼs theory of private money and economic implications for digital currencies

Mikhaylov, Alexey

doi:10.18522/2073-6606-2021-19-1-53-62

Cited by 84 publications

(27 citation statements)

References 19 publications

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“…From Equation ( 23) it is straightforward that σ 2 < min σ 2 1 , σ 2 2 , which clearly states that, by applying this method, a better estimate of β it is obtained. Thus, the article shows that the expression Equation ( 4) can be substituted by a direct and more simple-to-compute form, given that the above-mentioned assumptions hold [33][34][35].…”

Section: Methodsmentioning

confidence: 99%

Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework

et al. 2021

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The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models for credit risk assessment. Forecasting coefficients yields a better model accuracy than a trivial approach of using computed past statistics parameters for the next time period. In this paper, a new method of dealing with time-varying parameters of scoring models is proposed, which is aimed at computing the default probability of a borrower. It was empirically shown that in a continuously changing economic environment factors’ influence on a target variable is also changing. Therefore, forecasting coefficients yields a better financial result than simply applying parameters obtained by accumulated statistics over past time periods. The paper develops a new theoretical approach, incorporating a combination of the ARIMA class model, the DCC-GARCH model and the state–space model, which is more accurate, than using only the ARIMA model. Rigorous simulation testing is provided to confirm the efficiency of the proposed method.

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Section: Methodsmentioning

confidence: 99%

Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework

et al. 2021

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“…Theoretical roots of the decentralization of money offered by today's digital currencies we can find even back in the seventies in the Friedrich von Hayek's theory of private money. Economic implications of the theory for digital currencies are investigated in the paper [21]. In the digital economy, cash can actually disappear and payments can centre on social and economic platforms, weakening traditional monetary policy channels.…”

Section: Cryptocurrencies-a Short Overviewmentioning

confidence: 99%

Cryptocurrency Portfolio Selection—A Multicriteria Approach

2021

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This paper proposes the PROMETHEE II based multicriteria approach for cryptocurrency portfolio selection. Such an approach allows considering a number of variables important for cryptocurrencies rather than limiting them to the commonly employed return and risk. The proposed multiobjective decision making model gives the best cryptocurrency portfolio considering the daily return, standard deviation, value-at-risk, conditional value-at-risk, volume, market capitalization and attractiveness of nine cryptocurrencies from January 2017 to February 2020. The optimal portfolios are calculated at the first of each month by taking the previous 6 months of daily data for the calculations yielding with 32 optimal portfolios in 32 successive months. The out-of-sample performances of the proposed model are compared with five commonly used optimal portfolio models, i.e., naïve portfolio, two mean-variance models (in the middle and at the end of the efficient frontier), maximum Sharpe ratio and the middle of the mean-CVaR (conditional value-at-risk) efficient frontier, based on the average return, standard deviation and VaR (value-at-risk) of the returns in the next 30 days and the return in the next trading day for all portfolios on 32 dates. The proposed model wins against all other models according to all observed indicators, with the winnings spanning from 50% up to 94%, proving the benefits of employing more criteria and the appropriate multicriteria approach in the cryptocurrency portfolio selection process.

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“…Thus, it is vital to compare the analytical values of banks and brokers in order to present data on organizations utilizing open innovations and those that do not. Two regression analyses were conducted in accordance with these assumptions [12][13][14][15][16].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some people assume that a Know Your Customer (KYC) score is the responsibility of validation nodes on the accessed network. Others represent more far-reaching changes, with identity management being a service offered independently of data validation [12,13]. In addition, there is a certain degree to which regulators are likely to require a perfect view of non-anonymized data in the ledger to exercise proper market surveillance and support anti-money laundering and terrorist financing processes [22][23][24][25].…”

Section: Literature Reviewmentioning

confidence: 99%

Digital Trading Applications and Bank Performance: Evidence from Russia

Lisin

Shvandar

Meynkhard

et al. 2021

Journal of Open Innovation: Technology, Market, and Complexity

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Digital trading apps are evidence of developing open innovations in the financial sector. The investment industry (including banks and brokers) can greatly benefit from the utilization of digital trading applications and corresponding tools, such as smart contracts. The goal of this research paper is to examine the possibility that brokers’ existing mobile apps outperform banks without mobile apps in the Russian financial sector. The efficiency of brokers is compared to banks in Russia. The results of these institutions’ activities are related to the number of profitable banks, which declines as a sign of high efficiency. The paper uses methods of t-test, linear and polynomial regression analysis between assets (dependent variable) and the profit to assets (independent variable) in Russia. The article finds the different directions of the utilization of the discussed technology, and they all share the consequential growth after the technology’s introduction. The paper also discusses the various areas of digital trading apps implementation and the future contributions for the Russian banking system and economy.

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Development of Friedrich von Hayekʼs theory of private money and economic implications for digital currencies

Cited by 84 publications

References 19 publications

Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework

Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework

Cryptocurrency Portfolio Selection—A Multicriteria Approach

Digital Trading Applications and Bank Performance: Evidence from Russia

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