Modeling cryptocurrencies volatility using GARCH models: a comparison based on Normal and Student's T-Error distribution

Salamat, Shazia; Niu, Lixia; Naseem, Sobia; Mohsin, Muhammad; Rehman, Muhammad Zia ur; Baig, Sajjad Ahmad

doi:10.9770/jesi.2020.7.3(11)

Cited by 15 publications

(11 citation statements)

References 14 publications

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“…After taking the first differences, both conditional series have shown a 1 and 5% level of significance for all variables. The last column has contained the order of integration in which I represent the integrated order of variables (Johansen, 1992;Cheung and Lai, 1995;Mohsin et al, 2020a;Salamat et al, 2020). The numeric values 0 and 1 are used for level and first difference.…”

Section: Resultsmentioning

confidence: 99%

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

2021

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The rapid worldwide spread of COVID-19 forced many countries to enforce complete lockdown and strict quarantine policies. The strict lockdown and quarantine affect the psychological state of people toward cryptocurrency. The current research aims to examine the effect of COVID-19 on Bitcoin prices concerning cumulative deaths and confirmed cases. The research comprises daily data from January 20, 2020, to April 30, 2020, during the initial worldwide breakout of COVID-19. This research employed the augmented Dickey-Fuller test to check the stationarity of data, the co-integration test for the interdependency of variables, and the vector error correction model for identifying the direction and long or short-run relationship between Bitcoin prices and COVID-19. The research results show that Bitcoin prices are negatively significant and related to COVID-19 in the short-run. A unidirectional relationship between Bitcoin prices and cumulative deaths is also observed. Investors and the public’s psychological state were positively significant to Bitcoin prices in the long-term because of cashless transactions, unbanked, and less risky virus traveling. The second reason behind the positive psychological relation is un-centralization and easy-to-make payments by Bitcoin. This study’s finding provides timely evidence to decision-makers on Bitcoin price volatility and its impacts on the public’s psychological states regarding COVID-19.

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Section: Resultsmentioning

confidence: 99%

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

2021

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“…Again, the fake news of social media restricted the general public from accepting the vaccine of COVID-19. The useful information and encouraging vaccine material are rare on social media than negative and discoursing materials (Salali and Uysal, 2020;Madison et al, 2021;Murphy et al, 2021). Hence, we proposed the following hypothesis:…”

Section: Moderating Role Of Covid-19 Vaccinementioning

confidence: 99%

“…Frenkel et al (2020) indicated that once the WHO complained that social media organizations have been spreading false information over COVID-19 worldwide; few social media groups used their platforms to spread incorrect data and tried to remove it. A recent study described the effect of media on the health of people ( Mohsin et al, 2020b ; Salamat et al, 2020 ; Naseem et al, 2021 ; Sarfraz et al, 2021 ). Muwahed (2020) stated that social media had affected the shocking crisis over some countries while many people have been greedy for buying foodstuff and household things because of the widespread fear of COVID-19.…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Social Media Digitalization and Coronavirus Disease 2019 Fear Among Service Sector Employees

et al. 2021

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In the age of digitalization, social media has played a significant role in quickly spreading the news about current affairs. From December 2019 to now, coronavirus disease 2019 (COVID-19), with its several mutated shapes, has more transmissible potential catastrophe and has become a severe phenomenon issue worldwide. The international spread of the epidemic has created fear among people, especially employees working physically in different organizations. The present research aimed to measure the impact of social media on its users in the China. The social media users more often were influenced by shocking news instructively and destructively. The research analysis was based on service sector employees and data collected from 630 respondents via a structured questionnaire. This research was confirmed the negative impact of fear on social media on the performance of employees. This research was also confirmed the moderation impact of the COVID-19 vaccine on the relationship between social media fear and employee performance. This research recommends that the China Censor Board checked the news and its validity to reduce the fear of COVID-19 among employees. This research will become a roadmap for organizations and media controllers to understand the impact of social media during an intense situation. The telecommunication sector will reduce psychological disease and enhance the work capability of employees by controlling unnecessary and unapproved material about sensitive issues.

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“…Moreover, among several unique properties, [40] found that cryptocurrencies have leverage effects and Student's t error distributions. The study [41] uses the symmetric (GARCH 1,1) and asymmetric (EGARCH, TGARCH and PGARCH) models to measure the volatility of cryptocurrencies. The results prove again the high volatility of cryptocurrencies and in most cases, the asymmetric PGARCH with Student's t distribution provides a better fit.…”

Section: Data and Criteriamentioning

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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Modeling cryptocurrencies volatility using GARCH models: a comparison based on Normal and Student's T-Error distribution

Cited by 15 publications

References 14 publications

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

Examining the Psychological State Analysis Relationship Between Bitcoin Prices and COVID-19

The Relationship Between Social Media Digitalization and Coronavirus Disease 2019 Fear Among Service Sector Employees

Cryptocurrency Portfolio Selection—A Multicriteria Approach

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