Khan, Asad ul Islam
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Yönetim Bilimleri Fakültesi, İktisat Bölümü
İktisat Bölümü, başta Türkiye ve çevre ülkeler olmak üzere küresel ekonomileri anlayan, var olan sorunları analiz ederken, iktisadi kuramları ve kavramları yetkin ve özgün bir şekilde kullanma becerisine sahip bireyler yetiştirmeyi amaçlamaktadır.
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Khan
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Solunum Sistemi, Genel ve Dahili Tıp, Çevre Bilimleri ve Ekoloji, İş Ekonomisi, Bilim ve Teknoloji
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Yayın Threat of intervention in cryptocurrency market: West side story of Bitcoin and Ripple(Bucharest University of Economic Studies, 2023) Aysan, Ahmet Faruk; Isac, Nicoleta; Drammeh, Ousman; Khan, Asad ul Islam; Özcan, Rasim; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study examines the impact of intervention threats on the price and volume volatility of Bitcoin and XRP. Using the Threshold or GJR-GARCH model, we analyse the relationship between news shocks (representing intervention threats) and the volatilities of Bitcoin and XRP price and volume returns, based on data from January 2014 to April 2021. The results indicate a significant association between news shocks and Bitcoin's price volatility, suggesting that intervention-related news events have a notable impact. However, the relationship between news shocks and XRP's price volatility is insignificant. Notably, XRP's volume returns demonstrate a positive and significant relationship with news shocks, while Bitcoin's volume returns do not exhibit a significant relationship. Additionally, past shocks and conditional variance shocks significantly contribute to the volatility of today's price or volume returns. These findings suggest that Ripple (XRP) may benefit from the implicit threat of intervention, strategically managing its availability to control price surges.Yayın Unravelling crash risk transmission: Cryptocurrency impact on stock markets in G-7 and China(Johar Education Society Pakistan, 2024) Khan, Asad ul Islam; Özcan, Rasim; Ibrahim, Mahat Maalim; Yönetim Bilimleri Fakültesi, İktisat BölümüIn this paper, we use the Empirical Bayes estimation and multiple linear regression approach to examine the impact of the top 5 cryptocurrencies’ crash risks on the G-7 and China equity markets’ crash risks. MATLAB was used to calculate the crash risks, while Stata software was employed for the econometric analysis. Three crash risk measures are used to validate the robustness of the results: (i) the relative frequency of the number of crash days in the market, (ii) the monthly returns’ skewness, and (iii) the down-to-up volatility. Our findings indicate that overall crash risks of the top 5 cryptocurrencies are positively related with G-7 and Chinese stock markets’ crash risk. This suggests that the crash risk transmits from the crypto to the equity markets and the crashes in crypto can serve as a predictor in the stock markets. Furthermore, there is a negative correlation between the historical crash risks of the G-7 stock market and the present crash risks of the same stock market. This suggests that past stock market crashes can serve as a predictive factor for assessing the current risk of a stock market crash.