Khan, Asad ul Islam

Profil fotoğrafı
 E-posta Adresi
asad.khan@ihu.edu.tr
ORCID Profili
0000-0002-5131-577X
WoS Profili
AAJ-6453-2021
Scopus Profili
57204558870
YÖK Araştırmacı Profili
D34BC22808527E8F
Google Akademik Profili
IISCIjsAAAAJ&hl=tr&oi=ao
TR-Dizin Profili
0000-0002-5131-577X
SOBİAD Profili
311599
Web Sitesi
akademik.ihu.edu.tr/tr/asad-khan

Araştırma projeleri

Organizasyon Birimleri

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Organizasyon Birimi
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.

Adı Soyadı

Khan

İlgi Alanları

Solunum Sistemi, Genel ve Dahili Tıp, Çevre Bilimleri ve Ekoloji, İş Ekonomisi, Bilim ve Teknoloji

Kurumdaki Durumu

Aktif Personel

Filtreler

20242
Filtreleri Sıfırla

Ayarlar

Yazar: Özcan, Rasim × Konu: Crash Risk ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Yayın
    Stock market tumble sparks crypto chaos: A crash risk spillover analysis
    (Hungarian Central Statistical Office, 2024) Khan, Asad ul Islam; Özcan, Rasim; Abdul Rahman, Mutawakil; Waheed, Abdul; Yönetim Bilimleri Fakültesi, İktisat Bölümü
    The study employs an empirical Bayesian estimation approach to examine how the crash risk of the G-7 (United States [US], United Kingdom [UK], Japan, Germany, Canada, and France excluding Italy) and Chinese equity markets affects the crash risk of the top 11 cryptocurrencies. Two crash risk measures were adopted to determine the monthly crash risk of the two types of markets, which are the most appropriate for skewed returns. Four separate models were estimated using the empirical Bayes estimation method because it considers heterogeneity, is more efficient than least squares, and facilitates more accurate coefficient estimation. The results reveal that the German stock market's crash risks are significantly and contemporaneously associated with the crash risk of all 11 cryptocurrencies, indicating that the German equity market is not a reliable diversifier for cryptocurrencies. The crash risks of the US, UK, and Japanese (German and Canadian) equity markets have a positive (negative) impact on the crash risk of cryptocurrency markets with a one-month lag. Generally, lagged crash risks have a more substantial influence on cryptocurrency crash risk, suggesting that historical crashes in equity markets are better predictors of cryptocurrency crashes. The one-month significant delay effect may present arbitrage opportunities because the risk of crashes in stock markets may signal potential crashes in cryptocurrencies one month in advance. A series of robustness checks confirmed the results of the analysis and the validity of our conclusions. These findings suggest that crypto investors and policy-makers should pay attention to historical events in equity markets. Investors and portfolio managers in the cryptocurrency market should monitor unexpected fluctuations in the stock market, particularly significant declines that could result in significant losses in the future.
  • Küçük Resim
    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 Bölümü
    In 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.