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Yayın Fintech adoption in Pakistan: Mobile Wallet Service (MWS) over GDP causality evidence for pre and post COVID-19(Kinnaird College for Women, 2023) Latif, Muhammad Nouman; Özcan, Rasim; Özcan, RasimThis paper aims to analyze the use of mobile wallet services in Pakistan and how they affect both the economy and people's daily lives. Socioeconomically disadvantaged households in Pakistan will swiftly use mobile wallet services due to the increasing adoption of technology. Socioeconomic considerations are the most commonly used criterion for determining whether someone is underbanked or unbanked. We used data on mobile wallet services (MWS) and GDP from the State Bank of Pakistan for the period of 2013 to 2022. We conducted a causality test to ascertain the relationship between Pakistan's GDP and mobile wallet service. We discovered that the relationship between mobile wallet service and GDP is unidirectional. We then conducted an ordinary least square regression analysis, and the findings showed a positive correlation between GDP and mobile wallet service, confirming the causality. Because it is incredibly user-friendly and convenient for clients, it demonstrates that this service attracts attention from the public. Many low-income individuals use it, especially during the COVID-19 pandemic, as opposed to using standard banking systems. We recommend that financial literacy initiatives be taken seriously in order to promote equal financial inclusion in the economy. Mobile wallet users should be encouraged to keep using the service in order to aid the government in revenue mobilization. Additionally, it prevents the movement of illicit funds or fraudulent activity in the financial sector.Yayın Whether the crypto market is efficient? Evidence from testing the validity of the efficient market hypothesis(Bank Indonesia Institute, 2024) Özcan, Rasim; Khan, Asad ul Islam; Iftikhar, Sundas; Khan, Asad ul Islam; Özcan, Rasim; İnsan ve Toplum Bilimleri Fakültesi, İktisat BölümüThis study examines the validity of the efficient market hypothesis for the cryptocurrency market. We use the Exponential Generalized Autoregressive Conditional Heteroscedastic approach to examine the presence of different calendar anomalies i.e., the Halloween effect, the day-of-the-week (DOW) effect, and the month-of-the-year effect in the case of Bitcoin, Ethereum, XRP, Tether, and USD Coin. The findings show that there is no strong evidence of the Halloween effect. We find only robust Thursday and Saturday effects in the mean equation. In the case of the month-of-the-year effect, there is only a reverse January effect. More specifically, we note that April and February are statistically significant in the case of Bitcoin and Ethereum, respectively. Results obtained from the variance equations imply that September and October are the least risky months for investors.