2 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 2 / 2
Yayın Backcasting Bitcoin prices: implementation with ARCH & GARCH models(International Journal of Economics, Commerce and Management, 2024-12) Teker, Dilek; Teker, Suat; Demirel Gümüştepe, EsinBitcoin, the first decentralized cryptocurrency, has gained popularity among investors for several reasons. Its potential for high returns makes it attractive to those seeking alternatives to traditional investments. Bitcoin's volatility provides both risk and reward, drawing in speculative investors. Moreover, Bitcoin operates independently of central banks or governments, appealing to those wary of inflation and economic instability. As more businesses and financial institutions adopt Bitcoin as an investment tool and a medium of exchange, its appeal continues to grow. For institutional investors, Bitcoin offers a way to diversify portfolios amid low interest rates and geopolitical uncertainty. However, the volatility in Bitcoin markets tends to be a risk exposure, so developing models to understand Bitcoin fluctuations is crucial to determining more about market behavior. Accurate financial models help predict price movements, manage risk, and identify macroeconomic correlations. Given its complexity, these models are essential for long-term investors to navigate volatility and optimize their investment strategies. This research employs ARCH and GARCH models to forecast Bitcoin volatility. The outputs indicate that ARIMA is the best fit model that explains Bitcoin’s price fluctuations in the selected data period.Yayın Estimation of Bitcoin volatility: GARCH implementation(Seventh Sense Research Group, 2020-01) Teker, Dilek; Teker, SuatAs bitcoin has been a topic of high interest for academic and professional life over recent years, a number of literature has examined its price movements, volatility, and predictions. Bitcoin is the first and perhaps the most popular cryptocurrency with a high volatility pattern compared to the other cryptocurrencies. This paper examines the models that explain the volatility of Bitcoin prices. The daily data for the Bitcoin prices are used through a period of July 31, 2017, to April 3, 2019, with a total number of observations of 484. Initially, unit root tests are implemented. Then, the heteroskedasticity problem is tested among variables. Based on the results of the heteroskedasticity test, it is decided to use ARCH models. Then, ARCH, GARCH, TGARCH, and EGARCH results are tested to find out the best fit model that explains the bitcoin price movements.
