Journal of Economics and Financial Analysis

1-27

Authors: Yhlas Sovbetov

This paper examines factors that influence prices of most common five cryptocurrencies such as Bitcoin, Ethereum, Dash, Litecoin, and Monero over 2010-2018 using weekly data. The study employs ARDL technique and documents several findings. First, cryptomarket-related factors such as market beta, trading volume, and volatility appear to be significant determinant for all five cryptocurrencies both in short- and long-run. Second, attractiveness of cryptocurrencies also matters in terms of their price determination, but only in long-run. This indicates that formation (recognition) of the attractiveness of cryptocurrencies are subjected to time factor. In other words, it travels slowly within the market. Third, SP500 index seems to have weak positive long-run impact on Bitcoin, Ethereum, and Litcoin, while its sign turns to negative losing significance in short-run, except Bitcoin that generates an estimate of -0.20 at 10% significance level. Lastly, error-correction models for Bitcoin, Etherem, Dash, Litcoin, and Monero show that cointegrated series cannot drift too far apart, and converge to a long-run equilibrium at a speed of 23.68%, 12.76%, 10.20%, 22.91%, and 14.27% respectively.

61-85

Authors: Ahmad Sahyouni, Man Wang

Using a panel data set of 4995 banks across 11 developed and emerging countries during the period (2011-2015), this report analyses the amount of liquidity created by banks, how liquidity creation, bank-specific and the macroeconomic factors affecting bank profitability. The results show evidence of increased creation of liquidity over the period. By applying the panel data fixed effect technique, banks that create more liquidity, are set up to have lower profitability. As well as, Asset management, bank size and capital ratio are positively correlated with bank profitability. While, credit quality and operating efficiency affect bank’s profits negatively. Additionally, macroeconomic factors have different impact on profitability indicators in each market. Our findings may help decision makers inside and outside bank to determine important factors affecting bank profitability.

105-120

Authors: Mohamed Chikhi, Ali Bendob

This paper analyses cyclical behaviour of Orange stock price listed in French stock exchange over 01/03/2000 to 02/02/2017 by testing the nonlinearities through a class of conditional heteroscedastic nonparametric models. The linearity and Gaussianity assumptions are rejected for Orange Stock returns and informational shocks have transitory effects on returns and volatility. The forecasting results show that Orange stock prices are short-term predictable and nonparametric NAR-ARCH model has better performance over parametric MA-APARCH model for short horizons. Plus, the estimates of this model are also better comparing to the predictions of the random walk model. This finding provides evidence for weak form of inefficiency in Paris stock market with limited rationality, thus it emerges arbitrage opportunities.