This paper analyses the explanatory power of the frequency of abnormal returns in the FOREX for the EURUSD, GBRUSD, USDJPY, EURJPY, GBPCHF, AUDUSD and USDCAD exchange rates over the period 1994-2019. Abnormal returns are detected using a dynamic trigger approach; then the following hypotheses...

This paper examines the day of the week effect in the crypto currency market using a variety of statistical techniques (average analysis, Student's t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) as well as a trading simulation approach. Most crypto...

This paper examines the day of the week effect in the crypto currency market using a variety of statistical techniques (average analysis, Student's t-test, ANOVA, the Kruskal- Wallis test, and regression analysis with dummy variables) as well as a trading simulation approach. Most crypto...

This paper analyses the explanatory power of the frequency of abnormal returns in the FOREX over the period 1994-2019. The following hypotheses are tested: frequency of abnormal returns is asignificant driver of price movements (H1); it does not exhibit seasonal patterns (H2); it is stable over...

This paper analyses the long-memory properties of high frequency financial time series. It focuses on temporal aggregation and the influence that this might have on the degree of dependence of the series. Fractional integration or I(d) models are estimated with a variety of specifications for...

This paper focuses on nominal exchange rates, specifically the US dollar rate vis-à-vis the Euro and the Japanese Yen at a daily frequency. We model both absolute values of returns and squared returns using long-memory techniques, being particularly interested in volatility modelling and...

This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a...

This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a...