This paper provides some new empirical evidence on the weekend effect, one of the most recognized anomalies in financial markets. Two different methods are used: (i) a trading robot approach to examine whether or not there is such an anomaly giving rise to exploitable profit opportunities by...

One of the leading criticisms of the Efficient Market Hypothesis (EMH) is the presence of so-called “anomalies”, i.e. empirical evidence of abnormal behaviour of asset prices which is inconsistent with market efficiency. However, most studies do not take into account transaction costs. Their...

This paper examines long-term price overreactions in various financial markets (commodities, US stock market and FOREX). First, t-tests are carried out for overreactions as a statistical phenomenon. Second, a trading robot approach is applied to test the profitability of two alternative...

This paper provides some new empirical evidence on the weekend effect (one of the best known anomalies in financial markets) in Ukrainian futures prices. The analysis uses various statistical techniques (average analysis, Student's t-test, dummy variables, and fractional integration) to test for...

This paper examines short-term price reactions after one-day abnormal price changes and whether they create exploitable profit opportunities in various financial markets. A t-test confirms the presence of overreactions and also suggests that there is an "inertia anomaly", i.e. after an...

This paper investigates the degree of persistence of market fear. Specifically, two different long-memory approaches (R/S analysis with the Hurst exponent method and fractional integration) are used to analyse persistence of the VIX index over the sample period 2004-2016, as well as some...

This paper examines persistence in the cryptocurrency market. Two different longmemory methods (R/S analysis and fractional integration) are used to analyse it in the case of the four main cryptocurrencies (BitCoin, LiteCoin, Ripple, Dash) over the sample period 2013-2017. The findings indicate...

This paper investigates persistence in financial time series at three different frequencies (daily, weekly and monthly). The analysis is carried out for various financial markets (stock markets, FOREX, commodity markets) over the period from 2000 to 2016 using two different long memory...

This paper examines the degree of persistence in the volatility of financial time series using a Long Memory Stochastic Volatility (LMSV) model. Specifically, it employs a Gaussian semiparametric (or local Whittle) estimator of the memory parameter, based on the frequency domain, proposed by...

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...