An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application

This paper employs a local information, nearest neighbour forecasting methodology to test for evidence of nonlinearity in financial time series. Evidence from well-known data generating process are provided and compared with returns from the Athens stock exchange given the in-sample evidence of nonlinear dynamics that has appeared in the literature. Nearest neighbour forecasts fail to produce more accurate forecasts from a simple AR model. This does not substantiate the presence of in-sample nonlinearity in the series.nearest neighbour, nonlinearity

Testing the assumption of Linearity

The assumption of linearity is tested using five statistical tests for the US and the Canadian unemployment rates. An AR(p) model was used to remove any linear structure from the series. Strong evidence in favour of non-linearity was found in the case of Canada. The result for the US is not so clear cut.non-linearity

Market Efficiency and the Euro: The case of the Athens Stock Exchange

The behaviour of an emerging market, the Athens Stock Exchange (ASE), after the introduction of the euro is investigated. The underlying assumption is that stock prices would be more transparent; their performance easier to compare; the exchange rate risk eliminated and as a result we expect the new currency to strengthen the argument, in favour of the EMH. The General ASE Composite Index and the FTSE/ASE 20, which consists of “high capitalisation” companies, are used. Five statistical tests are employed to test the residuals of the random walk model: the BDS, McLeod-Li, Engle LM, Tsay and Bicovariance test. Bootstrap and asymptotic values of these tests are estimated. Alternative models from the GARCH family (GARCH, EGARCH and TGARCH) are also presented in order to investigate the behaviour of the series. Lastly, linear, asymmetric and non-linear error correction models are estimated and compared.Non-Linearity, Market Efficiency, Random Walk, GARCH, non- linear error correction

Purchasing Power Parity and the European Single Currency: Some New Evidence

The effect of the single currency on the Purchasing Power Parity (PPP) hypothesis is examined in this study for the 15 EU countries, vis a vis the US dollar, before and after the advent of the euro. Standard as well as nonlinear unit root tests are employed on the time series dimension. Unit root tests reject PPP and the highest half-lives are observed after the introduction of the single currency. Panel unit root (Pesaran, 2007) and stationarity tests (Hadri and Kurozumi, 2008) that take into account cross-sectional dependence are also estimated. The results remain inconclusive as panel stationarity tests fail to support PPP whereas panel unit root tests fail to reject PPP for the whole sample and for the period before the introduction of the single currency.Purchasing Power Parity, half-life, nonlinear unit roots, panel unit roots, heterogeneity, cross-section dependence

Calendar Anomalies in an Emerging African Market: Evidence from the Ghana Stock Exchange.

This paper investigates two calendar anomalies in an emerging African market. Both the day of the week and month of the year effects are examined for Ghana. The latter is an interesting case because i) it operates for only three days per week during the sample period and ii) the increased focus that African stock markets have received lately both from academics and practitioners. We employ rolling techniques to asses the affects of policy and institutional changes. This allows deviations from the linear paradigm. We finally employ non-linear models from the GARCH family in a rolling framework to investigate the role of asymmetries. Contrary to a January return pattern in most markets, an April effect is found for Ghana. The evidence also shows the presence of the day of the week effects with asymmetric volatility performing better than the benchmark linear estimates. This seasonality though disappears when only the latest information is used (time-varying asymmetric GARCH). Our approach provides a new framework for investigating this well-known puzzle in finance.Calendar Anomalies, Non-Linearity, Market Efficiency, Asymmetric Volatility, Rolling windows.