In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficien...

This research is related to the usefulness of different machine learning methods in forecasting time series on financial markets. The main issue in this field is that economic managers and scientific society are still longing for more accurate forecasting algorithms. Fulfilling this request leads to an increase in forecasting quality and, therefore, more profitability and efficiency. In this pa...

This paper presents an investigation into the relationship between investment and savings in Australia over the period 1960-2007. Using four time series techniques our results reveal that the Feldstein-Horioka puzzle exists in a weak form with a lower saving retention coefficient. Granger Causality tests illustrate that savings Granger cause investment both in the short and long runs. Our resul...

We investigate the effects of a Financial Transaction Tax (FTT) in an order-driven artificial financial market. FTTs are meant to limit short-term speculative behavior by reducing the amount of excess liquidity in the system. To quantify these effects, adjustments in trading strategies and their effects on liquidity need to be taken into account. We model an agentbased continuous double-auction...