We use weekly survey data on short-term and medium-term sentiment of German investors in order to study the causal relationship between investors' mood and subsequent stock price changes. In contrast to extant literature for other countries, a tri-variate vector autoregression for short-run sentiment, medium-run sentiment and stock index returns allows to reject exogeneity of returns. Depending...

This study forecasts trading signals of the Australian All Ordinary Index (AORD), one day ahead. These forecasts were based on the current day’s relative return of the Close price of the US S&P 500 Index, the UK FTSE 100 Index, French CAC 40 Index and German DAX Index as well as the AORD. The forecasting techniques examined were feedforward and probabilistic neural networks. Performance of the ...

In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at prices like any other commodity. As a result, deregulation of industry produced demand for wholesale organized marketplaces. Price predictions, are primarily meant to establish clearing price, have become significant ...

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passen...

<span>Load forecasting plays an essential role in power system planning. The efficiency and reliability of the whole can be increased with proper planning organization. Residential load is indispensable due to its increasing smart grid environment. Nowadays, meters deployed at residential level for collecting historical data consumption residents. Although employment ensures large availab...