Forecasting in finance: How sentiment analysis can make forecasting models more effective
Date: 18 November 2015
Time: 2pm to 3pm
We are very sorry to announce that this webinar has been cancelled. We hope to reschedule our webinar on the use of sentiment analysis in forecasting early next year.
Join Professor Neil Kellard for this webinar as he asks: Does the use of sentiment and search engine data help when using forecasting models in finance?
Sentiment analysis, or investor beliefs and feelings about the future direction of an asset price have been shown to improve the forecasting ability of models, for example using data from Google Search Volume Index.
Focusing on forecasting markets such as the FTSE100, the $US/Euro rate and the oil price, this webinar will consider both short-term forecasts (i.e., daily and intra-day) and long term forecasts (i.e., several years). Professor Neil Kellard will show that while other data are also useful in helping model and forecast prices, measures of sentiment and investor attention are likely to be more potent particularly in the short-term.
Aimed at analysts with a working knowledge of forecasting, this webinar will concentrate on sentiment and search engine data and how they can be used to enhance forecasting models. EViews will be used in the demonstration, however the models that will be shown can also be programmed in Matlab, R or Gauss.