Advanced Time Series Forecasting

This webinar will illustrate how to review historic data and use your knowledge of the system you are modeling to create more robust, credible forecasts that incorporate appropriate levels of uncertainty.

The webinar explains how to go about reviewing your data and the statistical tools and techniques that you can help reveal the underlying patterns. We will focus most on the thinking that underpins time series forecasting, using three different examples as illustration. Areas covered include:

How far forward you can forecast with a data set
Assessing the stability of past data and its relevance to a forecast
Visual review of past data
Assessing and modeling correlations between variable
Pearson v Spearman correlation
Forecasting actual values, log returns or simple returns
Review of some common financial model
Fitting distributions to movements
Building dependent forecasts using regression
Incorporating seasonality
Evaluating and incorporating lags (i.e. early indicators)
Adding bounds to forecast variables
Assessing and adding shocks to the system
Random event frequency modeling
Reliability of a system (modelling lifetime and failures)

About ModelRisk:
ModelRisk is the pre-eminent risk analysis tool for business, science, engineering and government. ModelRisk fully integrates with Microsoft Excel, automating Monte Carlo simulation in your Excel models so you can fully understand the risk and uncertainty involved in key decisions. ModelRisk uses simulation techniques to compare different decision options so you can select the ones that are most likely to succeed, and develop the most-cost effective strategy for reducing risk.

About Vose Software:
Vose Software designs, develops, sells and supports a range of quantitative risk analysis software. The products can be used independently to address specific risk issues, or integrated to provide a complete corporate risk management platform.