• Bootstrap;
  • Financial time series;
  • Heteroscedastic models;
  • Smoothing;
  • Statistical graphics;
  • Stochastic volatility models;
  • Volatility


The paper develops a framework for volatility graphics in financial time series analysis which allows exploration of the time progression of volatility and the dependence of volatility on past behaviour. It is particularly suitable for identifying volatility structure to be incorporated in specific volatility models. Plotting techniques are identified on the basis of a general time series volatility model and are illustrated on the Financial Times Stock Exchange 100-Share Index financial time series. They are statistically validated by bootstrapping and application to simulated volatile and non-volatile series, generated by both conditionally heteroscedastic and stochastic volatility models. An important point is that volatility can only be properly visualized and analysed for linearly uncorrelated or decorrelated series.