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2.6 Summary

Financial data display unique characteristics known as stylized facts, with the most prominent ones including:

• Lack of stationarity: The statistics of financial data change over time significantly and any attempt of modeling will have to continuously adapt.

• Volatility clustering: This is perhaps the most visually apparent aspect of financial time series. There is a myriad of models in the literature that can be utilized for forecasting (covered in Chapter 4).

• Heavy tails: The distribution of financial data is definitely not Gaussian and this constitutes a significant departure from many traditional modeling approaches (covered in Chapter 3).

• Strong asset correlation: The goal in investing is to discover assets that are not strongly correlated, which is a daunting task due to the naturally occurring strong asset correlation.