I have started to look into modeling time series. One thing I can't understand is that all the models in the financial literature, such as GARCH and ARIMA, have the random walk as their base assumption. But if markets are assumed to be random from the onset, what good are models? Sure, they can be useful when pricing options and such, but they are useless for making accurate predictions on the time series itself. Am I right?

Philip McDonnell replies:

To an extent the premise of the question is true. Random walks are a pretty good model for markets. The purpose of time series analysis or any other is to detect subtle deviations from randomness. To the extent that the model is unable to detect deviations from randomness then a trader will not be able to profit from it except by luck alone.

The opportunities lie in the deviations from randomness. These can be identified by the model and their strength and statistical significance estimated. Significance testing always starts with the naive null hypothesis that the market is random and cannot be beaten. The burden of proof is upon the data to 'prove' that the null is incorrect and that the market can be beaten.


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