Model-free quantification of time-series predictability.

@article{Garland2014ModelfreeQO,
  title={Model-free quantification of time-series predictability.},
  author={Joshua Garland and Ryan G. James and Elizabeth Bradley},
  journal={Physical review. E, Statistical, nonlinear, and soft matter physics},
  year={2014},
  volume={90 5-1},
  pages={
          052910
        }
}
This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data, which results from the dimension, nonlinearity, and nonstationarity of the generating process, as well as from measurement issues such as noise, aggregation, and finite data length, is both empirically quantifiable and directly correlated with predictability. In particular, we argue that… 

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