In this paper, we present a new method for modeling time-evolving correlation networks, using a Mean Reversion Autoregressive Model, and apply this to stock ...
A new method for modeling time-evolving correlation networks, using a Mean Reversion Autoregressive Model, is presented, and it is suggested that the model ...
In: Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, ...
It provides coverage of seasonal decomposition, mean reversion, heavy- tailed distributions, exponential smoothing, spike preprocessing, autoregressive time ...
Benefits of Correlation Network Evolution: Enhanced Returns: Exploiting mean reversion can lead to higher returns by identifying assets that are temporarily out ...
Missing: Autoregression. | Show results with:Autoregression.
It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time ...
C Ye. University of York, 2016. 3, 2016. Correlation network evolution using mean reversion autoregression. C Ye, RC Wilson, ER Hancock. Structural, Syntactic ...
We focus in this paper on predi... Cite · Request full-text · Correlation Network Evolution Using Mean Reversion Autoregression. Conference Paper. Nov 2016.
The main purpose of this paper is to study pairs trading rules under mean-reversion models coupled with a two-state Markov chain. In particular, we consider an ...
In this paper, we present a new method for modeling time- evolving correlation networks, using a Mean Reversion Autoregressive Model, and apply this to stock ...