Causality Detection on US Mutual Fund Movements using Evolutionary Subset Time-Series
In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including full-order models) with a forgetting factor and a constant term, using the exact-windowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias...[Show more]
|Collections||ANU Research Publications|
|Source:||International Journal of Services and Standards|
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