Futures Open Interest and Speculative Pressure Dynamics via Bayesian Models of Long‐Memory Count Processes
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DOI: 10.1002/for.70001
Abstract: In this work, we develop time series regression models for long‐memory count processes based on the generalized linear Gegenbauer autoregressive moving average (GLGARMA) framework. We present a comprehensive Bayesian formulation that addresses both in‐sample and… read more here.
Keywords: memory count; long memory; speculative pressure; count ... See more keywords