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Filtering without Recursion and Some of Its Uses in Financial Economics

Simon Donker van Heel and Neil Shephard
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Simon Donker van Heel: Erasmus University Rotterdam
Neil Shephard: Harvard University

No 26-068/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We develop a filter for time series, defined at each time t as the minimizer of a discounted convex combination of observed and expected losses. The filter can be estimated by simulation to an arbitrary level of accuracy in O(1) flops at each time point t and can be run for all values t=1,...,T in parallel. These methods are applied to robustly compute a preaveraged price process from the more than 1.5 million trades made on a single financial asset in a single day where the noise's variance is infinite. It yields a flat ''volatility signature'' plot, down to the 1 second level, so the microstructure noise no longer biases the volatility estimate. This is not true when linear methods are employed.

Keywords: Filtering; High frequency finance; Loss function; M-estimator; Volatility (search for similar items in EconPapers)
Date: 2026-09-13
New Economics Papers: this item is included in nep-ets
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