University of Sussex
Browse
EJOR_2020.pdf (1.09 MB)

A general property for time aggregation

Download (1.09 MB)
journal contribution
posted on 2023-06-09, 20:07 authored by Carol AlexanderCarol Alexander, Johannes Rauch
We classify all functions of multivariate stochastic processes having time-series estimates that are independent of data frequency. Such an estimator applied to high-frequency data may be used to infer properties of estimates relating to low-frequency data. Our property encompasses two previously-proposed time-aggregation properties (with limited solutions) as different special cases. Our general time-aggregating functions satisfy a pair of coupled second-order partial differential equations. We derive analytic solutions for arbitrary-dimensional martingales and log-martingales. The time-aggregation property of a time-series model is similar – indeed time-aggregating functions always correspond to point estimators based on expected values – but we do not propose a specific new forecasting model. However, we do derive time-aggregating unbiased and efficient estimators for nth-order moments of log returns, applying these results to problems facing portfolio managers who re-optimise portfolios or hedge their risks at lower frequencies than the frequency at which their risk premia are monitored.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

European Journal of Operational Research

ISSN

0377-2217

Publisher

Elsevier

Issue

2

Volume

291

Page range

536-548

Department affiliated with

  • Accounting and Finance Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2020-01-07

First Open Access (FOA) Date

2022-01-12

First Compliant Deposit (FCD) Date

2020-01-07

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC