ETF Basket-Adjusted Covariance estimation

A-Tier
Journal: Journal of Econometrics
Year: 2023
Volume: 235
Issue: 2
Pages: 1144-1171

Authors (4)

Boudt, Kris (Universiteit Gent) Dragun, Kirill (not in RePEc) Sauri, Orimar (not in RePEc) Vanduffel, Steven (Vrije Universiteit Brussel)

Score contribution per author:

1.005 = (α=2.01 / 4 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The increase in trading frequency of Exchanged Traded Funds (ETFs) presents a positive externality for financial risk management when the price of the ETF is available at a higher frequency than the price of the component stocks. The positive spillover consists in improving the accuracy of pre-estimators of the integrated covariance of the stocks included in the ETF basket. The proposed ETF Basket-Adjusted Covariance (BAC) equals the pre-estimator plus a minimal adjustment matrix such that the covariance-implied stock-ETF covariation equals a target value. We focus on a truncated pre-averaged version of the (Hayashi and Yoshida, 2005) pre-estimator and derive the asymptotic properties of its implied stock-ETF covariation. The simulation study confirms that the accuracy gains are substantial in all cases considered. In the empirical part of the paper, we show the gains in tracking error efficiency when using the BAC adjustment to construct portfolios that replicate a broad index using a subset of stocks.

Technical Details

RePEc Handle
repec:eee:econom:v:235:y:2023:i:2:p:1144-1171
Journal Field
Econometrics
Author Count
4
Added to Database
2026-01-24