Range-based covariance estimation using high-frequency data: The realized co-range

We introduce the realized co-range, a novel estimator of the daily covariance between asset returns based on intraday high-low price ranges. In an ideal world, the co-range is five times more efficient than the realized covariance, which uses cross-products of intraday returns, when sampling at the same frequency. In Monte Carlo simulations, we find that for plausible levels of bid-ask bounce, infrequent trading and nonsynchronous trading, the realized co-range still improves upon the realized covariance. In a volatility timing strategy for S&P500, bond and gold futures, we find that the co-range estimates are less noisy, which results in lower transaction costs and higher Sharpe ratios.