Systematic staleness (with Davide Pirino and Roberto Reno') (paper)

Journal of Econometrics, 2024, 238.

Asset prices are stale. We define a measure of systematic (market-wide) staleness as the percentage of small price adjustments over multiple assets. A notion of idiosyncratic (asset-specific) staleness is also established. For both systematic and idiosyncratic staleness, we provide a limit theory based on joint asymptotics relying on increasingly-frequent observations over a fixed time span and an increasing number of assets. Using systematic and idiosyncratic staleness as moment conditions, we introduce novel structural estimates of systematic and idiosyncratic measures of liquidity obtained from transaction prices only. The economic signal contained in the latter is assessed by virtue of suitable metrics.

Zeros (with Aleksey Kolokolov, Davide Pirino and Roberto Reno') (paper)

Management Science, 2020, 66, 3466-3479

Asset prices can be stale. We define price "staleness" as lack of price adjustments yielding zero returns (i.e., zeros). The term "idleness" (resp. "near idleness") is, instead, used to define staleness when trading activity is absent (resp. close to absent). We show that zeros are a genuine economic phenomenon linked to the dynamics of trading volume and, therefore, liquidity. Zeros are, in general, not the result of institutional features, like price discreteness. In essence, spells of idleness or near idleness are stylized facts suggestive of a key, omitted market friction in the modeling of asset prices. Using short-dated options as an economic metric, we show that illiquidity-induced staleness may generate sizable risk compensations in option returns.

EXcess Idle Time (with Davide Pirino and Roberto Reno') (paper)

Econometrica, 2017, 85, 1793-1846

We introduce a novel economic indicator, named excess idle time (EXIT), measuring the extent of sluggishness in financial prices. Under a null and an alternative hypothesis grounded in no-arbitrage (the null) and market microstructure (the alternative) theories of price determination, we derive a limit theory for EXIT leading to formal tests for staleness in the price adjustments. Empirical implementation of the theory indicates that financial prices are often more sluggish than implied by the (ubiquitous, in frictionless continuous-time asset pricing) semimartingale assumption. EXIT is interpretable as an illiquidity proxy and is easily implementable, for each trading day, using transaction prices only. By using EXIT, we show how to estimate structurally market microstructure models with asymmetric information.

Full Information Transaction Costs (with Jeff Russell) 

In a world with private information and learning on the part of the market participants, the (positive) difference between the observed transaction price of an asset and the corresponding unobserved full-information price (the price that reflects private and public information about the asset) represents an ideal measure of market quality. We call this difference "full-information transaction cost". We propose a simple and robust methodology to measure full-information transaction costs. Its simplicity is due to reliance on sample moments of observed high-frequency transaction price data. Its robustness hinges on the fact that the deviations of the observed transaction prices from the unobserved full-information prices can be imputed to fairly unrestricted operating (order-processing and inventory keeping) costs, adverse-selection costs, and learning in the marketplace. We estimate full-information transaction costs for a sample of S&P 100 stocks and find that, while related to existing measures of transaction costs, they differ in ways predicted by their theoretical construct. Specifically, we show that our approach captures a large (asymmetric information-induced) component of market quality which is missing from existing measures, such as effective spreads and bid-ask spreads.

Separating microstructure noise from volatility (with Jeff Russell) (paper)

Journal of Financial Economics, 2006, 79, 655-692

There are two variance components embedded in the returns constructed using high frequency asset prices: the time-varying variance of the unobservable efficient returns that would prevail in a frictionless economy and the variance of the equally unobservable microstructure noise. Using sample moments of high frequency return data recorded at different frequencies, we provide a simple and robust technique to identify both variance components. In the context of a volatility-timing trading strategy, we show that careful (optimal) separation of the two volatility components of the observed stock returns yields substantial utility gains.