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on Market Microstructure |
| By: | Gökhan Cebiroglu; Ulrich Horst |
| Abstract: | We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stock’s hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that large hidden orders are associated with larger transaction costs, higher price impact and increased volatility. In particular, as large hidden orders fail to attract (latent) liquidity to the market, hidden liquidity provision gives rise to negative liquidity externalities. |
| Keywords: | Hidden Liquidity, Pretrade Transparency, Iceberg Orders, Informed Trading, Market Impact, Market Quality, Liquidity Externalities, Upstairs Markets, Trade Negotiation |
| JEL: | G10 G11 G12 G14 G24 |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2012-023&r=mst |
| By: | Corsi, Fulvio; Peluso, Stefano; Audrino, Francesco |
| Abstract: | Motivated by the need for an unbiased and positive-semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra-high-frequency asset prices in a state-space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and Expectation Maximization (KEM) algorithm. In the expectation step, by means of the Kalman filter with missing data, we reconstruct the smoothed and synchronized series of the latent price processes. In the maximization step, we search for covariance matrices that maximize the expected likelihood obtained with the reconstructed price series. Iterating between the two EM steps, we obtain a KEM-improved covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive-semidefinite by construction. Extensive Monte Carlo simulations show the superior performance of the KEM estimator over several alternative covariance matrix estimates introduced in the literature. The application of the KEM estimator in practice is illustrated on a 10-dimensional US stock data set. |
| Keywords: | High frequency data; Realized covariance matrix; Market microstructure noise; Missing data; Kalman filter; EM algorithm; Maximum likelihood |
| JEL: | C13 C51 C52 C58 |
| Date: | 2012–01 |
| URL: | http://d.repec.org/n?u=RePEc:usg:econwp:2012:02&r=mst |
| By: | Gara Afonso; Ricardo Lagos |
| Abstract: | We use minute-by-minute daily transaction-level payments data to document the cross-sectional and time-series behavior of the estimated prices and quantities negotiated by commercial banks in the fed funds market. We study the frequency and volume of trade, the size distribution of loans, the distribution of bilateral fed funds rates, and the intraday dynamics of the reserve balances held by commercial banks. We find evidence of the importance of the liquidity provision achieved by commercial banks that act as de facto intermediaries of fed funds. |
| Keywords: | Federal funds market (United States) ; Bank reserves ; Liquidity (Economics) ; Federal funds rate |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:550&r=mst |
| By: | Philip Bond; Yaron Leitner |
| Abstract: | We study trade between a buyer and a seller who have existing inventories of assets similar to those being traded. We analyze how these inventories affect trade, information dissemination, and prices. We show that when traders’ initial leverages are moderate, inventories increase price and trade volume (a market “run-up”), but when leverages are high, trade is impossible (a market “freeze”). Our analysis predicts a pattern of trade in which prices and volumes first increase, and then markets break down. Moreover, the presence of competing buyers may amplify the increased-price effect. We discuss implications for regulatory intervention in illiquid markets. |
| Keywords: | Mortgages ; Markets ; Inventories ; Trade |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:12-8&r=mst |