2008-04-15 papers

on Market Microstructure

Issue of 2008‒04‒15
two papers chosen by
Thanos Verousis

A Two-Stage Non Discretionary Trading Suspension Mechanism: Effects on Market Quality By Anolli, Mario; Petrella, Giovanni
Forecasting Realized Volatility: A Bayesian Model Averaging Approach By Chun Liu; John M Maheu

A Two-Stage Non Discretionary Trading Suspension Mechanism: Effects on Market Quality

By:	Anolli, Mario; Petrella, Giovanni
Abstract:	This paper investigates the intraday effects on market quality of a unique trading suspension mechanism in place at the Italian stock market (Borsa Italiana) in case of price limit hit. Specifically, when prices hit the limit, Borsa Italiana halts trading for 5 minutes ('freeze phase') and removes the order that caused the limit to be hit. If trading regularly resumes after the freeze phase, exchange officials make no other intervention and we call this sequence of events 'Type 1' halt (i.e., freeze-only halt). Alternatively, if a second limit hit occurs after the freeze phase, an intraday call auction replaces the continuous trading. We name this sequence 'Type 2' halt (i.e., intraday auction halt). We examine both the general effects of trading halts and the specific effects of Type 1 and Type 2 trading suspensions on three dimensions of market quality: trading activity, return volatility, and price discovery. The full sample results reveal mixed evidence about the usefulness of price limit hit trading halts: trading volume and return volatility after the halt are abnormally high (trading interference hypothesis for volume and spillover hypothesis for volatility), whereas prices converge towards equilibrium values (cool off hypothesis for price discovery). When we partition the sample by type of halt three main results arise. First, Type 2 halts always show larger abnormal volume measures than Type 1 and this indicates a greater interference on the normal trading process of Type 2 relative to Type 1 halts. Second, Type 2 halts show lower post-halt abnormal volatility than Type 1. This might be explained by the difference in the way the market restarts after the halt. The call auction procedure associated with Type 2 allows for wider information dissemination, whereas the price discovery process in Type 1 trading halts takes place only through the tâtonnement process in continuous trading. Third, for the price discovery process, the call auction reopening procedure of Type 2 halts also has a stronger cool off effect relative to the Type 1 continuous trading.
Keywords:	price limits; trading halts; market quality; Italian stock market
JEL:	G14 G10
Date:	2007–04–19
URL:	http://d.repec.org/n?u=RePEc:pra:mprapa:7931&r=mst

Forecasting Realized Volatility: A Bayesian Model Averaging Approach

By:	Chun Liu; John M Maheu
Abstract:	How to measure and model volatility is an important issue in finance. Recent research uses high frequency intraday data to construct ex post measures of daily volatility. This paper uses a Bayesian model averaging approach to forecast realized volatility. Candidate models include autoregressive and heterogeneous autoregressive (HAR) specifications based on the logarithm of realized volatility, realized power variation, realized bipower variation, a jump and an asymmetric term. Applied to equity and exchange rate volatility over several forecast horizons, Bayesian model averaging provides very competitive density forecasts and modest improvements in point forecasts compared to benchmark models. We discuss the reasons for this, including the importance of using realized power variation as a predictor. Bayesian model averaging provides further improvements to density forecasts when we move away from linear models and average over specifications that allow for GARCH effects in the innovations to log-volatility.
Keywords:	power variation, bipower variation, Gibbs sampling, model risk
JEL:	C11 C22 G12
Date:	2008–04–03
URL:	http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-313&r=mst

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