Price formation on stock exchanges: the evolution of trading within the day

Prior analyses of prices of the NYSE and other exchanges findthat transitory price volatility is greater at the open of tradingthan at the close. We extend this line of research by using40 years of hourly Dow Jones 65 composite price index data toestimate transitory volatility throughout the trading day. Ourresults indicate that transitory volatility steadily declinesduring the trading day. We find a similar intraday decline intransitory volatility for a 2-year sample of the individualfirms in the Dow Jones 30 Industrials Index. The results areconsistent with the hypothesis that trading aids price formationand do not support the argument that particular trading mechanismsare the source of greater volatility at the open of trading.     

An Analysis of Individual NYSE Specialist Portfolios and Execution Quality

The value of specialist assistance to the trading of low-volume stocks has important implications in exchange design. We study the relation between the structure of individual specialist portfolios and the transitory volatility of low-volume stocks in these portfolios under the traditional NYSE auction-dealer market structure. We find that the trading quality for inactive stocks is positively related to the trading volume of active stocks in the same specialist portfolios. These results are consistent with specialist subsidization of low-volume stocks in their portfolios and suggest that specialists provide important support to the trading of inactive stocks if they have the resources.     

Liquidity Provision of Limit Order Trading in the Futures Market Under Bull and Bear Markets

Abstract:  This study investigates how limit orders affect liquidity in a purely order-driven futures market. Additionally, the possible asymmetric relationship between market depth and transitory volatility in bull and bear markets and the effect of institutional trading on liquidity provision behavior are examined as well. The empirical results demonstrate that subsequent market depth increases as transient volatility increases in bull markets. Market depth exhibits significantly positive relationship to subsequent transient volatility in bull markets. Additionally, although trading volume positively influences transient volatility in bull markets, no such relationship exists in bear markets. Liquidity provision decreases when institutional trading activity intensifies during bear markets. Thus, liquidity provision for limit orders differs between bull and bear markets.     

Dynamic Volatility Trading Strategies in the Currency Option Market

The conditional volatility of foreign exchange rates can be predicted using GARCH models or implied volatility extracted from currency options. This paper investigates whether these predictions are economically meaningful in trading strategies that are designed only to trade volatility risk. First, this article provides new evidence on the issue of information content of implied volatility and GARCH volatility in forecasting future variance. In an artificial world without transaction costs both delta-neutral and straddle trading stratgies lead to significant positive profits, regardless of which volatility prediction method is used. Specifically, the agent using the Implied Stochastic Volatility Regression method (ISVR) earns larger profits than the agent using the GARCH method. Second, it suggests that the currency options market is informationally efficient. After accounting for transaction costs, which are assumed to equal one percent of option prices, observed profits are not significantly differentfrom zero in most trading strategies. Finally, these strategies offered returns have higher Sharpe ratio and lower correlation with several major asset classes. Consequently, hedge funds and institutional investors who are seeking alternative “marketneutral” investment methods can use volatility trading to improvethe risk-return profile of their portfolio through diversification. This revised version was published online in November 2006 with corrections to the Cover Date.     

Differently motivated exchange traded fund trading activities and the volatility of the underlying index

This paper examines the correlations between two types of a market index's volatility and three trading motives of the index's exchange traded funds (ETFs). We find that ETF trading driven by belief dispersion is highly correlated with both the variance in efficient price innovations (VEPI) and the index's total volatility. Privately informed ETF trading is closely connected to the VEPI but not the total volatility, while liquidity ETF trading explains the total volatility but has little power in explaining the VEPI. Moreover, the leading ETF dominates smaller ETFs in explaining both types of volatility and often has more explanatory power than control variables.     

Futures Trading Activity and Commodity Cash Price Volatility

Abstract:   This paper examines the lead‐lag relationship between futures trading activity (volume and open interest) and cash price volatility for major agricultural commodities. Granger causality tests and generalized forecast error variance decompositions show that an unexpected increase in futures trading volume unidirectionally causes an increase in cash price volatility for most commodities. Likewise, there is a weak causal feedback between open interest and cash price volatility. These findings are generally consistent with the destabilizing effect of futures trading on agricultural commodity markets.     

Capturing volatility persistence: a dynamically complete realized EGARCH-MIDAS model

We introduce extensions of the Realized Exponential GARCH model (REGARCH) that capture the evident high persistence typically observed in measures of financial market volatility in a tractable fashion. The extensions decompose conditional variance into a short-term and a long-term component. The latter utilizes mixed-data sampling or a heterogeneous autoregressive structure, avoiding parameter proliferation otherwise incurred by using the classical ARMA structures embedded in the REGARCH. The proposed models are dynamically complete, facilitating multi-period forecasting. A thorough empirical investigation with an exchange-traded fund that tracks the S&P500 Index and 20 individual stocks shows that our models better capture the dependency structure of volatility. This leads to substantial improvements in empirical fit and predictive ability at both short and long horizons relative to the original REGARCH. A volatility-timing trading strategy shows that capturing volatility persistence yields substantial utility gains for a mean–variance investor at longer investment horizons.     

Stock market structure and volatility

The procedure for opening stocks on the NYSE appears to affectprice volatility. An analytical framework for assessing themagnitude of the structurally induced volatility is presented.The ratio of variance of open-to-open returns to close-to-closereturns is shown to be consistently greater than one for NYSEcommon stocks during the period 1982 through 1986. The greatervolatility at the open is not attributable to the way in whichpublic information is released since both the open-to-open returnand the close-to-close return span the same period of time.Instead, the greater volatility appears to be attributable toprivate information revealed in trading and to temporary pricedeviations induced by specialist and other traders. The impliedcost of immediacy at the open is significantly higher than atthe close. Other empirical evidence in this article documentsthe volume of trading at the open, the time delays between theexchange opening and the first transaction in a stock, the differencein daytime volatility versus overnight volatility, and the extendto which volatility is related to trading volume.     

Trading volume and stock market volatility: The Polish case

Relying on the mixture of distributions hypothesis (MDH), this paper investigates the relationship between daily returns and trading volume for 20 Polish stocks. Our empirical results show that in the majority of cases volatility persistence tends to disappear when trading volume is included in the conditional variance equation, which is in agreement with the findings of studies on developed stock markets. However, we cannot confirm the testable implications of the MDH in all cases, which indicates that future research on the causes and modeling of Polish stock market volatility is necessary.     

From pit to electronic trading: Impact on price volatility of U.S. Treasury futures

This paper investigates the dynamics of price volatility and trading volume of 10-year U.S. Treasury note futures within the context of transition from pit to electronic trading. The analysis is conducted over four discernible phases of futures trading evolution: the pit-only phase, the leap to electronic trading, and the electronic trading dominant phase, which is divided further into two periods, the before and after the financial crisis of 2007/2009. Generalized autoregressive conditional heteroskedasticity with in-mean conditional variance and generalized error distribution parameterization (GARCH-M-GED) tests are conducted to examine the conditional volatility of total returns index as a function of trading volume. The empirical results show a consistently negative relationship between the trading volume and price volatility for all four analyzed phases. They also show decreasing leptokurtosis (except for the direct effects of the recent crisis), continuously high persistency in volatility, as well as a weakening impact of unexpected ARCH-type shocks during the most recent analyzed period. Overall, the shift to electronic trading entails a substantial increase in trading volume, but not in price volatility of Treasury futures.