Microstructure Characteristics of U.S. Futures Markets

Prior finance literature lacks a comprehensive analysis of microstructure characteristics of U.S. futures markets due to the lack of data availability. Utilizing a unique data set for five different futures contract this dissertation fills this gap in the finance literature. In three essays price discovery, resiliency and the components of bid-ask spreads in electronic futures markets are examined. In order to provide comprehensive and robust analysis, both moderately volatile pre-crisis and volatile crisis periods are included in the analysis. The first essay entitled “Price Discovery and Liquidity Characteristics for U.S. Electronic Futures and ETF Markets” explores the price discovery process in U.S. futures and ETF markets. Hasbrouck’s information share method is applied to futures and ETF instruments. The information share results show that futures markets dominate the price discovery process. The results on the factors that affect the price discovery process show that when volatility increases, the price leadership of futures markets declines. Furthermore, when the relative size of bid-ask spread in one market increases, its information share decreases. The second essay, entitled “The Resiliency of Large Trades for U.S. Electronic Futures Markets,“ examines the effects of large trades in futures markets. How quickly prices and liquidity recovers after large trades is an important characteristic of financial markets. The price effects of large trades are greater during the crisis period compared to the pre-crisis period. Furthermore, relative to the pre-crisis period, during the crisis period it takes more trades until liquidity returns to the pre-block trade levels. The third essay, entitled “Components of Quoted Bid-Ask Spreads in U.S. Electronic Futures Markets,” investigates the bid-ask spread components in futures market. The components of bid-ask spreads is one of the most important subjects of microstructure studies. Utilizing Huang and Stoll’s (1997) method the third essay of this dissertation provides the first analysis of the components of quoted bid-ask spreads in U.S. electronic futures markets. The results show that order processing cost is the largest component of bid-ask spreads, followed by inventory holding costs. During the crisis period market makers increase bid-ask spreads due to increasing inventory holding and adverse selection risks.

Essays on the determinants of private investment: The effects of relative price uncertainty and political instability

The objective of this study was to provide empirical evidence on the effects of relative price uncertainty and political instability on private investment. My effort is expressed in a single-equation model using macroeconomic and socio-political data from eight Latin American countries for the period 1970–1996. Relative price uncertainty is measured by the implied volatility of the exchange rate and political instability is measured by using indicators of social unrest and political violence. ^ I found that, after controlling for other variables, relative price uncertainty and political instability are negatively associated with private investment. Macroeconomic and political stability are key ingredients for the achievement of a strong investment response. This highlights the need to develop the state and build a civil society in which citizens can participate in decision-making and express consent without generating social turmoil. At the same time the government needs to implement structural policies along with relative price adjustments to eliminate excess volatility in price movements in order to provide a stable environment for investment. ^

An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Three essays on market depth in futures markets

Liquidity is an important market characteristic for participants in every financial market. One of the three components of liquidity is market depth. Prior literature lacks a comprehensive analysis of depth in U.S. futures markets due to past limitations on the availability of data. However, recent innovations in data collection and dissemination provide new opportunities to investigate the depth dimension of liquidity. In this dissertation, the Chicago Mercantile Exchange (CME) Group proprietary database on depth is employed to study the dynamics of depth in the U.S. futures markets. This database allows for the analysis of depth along the entire limit order book rather than just at the first level. The first essay examines the characteristics of depth within the context of the five-deep limit order book. Results show that a large amount of depth is present in the book beyond the best level. Furthermore, the findings show that the characteristics of five-deep depth between day and night trading vary and that depth is unequal across levels within the limit order book. The second essay examines the link between the five-deep market depth and the bid-ask spread. The results suggest an inverse relation between the spread and the depth after adjusting for control factors. The third essay explores transitory volatility in relation to depth in the limit order book. Evidence supports the relation between an increase in volatility and a subsequent decrease in market depth. Overall, the results of this dissertation are consistent with limit order traders actively managing depth along the limit order book in electronic U.S. futures markets.

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Three Essays on Market Depth in Futures Markets

Liquidity is an important market characteristic for participants in every financial market. One of the three components of liquidity is market depth. Prior literature lacks a comprehensive analysis of depth in U.S. futures markets due to past limitations on the availability of data. However, recent innovations in data collection and dissemination provide new opportunities to investigate the depth dimension of liquidity. In this dissertation, the Chicago Mercantile Exchange (CME) Group proprietary database on depth is employed to study the dynamics of depth in the U.S. futures markets. This database allows for the analysis of depth along the entire limit order book rather than just at the first level. The first essay examines the characteristics of depth within the context of the five-deep limit order book. Results show that a large amount of depth is present in the book beyond the best level. Furthermore, the findings show that the characteristics of five-deep depth between day and night trading vary and that depth is unequal across levels within the limit order book. The second essay examines the link between the five-deep market depth and the bid-ask spread. The results suggest an inverse relation between the spread and the depth after adjusting for control factors. The third essay explores transitory volatility in relation to depth in the limit order book. Evidence supports the relation between an increase in volatility and a subsequent decrease in market depth. Overall, the results of this dissertation are consistent with limit order traders actively managing depth along the limit order book in electronic U.S. futures markets.