Measuring the quality of financial markets: An application on measuring market quality Nasdaq 100 index futures contracts by employing vector autoregression methodology

VI ABSTRACT Any technological, structural or functional changes occuring in a financial marketplace lead to studies of pricing efficieny and market quality, and possible impacts of these changes on other financial markets. Moreover, these innovations are deemed as opportunuties to conduct empirical studies. The subject of this dissertation is the measuring market quality, which constitutes an aspect of researches on microstructure analyses of security markets. Application of market quality measure has been performed on the Nasdaq 100 Index futures contracts traded in the United States. Quality measurement of this market has been carried out in consideration with the introduction of CUBEs. Being a new investment instrument in Exchange Traded Funds class, Cubes track the performance of Nasdaq 100 Index, and traded on the exchange just like shares of a common stock. By employing intraday tick-by-tick data, Hasbrouck's Vector Autoregression (VAR) methodology is used to analyze the efficiency of index futures market. For this purpose, pricing error variances are computed. Pricing error is defined as the deviation of transaction prices from the efficient price. The variance of the pricing error measures how closely actual transaction prices track the efficient price. Thus, it is a natural measure of market quality. In the study, VAR analysis is performed on two 200-day periods before and after Cubes. Pricing error variance computed for pre-Cubes period is 0.20030 while a significantly lower variance of 0.03907 is found for post-Cubes period. These findings suggest that hypothesized quality improvement in Nasdaq 100 Index futures market has been observed after the introduction of Cubes.