Selected Essays in Stock Market Liquidity. Innovative XLM Measure at the Frankfurt Stock Exchange: Cloudy Skies, Time of the Day and the Role of Designated Sponsors for Stock Market Liquidity.

This dissertation is built around three separate papers that research several aspects of stock market liquidity. All three papers use the innovative XLM (Exchange Liquidity Measure) data to measure the liquidity. The first paper entitled Does Screen Trading Weather the Weather? A Note on Cloudy Skies, Liquidity and Computerized Stock Markets tests for the presence of a weather effect on liquidity in a screen-based electronic stock market. The empirical evidence suggests that cloudy skies correspond with high natural liquidity levels and low liquidity injected by market makers. This result is consistent with findings for floor-based stock trading and with the hypothesis that market makers add less value in markets with high natural liquidity. The second paper entitled Designated Sponsors on Xetra – Is One Designated Sponsor Enough? tests for the impact of Designated Sponsors on liquidity in the electronic trading system Xetra at the Frankfurt stock exchange. The empirical results suggest that Designated Sponsors improve liquidity and that the increase in a number of Designated Sponsors improves liquidity further. The third paper entitled How Do Trading Costs Vary Across the Day? A note on the innovative XLM measure for Small Caps at the Frankfurt Stock Exchange provides empirical evidence on the intraday pattern of trading costs for German small cap stocks in the electronic trading system Xetra. The empirical evidence for the TecDAX stocks under investigation suggests a reverse-J shaped intraday profile for execution costs. Thus, trading is most expensive in the first 30 minutes after Xetra opens, and it is cheapest at the time when the NYSE starts trading. We conclude that cross-border integration of stock exchanges fosters market quality. --Liquidity,stock market,XLM,Xetra,weather,Designated sponsors,intraday,market makers

High frequency trading and co-movement in financial markets

© 2019 Elsevier B.V. Using the staggered entry of Chi-X in 12 European equity markets as a source of exogenous variation in high frequency trading (HFT), we find that HFT causes significant increases in comovement in returns and in liquidity. About one-third of the increase in return comovement is due to faster diffusion of market-wide information. We attribute the remaining two-thirds to correlated trading strategies of HFTs. The increase in liquidity comovement is consistent with HFT liquidity providers being better able to monitor other stocks and adjust their liquidity provision accordingly. Our findings suggest a channel by which HFT impacts the cost of capital

Foresight: the future of computer trading in financial markets: final project report

SRC researchers were involved in a study that explores how computer generated trading in financial markets will evolve over the next 10 years. The project was led by the Government Office for Science. Advances in technology are transforming how our financial markets operate. The volume of financial products traded through computer automated trading taking place at high speed and with little human involvement has increased dramatically in the past few years. Today, over one-third of UK equity trading volume is generated through high frequency automated computer trading while in the US this figure is closer to three-quarters. This project examined the technological advances which have transformed market structures in recent years and explored how computer trading will evolve over the next 10 years

The Value of Social Media for Predicting Stock Returns - Preconditions, Instruments and Performance Analysis

The cumulative dissertation of Michael Nofer examines whether Social Media platforms can be used to predict stock returns. Market-relevant information is available on various platforms on the Internet, which consist largely of user generated content. For instance, emotions can be extracted in order to identify the investors' risk appetite and in turn the willingness to invest in stocks. Discussion forums also provide an opportunity to extract opinions on certain stocks. Taking Social Media platforms as examples, the dissertation examines the forecasting quality of user generated content on the Internet

Essays on intraday volatility and market microstructure

This work makes three main contributions to the financial econometrics literature. In Chapter 3, we study the intraday volatility of European government bonds under the framework of the multiplicative component GARCH model (Engle and Sokalska, 2012). We suggest a flexible and effective procedure for jointly filtering mid-quote prices and estimating volatility models and show that intraday data contain relevant information for daily volatility forecasts. In Chapter 4, we show that a bond portfolio can reduce its intraday variance risk by including bonds from Italy and Spain. Furthermore, we demonstrate that the bivariate (scalar) DCC model is capable of computing an accurate VaR, providing correct conditional and unconditional coverage at lower than 1% (inclusive) confidence level and inducing lower losses. In Chapter 5, we demonstrate that liquidity measures, such as the bid-ask spread and quantity available for trading at the best quotes, improve across maturities and countries after EuroMTS has allowed every market participant to post limit orders and not just designated market makers. In particular, we show that the relative bid-ask spread for trading 10 million bonds decreases with the rule change. The proportion of time when the relative bid-ask spread stays low also increases. The results suggest that greater competition amongst liquidity providers improves liquidity