Lead-Lag Structures in Ultra-High-Frequency Trading

Lead-lag effects in the market microstructure context describe situations where financial instruments are leading and provide information about the future price, liquidity, or volatility development of other instruments lagging behind. In modern financial markets, where algorithmic and high-frequency trading is prominent, lead-lag relationships may be subject to substantial changes because information-based trading increasingly relates to patterns in high-frequency market data instead of fundamental information. Against this background, this thesis analyzes lead-lag relationships of various market microstructure measures for price, liquidity, depth, and volatility across a broad range of assets and asset classes using high-frequency data. The analysis is based on high-resolution limit order book and transaction data of 32 different instruments in total, including 6 equities, 9 future contracts, 3 options, and 14 ETPs. The results show that lead-lag effects predominantly occur across different price measures, but also exist across volatility measures. The strongest correlations are among the midquotes where index future contracts such as the EuroStoxx50 future significantly lead single stocks and ETFs. With respect to liquidity and depth measures, lead-lag relationships are detected only for specific instrument combinations. For instance, the EuroStoxx50 future leads ETFs that track major equity indices with respect to trading volume. In sum, the thesis highlights several significant lead-lag relationships between different instruments, asset classes, and measures. The strongest correlations are mostly driven by fundamental relationships, however, lead-lag effects also exist between instruments that are not fundamentally related.