This dissertation empirically studies the implications of today’s fast-paced markets for securities trading and clearing. Chapter 2 proposes an approach that not only tracks the risk exposure of a central counterparty (CCP), but also offers a decomposition. Implementing the approach on real-world data from a large equity CCP, we find that extreme CCP exposure changes are disproportionately due to crowded trades and extreme CCP exposures are highly concentrated in a few clearing members and risk factors. Chapter 3 utilizes a granular regulatory dataset to contrast the roles of dealer banks and high-frequency traders (HFTs) in liquidity provision and price discovery in the foreign exchange (FX) market. On liquidity provision, we find while order-book liquidity provided by HFTs is less sensitive to large market-wide volatility spikes, that by dealer banks is more resilient ahead of scheduled macroeconomic news announcements. On price discovery, HFTs contribute the dominant share through their high-frequency quote updates which incorporate public information. In contrast, dealer banks contribute to price discovery more through their trades, impounding private information. Chapter 4 examines the role of the public data feed in the US equities market. Using exogenous events affecting the speed and availability of the public data feed as an identification, we find that a faster public data feed has an adverse, albeit mild, impact on market liquidity, possibly as a result of more non-high-frequency algorithmic trading activities from informed institutional traders. However, when the public feed becomes corrupted or unavailable due to a technical glitch, market liquidity significantly worsens.