Market making and dealer markets
Creators: name: Lorusso, Valentina
Publisher: name: Imperial College London
Year: 2016

description: The thesis investigates information and liquidity provision in financial markets. I explore the implications of the strategic behaviour of market makers competing with high frequency traders and of dealers involved in long term relationships with clients in the foreign exchange markets. Additionally, I analyse the value of information from the liquidity order flow to market makers and dealers. Further, I reflect on regulatory implications of my findings. The first chapter presents a literature review to motivate the following chapters. First, I survey the main findings of the papers on market making most relevant to this thesis. Second, I discuss the regulatory and academic debate on high frequency traders, which are widely viewed as a new type of liquidity providers. Third, I discuss important differences between market makers and FX dealers, including specific features of foreign exchange markets and their informational structure. Lastly, I provide a brief overview of the recent regulatory debate on OTC markets. The second chapter analyses the effect of competition between a designated, traditional market maker and a High Frequency Trader providing liquidity. The market maker is risk neutral and the high frequency trader is risk averse, which creates differences in their inventory exposures. The market power of these two participants creates a bid ask spread, but the high frequency trader narrows the spread and improves liquidity. The chapter further investigates the liquidity provision by a monopolistic high frequency trader. I show that having agents with strong inventory concerns as market makers could hamper liquidity provision. I explain how ceteris paribus small changes in the reservation value of liquidity traders can trigger shifts in the equilibrium spread. The third chapter endogenizes the existence of intermediation in a two-tier market. Specifically, trading takes place sequentially in a client-dealer OTC market and in an interdealer market organised as a limit order book. A privately-informed client chooses between trading through dealers or paying an entry cost to join the interdealer market directly. Dealer rents from intermediation increase in the entry cost. I show that competitive dealers use the bid ask spread strategically to reward the client for the information conveyed by his order flow. Furthermore, I show that the client dealer relationship is affected by a commitment problem: clients who trade una tantum execute trades with multiple dealers. Ongoing client dealer relationships viewed as an infinitely repeated game can overcome this problem and the client may benefit from trading exclusively with one dealer. The fourth chapter analyses information sharing and collusion incentives of strategic liquidity providers and the impact of their cooperation on asset prices. Risk neutral liquidity providers operate in a market with risk-averse informed traders (fundamentalists) and noise traders. I consider four regimes: 1) pure market making; 2) dealership without information sharing; 3) dealership with information sharing but without collusion in trading; and 4) dealership with information sharing and collusion in trading. I show that information sharing substantially increases agents' profits, while colluding in trading has a relatively low additional impact on profits. This suggests that if there are penalties for collusion, dealers may choose to only share information, but not to collude. Furthermore, I investigate the effect of the four regimes on market depth, volatility of prices and information content of prices. I find that dealers sharing information and colluding increase market depth compared to dealership without information sharing. However, the market depth is lower compared to pure market making. Both volatility of prices and the information content of prices increase when liquidity providers act as dealers. The magnitude of these differences depends on the parameters of the model.