Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item High Frequency Market Dynamics An Analysis of Market Depth & Quoting Behaviors in Crude Oil Futures Markets(2018) Roberts, John Spencer; Kyle, Albert S; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Most derivative and equity transactions occur in electronic order driven markets and depend on a limit order book. Yet many questions remain regarding the way traders interact with the limit order book, especially the role of algorithmic and high frequency trading. This dissertation investigates how the limit order book evolves over time. We study the nature of fleeting liquidity and flash quotes to deepen our understanding of the way modern markets operate. This research is based on raw message data sold by the exchange and contains every update to the limit order book linked to the top ten levels. We rebuild the limit order book and define quote segments to divide the day into non-overlapping intervals based on observed changes in the best quotes and the bid-ask spread. We propose a novel way to visualize dynamics of the limit order book by combining changes in best quotes and visible depth. Using the limit order book and quote segments, we define a measure for offered liquidity and then a measure to capture the responsiveness on both sides of the market during sub-second intervals. Flash quotes are identified and are combined with measures of offered liquidity to study why such behavior is observed in the market. We find empirical evidence that movement in market depth explains movement in the bid-ask spread. We show how combining movements in best quotes and visible depth provides a clearer picture of the direction of the market. Evidence is presented that breaks down the dynamics of offered liquidity into both trade response and prior movement of depth. We find standard measures of market liquidity, such as the bid-ask spread, can appear normal while responsiveness can remain elevated following a major market movement. Depth data assists with best execution, but this research highlights alternative uses that are important to consider when participating in modern markets. The observed dynamics of the limit order book contain relevant information that need to be captured in a full discussion of market liquidity.Item Credit and Liquidity in the Macroeconomy(2015) Kreamer, Jonathan; Korinek, Anton; Shea, John; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation studies the role of credit and liquidity in macroeconomic fluctuations. Chapter 1 analyzes the effect of endogenous unemployment risk on the dynamics of recovery from a liquidity trap. In a liquidity trap, an adverse demand shock raises unemployment and produces a period of slow hiring. Slow hiring further reduces demand, both for standard precautionary reasons and because credit conditions endogenously worsen, reducing households' ability to borrow and consume. Multiple equilibrium paths exist, and which one the economy follows depends on household expectations and the policy rule adopted by the central bank after the economy exits the trap. Employment remains depressed for a substantial period after an adverse shock because high unemployment increases the dispersion of household debt holdings, slowing the recovery of demand. I find that the initial household debt distribution significantly affects the economy's sensitivity to a demand shock, and study the role of central bank policy in mitigating the initial fall in employment and promoting faster recovery. Chapter 2 explores a novel channel through which financial shocks affect the real economy through the supply of liquidity. I consider a model in which firms require uncertain ongoing financing, and agency costs limit their ability to raise new funds. To secure future financing, firms hold assets to sell if needed, and purchase credit lines from financial intermediaries. I collectively refer to these instruments as liquidity. Financial intermediaries' ability to commit future funds depends on their capital. This creates a linkage between bank balance sheets and the aggregate supply of liquidity. Bank losses raise the liquidity premium and reduce investment. I analyze the optimal supply of public liquidity, and find that when private liquidity is scarce the government should issue bonds for their liquidity properties. I further find that the optimal supply of government debt is decreasing in bank capital. This suggests that in the wake of a financial crisis in which financial intermediaries suffer large losses, governments should increase debt issuance. Chapter 3 considers the distributive implications of financial regulation. It develops a model in which the financial sector benefits from financial risk-taking by earning greater expected returns. However, risk-taking also increases the incidence of large losses that lead to credit crunches and impose negative externalities on the real economy. A regulator has to trade off efficiency in the financial sector, which is aided by deregulation, against efficiency in the real economy, which is aided by tighter regulation and a more stable supply of credit.Item ESSAYS ON MARKET MICROSTRUCTURE AND HIGH FREQUENCY TRADING(2014) Li, Wei; Kyle, Albert S.; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation includes two chapters on topics related to market microstruc- ture and high frequency trading. In the first chapter, I explore the effects of speed differences among front-running high frequency traders (HFTs) in a model of one round of trading. Traders differ in speed and their speed differences matter. I model strategic interactions induced when HFTs have different speeds in an extended Kyle (1985) framework. HFTs are assumed to anticipate incoming orders and trade rapidly to exploit normal-speed traders' latencies. Upon observing a common noisy signal about the incoming order flow, faster HFTs react more quickly than slower HFTs. I find that these front-running HFTs effectively levy a tax on normal-speed traders, making markets less liquid and prices ultimately less informative. Such negative effects on market quality are more severe when HFTs have more heterogeneous speeds. Even when infinitely many HFTs compete, their negative effects in general do not vanish. I analyze policy proposals concerning HFTs and find that (1) lowering the frequency of trading reduces the negative impact of HFTs on market quality and (2) randomizing the sequence of order execution can degrade market quality when the randomizing interval is short. Consistent with empirical findings, a small number of HFTs can generate a large fraction of the trading volume and HFTs' profits depend on their speeds relative to other HFTs. In the second chapter, I study the effects of higher trading frequency and front-running in a dynamic model. I find that a higher trading frequency improves the informativeness of prices and increases the trading losses of liquidity driven noise traders. When the trading frequency is finite, the existence of HFT front-runners hampers price efficiency and market liquidity. In the limit when trading frequency is infinitely high, however, information efficiency is unaffected by front-running HFTs and these HFTs make all profits from noise traders who do not smooth out their trades.Item Essays on Market Microstructure(2012) Yamada, Masahiro; Kyle, Albert S; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation studies topics on market microstructure. The first chapter theoretically studies market manipulation in stock markets in a linear equilibrium. The second chapter empirically examines the presence of opportunities for liquidity arbitrage. The last chapter develops and examines a method to capture a co-movement of informed trading. In chapter 1, I study a theory of trade-based price manipulation in markets. I compare two different types of price manipulation studied in previous literature, uninformed and informed manipulation, in the same linear equilibrium model. I show that the presence of positive-feedback traders creates an incentive for the informed trader to bluff, but the opportunity is absent if a sufficient number of uninformed traders behave strategically. Numerical comparable statics results show that informed manipulation is more likely and more profitable when the noise trading is more volatile and that market efficiency could become worse under the presence of manipulation. A financial transaction tax can not prevent informed manipulation, but it reduces the liquidity of the market. Chapter 2 empirically investigates intra-day price manipulation in a stock market. My microstructure model is specifically designed to define the conditions under which a manipulation opportunity arises from the variation in liquidity as measured by price impact. My empirical analysis using data from the Tokyo Stock Exchange suggests that while there is a significant chance of uninformed manipulation across time and stock codes, it is not profitable enough to affect price fluctuations. Analysis of intraday price and trade sizes shows that the opportunity begins to disappear shortly. Chapter 3 studies contagion in a financial market by using a market microstructure model. We extend the Easley, Kiefer, and O'Hara (1997) model to a multiple-asset framework. The model allows us to identify whether the driving forces of informed trading common or idiosyncratic information events are. We apply the method to three groups of stocks listed on the New York Stock Exchange: American Depositary Receipts (ADRs) of developed and emerging countries, and blue chips. We find contagion among emerging-country ADRs during the Asian Financial Crisis of 1997, in the sense that informed trades were mostly driven by common information events.Item Essays on Empirical Market Microstructure(2011) Tuzun, Tugkan; Kyle, Albert S; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The first essay examines the events of May 6, 2010: the ``Flash Crash". The Flash Crash, a brief period of extreme market volatility on May 6, 2010 raised questions about the current structure of the U.S. financial markets. Audit-trail data from U.S. Commodity Futures Trading Commission (CFTC) is used to describe the structure of the E-mini S\&P 500 stock index futures market on May 6. In this study, three questions are asked. How did High Frequency Traders (HFTs) trade on May 6? What may have triggered the Flash Crash? What role did HFTs play in the Flash Crash? There is evidence which supports that HFTs did not trigger the Flash Crash, but their responses to the unusually large selling pressure on that day exacerbated market volatility. The second essay examines the relationship between mutual fund trading and liquidity consumption in financial markets. Using Thompson Mutual Funds holdings data and the Trade and Quotes (TAQ) data, we relate the mutual fund trading to liquidity consumption. Mutual fund trading is positively correlated with liquidity consumption. Mutual fund sensitivity to liquidity consumption differs based on mutual fund investment style. Large trades reveal the trading activity of actively managed mutual funds whereas the trading activity of index funds can be explained by small trades. This is consistent with a plausible explanation that index funds need to use small trades to rebalance their portfolios and information motivates the large trades of active mutual funds. The third essay tests the predictions of trading game invariance using the sample of trades from TAQ dataset from 1993 to 2008. The theory of trading game invariance predicts that the distribution of trade sizes as a fraction of trading volume should vary across stocks proportionally to their trading activity in -2/3 power and that the number of trades should vary across stocks proportionally to their trading activity in 2/3 power. The data supports predictions of the invariance theory. For the number of trades, the estimated power coefficient of 0.69 (with standard errors of 0.001) is especially close to the predicted one of 2/3 on the subsample before 2001. These estimates increases to 0.79 (with standard errors of 0.004) after 2001 following a structural break related to a reduction in tick size and a consequent spread of algorithmic trading. Furthermore, the entire distribution of trade size shifts with the trading activity in a manner predicted by invariance theory. When trade sizes are adjusted for differences in trading activity, then their distribution is stable across stocks and similar to the distribution of a log-normal variable, truncated at the 100-share threshold.