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Author: Yi Xue Publisher: ISBN: Category : Econometrics Languages : en Pages : 294
Book Description
This thesis consists of three essays that study three interdependent topics: microstructure foundation of volatility clustering, inefficiency of information diffusion and jump detection in high frequency financial time series data. Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. The first essay forms Chapter 1 which presents a market microstructure model that is able to generate volatility clustering with hyperbolic autocorrelations through traders with multiple trading frequencies using Bayesian information updating in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequency, can increase the persistence of the volatility of returns. Furthermore, it is shown that the local temporal memory of the underlying time series of returns and their volatility varies greatly with the number of traders in the market. The second essay, Chapter 2, presents a market microstructure model showing that an increasing number of information hierarchies among informed competitive traders leads to a slower information diffusion rate and informational inefficiency. The model illustrates that informed traders may prefer trading with each other rather than with noise traders in the presence of the information hierarchies. Furthermore, it is shown that momentum can be generated from the trend following behavior pattern of noise traders. I propose a new nonparametric test based on wavelets to detect jump arrivals in high frequency financial time series data, in the third essay, Chapter 3. It is demonstrated that the test is robust for different specifications of price processes and the presence of market microstructure noise and it has good size and power. Further, I examine the multi-scale jump dynamics in U.S. equity markets and the findings are as follows. First, the jump dynamics of equities are entirely different across different time scales. Second, although arrival densities of positive jumps and negative jumps are symmetric across different time scales, the magnitude of jumps is distributed asymmetrically at high frequencies. Third, only twenty percent of jumps occur in the trading session from 9:30AM to 4:00PM, suggesting that jumps are largely determined by news rather than liquidity shocks.
Author: Yi Xue Publisher: ISBN: Category : Econometrics Languages : en Pages : 294
Book Description
This thesis consists of three essays that study three interdependent topics: microstructure foundation of volatility clustering, inefficiency of information diffusion and jump detection in high frequency financial time series data. Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. The first essay forms Chapter 1 which presents a market microstructure model that is able to generate volatility clustering with hyperbolic autocorrelations through traders with multiple trading frequencies using Bayesian information updating in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequency, can increase the persistence of the volatility of returns. Furthermore, it is shown that the local temporal memory of the underlying time series of returns and their volatility varies greatly with the number of traders in the market. The second essay, Chapter 2, presents a market microstructure model showing that an increasing number of information hierarchies among informed competitive traders leads to a slower information diffusion rate and informational inefficiency. The model illustrates that informed traders may prefer trading with each other rather than with noise traders in the presence of the information hierarchies. Furthermore, it is shown that momentum can be generated from the trend following behavior pattern of noise traders. I propose a new nonparametric test based on wavelets to detect jump arrivals in high frequency financial time series data, in the third essay, Chapter 3. It is demonstrated that the test is robust for different specifications of price processes and the presence of market microstructure noise and it has good size and power. Further, I examine the multi-scale jump dynamics in U.S. equity markets and the findings are as follows. First, the jump dynamics of equities are entirely different across different time scales. Second, although arrival densities of positive jumps and negative jumps are symmetric across different time scales, the magnitude of jumps is distributed asymmetrically at high frequencies. Third, only twenty percent of jumps occur in the trading session from 9:30AM to 4:00PM, suggesting that jumps are largely determined by news rather than liquidity shocks.
Author: Jiang Liang Publisher: ISBN: Category : Econometrics Languages : en Pages : 0
Book Description
"This dissertation develops several econometric techniques to address three issues in financial economics, namely, constructing a real estate price index, estimating structural break points, and estimating integrated variance in the presence of market microstructure noise and the corresponding microstructure noise function. Chapter 2 develops a new methodology for constructing a real estate price index that utilizes all transaction price information, encompassing both single-sales and repeat-sales. The method is less susceptible to specification error than standard hedonic methods and is not subject to the sample selection bias involved in indexes that rely only on repeat sales. The methodology employs a model design that uses a sale pairing process based on the individual building level, rather than the individual house level as is used in the repeat-sales method. The approach extends ideas from repeat-sales methodology in a way that accommodates much wider datasets. In an empirical analysis of the methodology, we fit the model to the private residential property market in Singapore between Q1 1995 and Q2 2014, covering several periods of major price fluctuation and changes in government macroprudential policy ..."--Author's abstract.
Author: Sean Lew Publisher: ISBN: Category : Languages : en Pages :
Book Description
This thesis contains three essays on market microstructure. Chapter 1 studies how endogenous information acquisition affects financial markets by modelling potentially informed traders who optimally acquire variable information at increasing cost. Prices affect the informed trading by providing incentives for acquiring information. Endogenous information acquisition explains the stylised facts that informed trading and transaction volume spike after informational events and fall over time. My model also tells a cautionary tale for interpreting measures of informed trading. Three common empirical proxies derived under the exogenous assumption (spreads, Easley O'Hara's PIN and blockholder interest) do not agree with each other in my setup. Chapter 2 develops a more general framework with endogenous information acquisition which I use to examine the behaviour of an optimal monopolistic market maker. Unlike a competitive market maker, he sets prices to increase information revelation which is valuable to him. I characterise market information structure by whether narrower or wider spreads increase the information revealed by trades. An optimal monopolistic market maker may behave differently from the standard exogenous information benchmark. He may set narrower spreads in early periods. On average, spreads may widen over time. The different results arise from the interaction of a monopolistic market maker with endogenous information acquisition. Chapter 3 studies the impact of confidential treatment requests made by institutional investors to the Securities and Exchange Commission (SEC) to delay disclosure of their holdings. The SEC requires the manager to present a coherent on-going trading program in his request for confidential treatment. If granted, he is restricted to trade in a manner consistent with his reported forecast in the subsequent period. Under the restriction, the manager earns higher expected profits by applying for confidential treatment only if his probability of success exceeds a threshold. The model predicts that the price impact of a disclosed trade due to a confidential treatment request denial is greater than that of a disclosed trade where there is no request.
Author: Cheng Few Lee Publisher: World Scientific ISBN: 9814478830 Category : Business & Economics Languages : en Pages : 269
Book Description
News Professor Cheng-Few Lee ranks #1 based on his publications in the 26 core finance journals, and #163 based on publications in the 7 leading finance journals (Source: Most Prolific Authors in the Finance Literature: 1959-2008 by Jean L Heck and Philip L Cooley (Saint Joseph's University and Trinity University). Market microstructure is the study of how markets operate and how transaction dynamics can affect security price formation and behavior. The impact of microstructure on all areas of finance has been increasingly apparent. Empirical microstructure has opened the door for improved transaction cost measurement, volatility dynamics and even asymmetric information measures, among others. Thus, this field is an important building block towards understanding today's financial markets. One of the pioneers in the field of market microstructure is David K Whitcomb, who retired from Rutgers University in 1999 after 25 years of service. David generously funded the David K Whitcomb Center for Research in Financial Services, located at Rutgers University. The Center organized a conference at Rutgers in his honor. This conference showcased papers and research conducted by the leading luminaries in the field of microstructure and drew a broad and illustrious audience of academicians, practitioners and former students, all who came to pay tribute to David K Whitcomb. Most of the papers in this volume were presented at that conference and the contributions to this volume are a lasting bookmark in microstructure. The coverage of topics on this volume is broad, ranging from the theoretical to empirical, and covering various issues from market architecture to liquidity and volatility.
Author: Anil K. Bera Publisher: Springer ISBN: 3319099469 Category : Business & Economics Languages : en Pages : 282
Book Description
In the era of Big Data our society is given the unique opportunity to understand the inner dynamics and behavior of complex socio-economic systems. Advances in the availability of very large databases, in capabilities for massive data mining, as well as progress in complex systems theory, multi-agent simulation and computational social science open the possibility of modeling phenomena never before successfully achieved. This contributed volume from the Perm Winter School address the problems of the mechanisms and statistics of the socio-economics system evolution with a focus on financial markets powered by the high-frequency data analysis.
Author: Yi Xue
Author: Yi Xue
Author: Jiang Liang
Author: Jianxun Li
Author: Andrew Seong Kiat Tan
Author: Sean Lew
Author: Cheng Few Lee
Author: Long Kang
Author: Anil K. Bera
Author: 
Author: Min Hwang