Statistical analysis of illiquidity risk and premium in financial price signals

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 185-188).Price is the most visible signal produced by competition and interaction among a complex ecology of entities in a system called financial markets. This thesis deals with statistical analysis and model identification based on such signals. We approach this problem at various levels of abstraction, with a particular emphasis on linking certain statistical anomalies identified to specific frictions that are only observable in a more microscopic view.We first give a brief review of the framework for the analysis of financial prices. We highlight the important role of information by introducing the concept of informational efficiency. The main body consists of two parts. Part A consists of Chapters 3, 4 and 5. We first link unpredictability of financial returns, a direct consequence of the informational efficiency, to the expected covariance structure of resulting return signals. We discuss a particular algorithm designed to detect the existence of weak mean-reverting component in the observed returns. Applying this detection scheme to US stock returns between 1995 and 2007, we detect a statistically significant but continually decreasing mean-reverting component in the returns. To explain this observation, we link the mean-reverting component to the arrival structure of buyers and sellers and their interactions. We discuss a particular model for this interaction and apply various tests to establish the validity of the proposed model. Part A concludes with an application of these tools in analyzing the sequence of events in August 2007 which resulted in a breakdown of normal behavior of the system.Part B, consisting of Chapters 6 and 7, also deals with the issue of predictability in financial returns, but at a different frequency and based on a different set of instruments. We first produce the evidence for an unusually high level of predictability among returns of certain classes of hedge funds. To explain this observation, we discuss a model built based on the notion of partially observed price signals. When prices are not observed, for example due to lack of trading, the most recent price is used to calculate the value of an investment, and this process results in perceived serial correlation in the calculated returns. We view this lack of trading as the second example of friction in this system, and set out to link this friction to the mean of the resulting returns signals. We find strong link between predictability and first moment in certain groups of returns used.by Amir E. Khandani.Ph.D

IPO underpricing and after-market liquidity

The underpricing of the shares sold through Initial Public Offerings (IPOs) is generally explained with asymmetric information and risk. We complement these traditional explanations with a new theory. Investors who buy IPO shares are also concerned by expected liquidity and by the uncertainty about its level when shares start trading on the after-market. The less liquid shares are expected to be, and the less predictable their liquidity is, the larger will be the amount of "money left on the table" by the issuer. We present a model that integrates such liquidity concerns within a traditional framework with adverse selection and risk. The model's predictions are supported by evidence from a sample of 337 British IPOs effected between 1998 and 2000. Using various measures of liquidity, we find that expected after-market liquidity and liquidity risk are important determinants of IPO underpricing, after controlling for variables traditionally used to explain underpricing.liquidity, initial public offering, post-IPO market, after-market trading

Information in the term structure of yield curve volatility

We study information in the volatility of US Treasuries. We propose a no-arbitrage term structure model with a stochastic covariance of risks in the economy, and estimate it using high-frequency data and options. We identify volatilities of the expected short rate and of the term premium. Volatility of short rate expectations rises ahead of recessions and during stress in financial markets, while term premium volatility increases in the aftermath. Volatile short rate expectations predict economic activity independently of the term spread at horizons up to one year, and are related to measures of monetary policy uncertainty. The term premium volatility comoves with a more general level of economic policy uncertainty. We also study channels through which volatility affects model-based inference about the yield curve

"The Contributions of Professors Fischer Black, Robert Merton, and Myron Scholes to the Financial Services Industry"

This paper is written as a tribute to Professors Robert Merton and Myron Scholes, winners of the 1997 Nobel Prize in economics, as well as to their collaborator, the late Professor Fischer Black. We first provide a brief and very selective review of their seminal work in contingent claims pricing. We then provide an overview of some of the recent research on stock price dynamics as it relates to contingent claim pricing. The continuing intensity of this research, some 25 years after the publication of the original Black-Scholes paper, must surely be regarded as the ultimate tribute to their work. We discuss jump-diffusion and stochastic volatility models, subordinated models, fractal models, and generalized binomial tree models, for stock price dynamics and option pricing. We also address questions as to whether derivatives trading poses a systemic risk in the context of models in which stock price movements are endogenized, and give our views on the "LTCM crisis" and liquidity risk.