The Institute funded the following projects since 2000.  Many of these projects have been completed and therefore also are described on the Recently Completed Projects page. 

2007
2006
2005
2004
2003
2002
2001
2000

Recently Completed Projects

 

PROJECTS FUNDED IN 2006

Hedge Funds Activism, Corporate Governance, and Firm Performance

Alon Brav, Duke
Wei Jiang, Columbia

With over a trillion dollars of capital at the disposal of U.S.-based hedge funds, and a quarter trillion dollars in European funds, hedge fund managers have been aggressively looking for attractive investment opportunities and, in particular, have changed the role that they play in the corporate governance of publicly traded companies.  Indeed, over the last few years we have witnessed a surge in hedge fund activism, ranging from proposals or proxy contests aimed at changing companies’ payout policies, acquisition decisions, or executive compensation, to full-scale take-over bids.  This new form of activism has led to a heated debate as to whether it helps or harms the economic and financial health of target companies.  Some argue that activism results in higher firm productivity and growth and thus higher shareholder value.  Others are concerned that hedge funds’ actions generate short run profits at the expense of long-term shareholder value.  To date, there has not been an empirical study with a focus on the determinants and consequences of hedge fund activism.  With this project we intend to fill this gap.  We plan to hand-collect a comprehensive event-based sample from various SEC and media sources, and perform an empirical study on the causes, nature and consequences of hedge fund activism.  We believe that the evidence and conclusions from this project will provide a useful benchmark for law and policy makers, institutional investors, corporate boards and managers, as well as to researchers. 

This study investigates hedge fund activism.  What types of companies do hedge funds target and does their activism increase or decrease corporate productivity?  Since hedge funds often hold larger, more concentrated positions in securities than do mutual funds, their activism may be of greater importance than the activism of other investors. 

A Tale of Two Anomalies: The Implication of Investor Attention for Price and Earnings Momentum 

Kewei Hou , Ohio State
Lin Peng, Baruch College
Wei Xiong, Princeton

In this project, we examine the profitability of price and earnings momentum strategies.  We find that price momentum profits are higher among high volume stocks and in up markets, while earnings momentum profits are higher among low volume stocks and in down markets.  In the long run, price momentum profits are reversed, while earnings momentum profits are not.  The dichotomy between price and earnings momentum is more pronounced when we orthogonalize one with respect to the other.  To the extent that trading volume increases with investor attention and that investors tend to pay more attention to stocks in up markets, our results suggest a dual role for investor attention: while price underreaction to earnings news declines with investor attention, price continuation caused by investors' overreaction rises with attention.

Price and earnings momentum strategies are among the most common quantitative strategies pursued by active managers.  The inter-relationship between these two forms of momentum, and their separate dependencies on trading volume therefore should be of interest to our members.

The Effect of Short Sales Constraints on Shorting Volume and Price Formation 

Paul Asquith, MIT
Parag Pathak, Harvard

This project investigates the role of short sales constraints on shorting volume and price formation.  Using newly released data from the SEC's Regulation SHO of every short trade from 2005, combined with proprietary data rebate rate data from two large lenders, who make a market in over 90% of the our universe and account for over 17% of all short sale transactions, we provide a detailed empirical description of the costs of short trades.  We focus on four costs: 1) locating shares to borrow, 2) price charged by lenders, 3) uptick rule and 4) recall risk.  For each cost we document its empirical magnitude and investigate its effect on stock mispricing.

This study investigates the costs of shorting and the effect of those costs on stock prices.  With the growth of 130/30 funds and other long/short funds, more and more managers are shorting stocks.  Knowing what the costs of shorting have been and their effect on stock prices may help to gauge the future impact of increased short-selling.

The True Cost of Asset Management: Beta-Adjusted Fees

Jacob (Kobi) Boudoukh, NYU
Matthew P. Richardson, NYY
Richard H. Stanton, Berkeley
Robert F. Whitelaw, NYU

The majority of research on hedge funds, private equity funds and venture capital funds focuses on the risk/return profile of these funds, ignoring the crucial role of ex ante fees.  In this paper we focus on the interaction between ex ante fees and the investment’s risk characteristics.  We consider the different sources of fund risk and ask how much investors pay ex ante for alpha.  The main idea is quite simple:  while beta risk is nearly free and investors should only be willing to pay high fees for alpha, funds charge a high fee which is at least partly a function of total volatility (market risk plus fund specific alpha-related risk).  We show, both empirically as well as theoretically, that, depending on the beta, effective fees could in some cases be huge. 

Investment management fees matter to plan sponsors and participants, investment manager, investment consultants and others. Although a single fee often purchases exposure to multiple types of risk, little work has been done to characterize the relation between fees and risk components.  This project should provide a deeper understanding of the economics of investment management fees, in particular how much different types of managers charge for alpha and for beta.

Stock Price Jumps and Return Predictability

George Jiang, Arizona
Tong Yao , Arizona

In this study, we propose a new methodology to empirically investigate the predictability of cross-sectional stock returns.  Our focus is about one particular type of stock price changes, i.e., those large and discontinuous price movements known as jumps.  We use recently developed statistical techniques to identify jumps in stock prices, and examine the relation with various well-known return predictive variables.  Our research can shed new lights on cross-sectional stock return predictability, and improve our understanding of competing explanations to asset return anomalies.  Our research also offers practical value to investment professionals through improving the timing aspect of investment strategies.

Extreme volatility affects many investment strategies, and most particularly quantitative strategies using options.  For many of our members, discrete price jumps represent either their greatest risks or their greatest opportunities.  Thus, any methods that can help us better identify which securities are most subject to these jumps should be of interest.

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PROJECTS FUNDED IN 2005

The Rise of Teams in Fund Management

Massimo Massa, INSEAD
Jonathan Reuter, University of Oregon
Eric W. Zitzewitz, Stanford University

Increasingly, mutual funds are turning from named portfolio managers to unnamed management teams.  We propose to study the impact of this decision on managerial incentives and investor perceptions.  On the one hand, we expect that associating a fund's performance with a particular manager will generate higher inflows through more positive media mentions and higher returns.  On the other hand, we expect that the use of unnamed management teams will limit the rents a high-performing manager can extract from the family by threatening to depart, and will increase the demand spillovers from one fund's performance to the other funds in its family.

The Research Committee expects that this research will help our membership better understand the costs and incentives associated with alternative management contracts.  Since many of our members participate in these contracts, we expect that the results should better inform decisions about how to structure their businesses.

Market Volatility, Investor Flows, and the Structure of Hedge Fund Markets

Link to PDF File: Market Volatility, Investor Flows, and the Structure of Hedge Fund Markets

Bill Ding, SUNY, Albany
Mila Getmansky, University of Massachusetts
Bing Liang, University of Massachusetts
Russell R. Wermers, University of Maryland

Market observers and regulators often cite hedge funds as contributing substantially to the volatility of financial markets.  In this project, we will study the characteristics of funds, and the structure of fund categories, that impact investor flows to these funds and fund categories.  Further, we will test whether the structure of certain hedge funds, or hedge fund categories are more conducive to flows contributing to excessive market volatility, especially during extreme market events.  Our study, by examining the impact of flows on the markets in which hedge funds invest, will provide an important, new perspective for investors in these funds.

The Research Committee expects that this research will help our membership better understand the factors that determine how sponsors allocate and withdraw the one trillion dollars that they now entrust to hedge funds.  Since many of our members operate hedge funds, complete with them, or fund them, we expect that the results will allow them to better understand the environment within which they operate.

Informed and Strategic Order Flow in Bond and Stock Markets

Link to PDF File: Informed and Strategic Order Flow in Bond and Stock Markets

Paolo Pasquariello, University of Michigan
Clara Vega, University of Rochester

We study the role of private and public information in the U.S. Treasury bond market.  We develop a model of speculative trading in the presence of two realistic market frictions—information heterogeneity and imperfect competition among informed traders—and a public signal.  We test its implications by analyzing the response of two-year, five-year, and ten-year U.S. bond yields to order flow and real-time U.S. macroeconomic news.  We find strong evidence of informational effects:  unanticipated order flow has a significant and permanent impact on daily bond yield changes during both announcement and non-announcement days.  Our analysis further shows that, consistent with our model, the contemporaneous correlation between order flow and yield change is higher when the dispersion of beliefs among market participants is high and public announcements are noisy. 

The Research Committee expects that this research will help our membership better understand how what factors determine prices in the U.S. Treasury bond markets.  The results will interest our member who trade Treasury bonds or how use signals from the Treasury bond markets when making other trading decisions.

Who Monitors the Mutual Fund Manager, New or Old Shareholders?

Woodrow T. Johnson, University of Oregon

When shareholders consider investing in a new fund, they presumably have access to several alternatives and ultimately choose a top-performing fund.  Do shareholders trade in response to returns thereafter?  This paper explores this question by decomposing the within-fund return-flow relationship.  The first stage of the analysis compares buys with sells to see whether shareholders sell poor returns with the same vigilance they buy good returns.  The second stage tests whether the return-buy relationships for account-opening buys and post-opening buys are the same.  The final stage examines why shareholders do not sell in response to poor returns.

The Research Committee expects that this research will help our membership better understand the factors that make mutual fund flows sticky.  The results have implications for our members who need to predict and accommodate fund flows, or who must allocate managerial talent to maximize funds under management.  The results may also inform our members who use fund flows to make investment decisions.

Operational Risk

Link to PDF File: Operational Risk

Robert Jarrow, Cornell University

The purpose of this proposal is to provide an economic and mathematical characterization of operational risk, useful for quantification and estimation.  This characterization will be based on insights from the corporate finance and credit risk literatures. From the corporate finance literature, the notion of agency costs will be crucial in characterizing operational risk.  From the credit risk literature, the mathematical characterization of jumps in asset values will be utilized, in an arbitrage-free setting.  Estimation of the model's parameters will be discussed, but an empirical investigation is left for subsequent research.

The Research Committee expects that this research will produce tools that will allow our membership to better quantify and thus manage operational risk.  All management firms and their sponsors face operational risk in additional to the many other risks with which we are so familiar.  The proposed research will provide a framework within which these risks and their implications for the investment management process can be better quantified.

 

 

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PROJECTS FUNDED IN 2004

The Selection and Termination of Investment Managers by Plan Sponsors

Amit Goyal, Emory University
Sunil Wahal, Emory University

We examine the selection and termination of investment managers by plan sponsors. We build a unique dataset that comprises hiring and firing decisions by approximately 3,600 plan sponsors over a 10-year period from 1994 to 2003. We find that plan sponsors hire investment managers after these managers earn large positive excess returns up to three years prior to hiring. Despite general persistence in investment manager returns, this return chasing behavior does not deliver positive excess returns thereafter; post-hiring excess returns are indistinguishable from zero. Plan sponsors terminate investment managers after underperformance but excess returns after being firing are frequently positive.

Hedge Fund Performance Evaluation: A Stochastic Discount Factor Approach

Warren Bailey, Cornell University
Haitao Li, Cornell University
Xiaoyan Zhang, Cornell University

We provide a comprehensive empirical analysis of hedge performance using the stochastic discount factor (SDF) approach. We explicitly take into account the no-arbitrage restriction on asset pricing models, which ensures appropriate valuation of derivatives and dynamic trading strategies used by hedge funds. Using the SDFs of a wide variety of asset pricing models, we evaluate the performance of hedge fund portfolios sorted on styles and characteristics. Without the no-arbitrage restriction, a few models are able to explain the hedge fund returns. With such restriction, these models fail to explain the returns on a couple of style portfolios.

Option Valuation with a Multifactor Term Structure of Volatility

Link to PDF File: Option Valuation with a Multifactor Term Structure of Volatility

Peter Christoffersen, McGill University
Steve Heston, University of Maryland
Kris Jacobs, McGill University

The substantial academic literature on theoretically sound improvements to the seminal Black-Scholes model has left industry practice largely unaffected. Option traders recognize the systematic biases in the Black-Scholes model, but typically rely on non-theoretical curve fitting methods to match observed implied volatility surfaces. Standard stochastic volatility models such as Heston (1993) reduce the biases of the Black-Scholes model, but are unable to remove these biases completely. The objective of our study is to reduce the gap between industry and academia by establishing and implementing a parsimonious two-factor stochastic volatility model. The model is empirically tractable, in that the option valuation formula is available in closed form, and relatively parsimonious.

Option Coskewness and Capital Asset Pricing

Joel M. Vanden, Dartmouth College

Today there is considerable empirical evidence suggesting that at least some options in the economy are nonredundant assets. Furthermore, it is well known from the work of Kraus and Litzenberger (1976), Harvey and Siddique (2000), and Dittmar (2002) that higher order moments such as coskewness and cokurtosis are important for explaining risky asset returns. The goal of this research project is to investigate the intersection of these two lines of literature by showing how the market coskewness and market coskurtosis models are altered when a nonredundant option is optimally traded. Due to the nonredundancy of the option, it is shown that the economy's stochastic discount factor depends not only on the market return and the square of the market return, but also on the option return, the square of the option return, and the product of the market and option returns. This leads to an asset pricing model in which the expected return on any risky asset depends explicitly on the asset's coskewness with option returns. The empirical results suggest that option coskewness may capture some of the same risks as the Fama-French factors SMB and HML. Furthermore, the option coskewness model outperforms several competing benchmark models. These results suggest that the factors that drive the pricing of nonredundant options may also important for pricing risky equities.

Understanding Commodity Futures: Data Construction and Tests

Gary Gorton, University of Pennsylvania
Geert Rouwenhorst, Yale University

Commodity futures are one of the oldest asset classes, yet little is know about commodity futures. The main reason for this appears to be a lack of data. There are no long time series of commodity futures returns; no benchmark index that extends back very far, and no panel data of significant length. Existing indices are short or cannot be reproduced (because of lost data over the years). We propose to build a comprehensive data set of commodity futures returns in order to study basic properties of commodity futures and to test hypotheses about commodity futures. We have already built a data set of commodity futures monthly returns back to 1959 for commodity futures traded on the CBOT, CME, and LME. See our attached paper “Facts and Fantasies about Commodity Futures.” The plan for the proposed project is fourfold: (1) for the current data set that we have constructed we want to fill in the contracts that were traded in the past, but that are not traded now (these were omitted from the source data that we used); (2) we want to extend the commodity futures return series back in time – if possible to the start of futures trading in the US in the 1850s; (3) we want to recalculate and investigate the stylized facts that we have computed in the current working paper; (4) we want to test hypotheses concerning why futures markets exist.

Relatively little is known about commodity futures as an asset class. We believe that the construction of a data set that has long times series, the documentation of basic stylized facts about commodities, as well as information in the form of tests of hypotheses about the existence of these markets, will be very valuable for the investment community.

 

 

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PROJECTS FUNDED IN 2003

How Much Error Is in The Tracking Error? A Study of the Impact of Estimation Risk on Mutual Fund Tracking Errors

Andrew F. Siegel, University of Washington
Artemiza Woodgate, University of Washington

A mutual fund's tracking error is considered to be a very important measure of performance, and the tracking error volatility is an important measure of the fund's risk. We propose to look at the impact of estimation risk on these measures and derive closed form formulae for the anticipated mean and variance of the tracking error after adjusting for estimation risk bias. We will test these formulae through simulations and using real data from Morgan Stanley Indices. Additionally we will look at how trading costs are affected by the bias adjustment, and how short-sales or risk constraints affect the adjustment.

A Conditional Characteristics Model of Stock Prices

Link to PDF File: A Conditional Characteristics Model of Stock Prices

Malcolm Baker, Harvard University
Jeffrey Wurgler, New York University

We propose to examine how investor sentiment affects the cross-section of stock returns. Theory predicts that a broad wave of sentiment will disproportionately affect stocks whose valuations are highly subjective and are difficult to arbitrage. We plan to test this prediction by studying how the cross-section of subsequent stock returns varies with proxies for beginning-of-period investor sentiment. When the sentiment is low, we expect subsequent returns on smaller, high volatility, unprofitable, no-dividend-paying, extreme-growth, and distressed stocks to be relatively high, consistent with an initial underpricing of these stocks. When sentiment is high, we expect these patterns to attenuate or fully reverse.

Closing Time? The Signaling Content of Mutual Fund Closures

Link to PDF File: Closing Time? The Signaling Content of Mutual Fund Closures

Arturo Bris, Yale School of Management
Huseyin Gulen, Virginia Tech
Padma Kadiyala, Fairleigh Dickinson University
P. Raghavendra Rau, Purdue University

We analyze why managers of open-ended mutual funds choose to close their funds to new investment. We use a multi-period signaling model to derive the optimal closing and reopening decision for fund managers when fund performance is a noisy indicator of managerial skill. The model predicts that funds close when they are sufficiently large and when the population of high-quality managers is low. We test the empirical predictions of the model on a sample of 141 mutual funds that closed to new investment between 1992 and 2002. Our most important finding is that the length of the fund closure period is a significant predictor of excess fund flows at reopening.

Market Frictions, Price Delay, and the Cross-Section of Expected Returns

Link to PDF File: Market Frictions, Price Delay, and the Cross-Section of Expected Returns

Kewei Hou, Ohio State University
Tobias J. Moskowitz, University of Chicago

We parsimoniously characterize the severity of market frictions affecting a stock using the average delay with which its share price responds to information. The most severely delayed firms command a large return premium that captures the size effect and part of the value premium. Moreover, idiosyncratic risk is priced only among the most delayed firms. These results are not explained by other sources of return premia, microstructure, or traditional liquidity effects (price impact and cost), but appear most consistent with investor recognition. The very small segment of extremely delayed, neglected firms captures substantial variation in cross-sectional average returns.

Optimal Asset Allocation and Risk Shifting Incentives in Money Management

Suleyman Basak, London Business School and CEPR
Anna Pavlova, Massachusetts Institute of Technology
Alex Shapiro, New York University

Money managers are reward for increasing the value of assets under management, and predominately so in the mutual fund industry. In a dynamic asset allocation framework, we show that as the year-end approaches, the ensuing convexities in the manager’s objective induce her to closely mimic the index, relative to which her performance is evaluated, when the fund’s year-t-date return is sufficiently high. As her relative performance falls behind, she chooses to deviate from the index by either increasing or decreasing the volatility of her portfolio. The maximum deviation is achieved at a critical level of underperformance. It may be optimal for the manager to reach such deviation via selling the risky asset despite it positive risk premium. The manager’s policy results in economically significant departures from investors’ desired risk exposure. We then demonstrate how constraining the managers’ invest mend opportunity set, via a simple benchmarking restriction, can ameliorate the adverse effects of managerial incentives. Finally, we employ data on mutual funds holdings to provide empirical support for our implications regarding managerial risk-taking incentives. In that we differ from the existing literature that used portfolio volatility as a measure of risk-taking.

 

 

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PROJECTS FUNDED IN 2002

Indices of Demand and Supply in Asset Markets with an Application to Formation of a Constant Liquidity Index for Real Estate

Jeffrey Fisher, Indiana University
Dean H. Gatzlaff, Florida State University
David Geltner, Massachusetts Institute of Technology
Donald Haurin, Ohio State University

In some asset markets, the transaction price represents both value and liquidity. Introducing liquidity requires modeling the underlying search process of asset buyers and sellers. Not all assets sell at each point in time, which introduces concepts such as time-on-market and ease-of-selling the asset. We characterize how the buyer-seller match process changes over a market’s cycle, highlighting the role of transaction volume. We then show how standard price indices used to measure changes in the value of assets such as commercial and residential property are flawed and we separate the impact of changing value of the asset from changing liquidity. We will apply our theory to calculate the periodic returns of properties in the NCREIF index of commercial real estate.

What Are Assets under Management Worth to Managers?

Susan Christoffersen, McGill University
Rene Garcia, CIRANO
David K. Musto, University of Pennsylvania

What is a dollar under management worth to the manager? It depends how long the manager expects it to stay; the longer it stays, the longer the manager collects fees and therefore the more it is worth. We will develop a model relating a fund’s outflows to its earlier inflows, with particular attention to the circumstances of the original inflows, such as the recent performance of the fund, its category or its asset class, and also to the fund’s attrition. Our results will bear on the incentives provided by fund flows, and also on the valuation of investment advisory contracts.

Taxes, Estate Planning and Financial Theory: New Insights and Perspectives

Link to PDF File: Taxes, Estate Planning and Financial Theory: New Insights and Perspectives

Robert Dammon, Carnegie-Mellon University
Chester Spatt, Carnegie Mellon University
Harold Zhang, University of North Carolina

We provide insight into conventional approaches to estate planning and suggest how to enhance these strategies. For example, we show that the advantage of resetting the investor’s capital gains tax bases to the market value at the time of death is greater for individual rather than joint ownership of assets, provided that at the first death of one of the owners the basis is reset to an average of the date of death value and the survivor’s original cost. Furthermore, we analyze asset location and distribution policies for the beneficiary’s direct funds as well as trusts that are outside his taxable estate, highlighting the effect of estate taxation and reset of the capital gains tax basis at death. Finally, we examine the value and importance of borrowing in estate planning.

A Rational Model of Active Portfolio Management

Richard Green, Carnegie-Mellon University
Jonathan Berk, University of California, Berkeley

The objective of this research proposal is to develop a rational model of active portfolio management. Such a model provides a natural benchmark against which to evaluate several features of the fund management industry. Using this model we will show that many of the effects that are widely regarded as anomalous are consistent with the rational paradigm. A puzzle that remains to be tackled is the existence of two different compensation contracts in the money management process. A second stage of this research proposal will extend the model. We hope to use the model to understand why the two types of compensation contracts co-exist.

Evaluating Fixed Income Fund Performance with Stochastic Discount Factors

Wayne Ferson, Boston College
Darren Kisgen, University of Washington
Tyler Henry, University of Washington

We evaluate the performance of fixed income mutual funds using stochastic discount factors from continuous-time term structure models. We also provide the first conditional performance evaluation for US fixed income mutual funds, conditioning on a variety of discrete ex ante characterizations of the state of the term structure and the economy. Preliminary results suggest that the additional empirical factors that arise when the term structure models are time-aggregated for discrete data contribute to an improved performance of the models. Fixed income funds return less than passive benchmarks that don't pay expenses, but not in all economic states.

Understanding Comovement

Nicholas Barberis, University of Chicago
Andrei Shleifer, Harvard University
Jeffrey Wurgler, New York University

A number of studies have identified patterns of positive correlation of returns, or comovement, among different traded securities. The traditional view of comovement explains these patterns with a positive correlation in fundamental values. We model tow alternative views, which attribute comovement to investor trading patterns in markets with imperfect arbitrage, and then assess them empirically using data on revisions in the S&P 500 Index. Index revisions are noteworthy because they change the way a stock is traded but not its fundamentals. Using a variety of regression specifications, we finds that, when a stock is added to the index, its beta and R-squared with respect to the index increase, while it beta with respect to stocks outside the index falls. The converse happens when a stock is deleted. These results support the predictions of the trading-based models of comovement but not the fundamentals view. We argue that trading-based models may help explain other instances of comovement in the data.

 

 

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PROJECTS FUNDED IN 2001

Downside Risk, Cross-Sectional Equity Returns and the Momentum Effect

Link to PDF File: Downside Risk, Cross-Sectional Equity Returns and the Momentum Effect

Joe Chen, University of Southern California
Andrew Ang, Columbia University
Yuhang Xing, Columbia University

Stocks with greater downside risk, which is measured by higher correlations conditional on downside moves of the market, have higher returns. After controlling for the market beta, the size effect and the book-to-market effect, the average rate of return on stocks with the greatest downside risk exceeds the average rate of return on stocks with the least downside risk by 6.55% per annum. Downside risk is important for explaining the cross-section of expected returns. In particular, the authors find that some of the profitability of investing in momentum strategies can be explained as compensation for bearing high exposure to downside risk.

Getting Squeezed: Market Manipulation in US Equity Markets

Owen Lamont, University of Chicago

The author will study intentional “short squeezes” in US equity markets, defined as situations in which short-sellers are forced to cover their short position. He will focus on legal market manipulation, in which firm management attempts to force short sellers to close their position. Management can attack short sellers by publicly coordinating an attempt to deny short sellers the ability to borrow shares, by taking legal action against short sellers, or by publicly denouncing them. Lamont will study the effect of short squeezes on stock prices, whether this effect is temporary or permanent, and the long-term returns to holding squeezed stocks.

Informed Trading in Stock and Option Markets

Stewart Mayhew, University of Georgia
Sugato Chakravarty, Purdue University
Huseyin Gulen, Virginia Tech

The authors propose to investigate how much price discovery occurs in the option market, as compared to the underlying stock market. Using six years of transactions data on sixty stocks from ISSM and the Berkeley Options Database, they will employ the techniques of Hasbrouck (1995) and Harris, McInish and Wood (2001) to estimate the proportion of price discovery occurring in each market for each stock, each month. Then, they will test whether significant price discovery occurs in the option market, and whether factors such as trading volume or volatility can help explain cross-sectional and time-series variation in these measures.

Evidence on the Speed of Convergence to Market Efficiency

Tarun Chordia, Emory University
Richard Roll, UCLA
Avanidhar Subrahmanyam, UCLA

Order imbalances for large and mid-cap stocks listed on the New York Exchange are highly persistent from day to day. In contrast, daily returns on the same stocks have no serial dependence. These two empirical facts can be reconciled if arbitrageurs react to order imbalances within the trading day by engaging in countervailing trades sufficient to remove serial dependence over the daily horizon. How long does this actually take? The authors propose to study the pattern of intra-day serial dependence, over intervals ranging from five minutes to one hour, to uncover traces of arbitrage.

Style Drift

Russ Wermers, University of Maryland

Prior research has used regression techniques to extract style information from the net returns data of professionally managed portfolios. While easy to apply, these methods cannot capture the dynamic nature of style loadings through time. This study proposes new portfolio holdings-based measures that precisely track the style characteristics of a fund through time. Specifically, the author will decompose style drift into drift in each style dimension (e.g., size, book-to-market, momentum, or liquidity), as well as decomposing drift into “active” and “passive” components. Finally, he will measure the impact of both passive and active drift on the performance of funds.

 

 

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PROJECTS FUNDED IN 2000

Takeover Defenses at IPO Firms

Laura Casares Field, Pennsylvania State University
Jonathan M. Karpoff, Washington State University

Contrary to widespread belief, many firms deploy anti-takeover defenses before they go public. The authors propose to document the use of takeover defenses in IPO firms, the characteristics of IPO firms that deploy defenses, and the defenses' effects on acquisition likelihood and takeover premiums. Work to date indicates that IPO managers deploy takeover defenses particularly when their personal benefits are high and they can shift costs of takeover protection to non-management pre-IPO shareholders. The presence of a takeover defense in IPO firms is negatively related to acquisition likelihood, yet has no impact on takeover premiums for firms that are acquired.

The International Costs of Equity Trading in Emerging Markets

David A. Lesmond, Tulane University

Over the past decade, world stock market capitalization rose from $4.7 trillion to $15.2 trillion, and emerging market capitalization rose from less than 4% to 13% of total world capitalization in 1995. World Bank estimates of net long-term financial flows to developing countries in 1995 was over $45 billion from a mere $0.1 billion in 1985. While risk, volatility, and correlation have been analyzed for emerging markets, no study has attempted to measure the trading costs or measure the liquidity based risk factors that arise from liquidity concerns. The dramatic increase in both market value and international financial flows in emerging economies underscores the importance in determining the costs of trading securities in these economies and other risk measures that result from that trade. The researchers will obtain trading cost estimates for both securities listed in emerging markets as well as their American Depositor Receipt (ADR) or Global Depositor Receipt (GDR) counterpart, where they apply, to gauge trading cost magnitudes and differences. Additionally, they will estimate liquidity risk to gauge potential price impact effects of informed trading. The study will examine over 30 different emerging country exchanges to provide a very comprehensive characterization of global trading costs.

Stocks Are Special Too: An Analysis of the Costs of Short-Selling

Christopher Geczy, University of Pennsylvania
David Musto, University of Pennsylvania
Adam Reed, University of Pennsylvania

The authors propose to analyze the price of borrowing a given security using methods developed to leverage a proprietary base of short interest rebate data collected from large hypothecators of equities. They posit a number of factors to explain the cost of borrowing securities for the purposes of short-selling and they develop a corresponding empirical model for it. They will use this model to estimate the potential profit funds may expect to make by lending their shares. The results will also directly characterize the inherent costs that security borrowers face. Finally, the data and methods utilized in the study will permit exploration of the link between short-selling activity and borrowing costs.

Commonality in Order Flow, Returns and Trading Costs: Causes and Effects

Jarrad Harford, University of Oregon
Aditya Kaul, University of Oregon

The authors will examine common factors in order flow, returns and trading costs by comparing such commonalities through time and across stocks in the S&P 500 index and the rest of the universe. They will document the magnitude of order flow commonalities induced by institutional trading, as well as the growth in such commonalities over the past 15 years. They will also document the effects of these commonalities on prices and trading costs. Finally, they will examine whether market-makers in electronic markets (notably, NASDAQ) are better able to monitor contemporaneous trading activity in other S&P 500 stocks than is the specialist.

Family Values and the Star Phenomenon

Vikram Nanda, University of Michigan
Z. Jay Wang, University of Michigan
Lu Zheng, University of Michigan

Most mutual funds belong to fund families. The authors propose to investigate the impact of family structure on fund strategy to attract investor funds – and, in turn, the effect of such strategies on the size and nature of the fund family. Preliminary results indicate that there is a strong positive spillover effect of a star performer, resulting in higher cash inflow for other funds in the family as well. A family can raise the probability of obtaining a star performer by increasing family size and making the fund returns more negatively correlated. Factors that increase the odds of producing a star are also ones associated with a lower average performance.