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Convertible Bond Arbitrageurs as Suppliers of Capital
with Darwin Choi, Brian Henderson and Heather Tookes
Full paper
(pdf)
Abstract: This paper examines the potential
impact of capital supply on security issuance. We focus on
the role of convertible bond arbitrageurs as suppliers of
capital to issuers of convertible bonds. We estimate a
simultaneous equations model of demand and supply of convertible
bond capital, linking the time series of aggregate convertible
bond issuance to measures of capital supply: convertible
bond arbitrage hedge fund flows, returns, and a proxy for
arbitrageurs' use of leverage. We find that issuance is
positively and significantly related to increases in all three
supply measures. To provide further interpretation, we
conduct a second test. We use the
ban on short selling in September and October 2008 as a natural
experiment to examine the impact of an exogenous shock to the
supply of capital from convertible bond arbitrageurs. We
find a significant decline in issuance during the ban.
Results from both empirical
approaches provide evidence that the supply of capital from
convertible bond arbitrageurs impacts issuance.
Crises and Hedge Fund Risk
with Monica
Billio and Loriana Pelizzon
Full
paper (pdf)
Supplementary files
Abstract:
We study the effects of financial crises on hedge fund risk and
show that liquidity, credit, equity market, and volatility are
common risk factors during crises for various hedge fund
strategies. We also apply a novel methodology to identify the
presence of a common latent (idiosyncratic) risk factor exposure
across all hedge fund strategies. If the latent risk factor is
omitted in risk modeling, the resulting effect of financial
crises on hedge fund risk is greatly underestimated. The common
latent factor exposure across the whole hedge fund industry was
present during the Long-Term Capital Management (LTCM) crisis of
1998 and the 2008 Global financial crisis. Other crises
including the subprime mortgage crisis of 2007 affected the
whole hedge fund industry only through classical systematic risk
factors.
Share Restrictions and Investor Flows in the Hedge Fund
Industry
with Bill Ding, Bing Liang and Russ Wermers
Full paper (pdf)
Abstract:
This paper studies the effect of share restrictions on the
flow-performance relation of individual hedge funds.
As such, we reconcile previous research that shows
conflicting results for this relation without explicitly
considering restrictions.
Specifically, we find that hedge funds exhibit a convex
flow-performance relation in the absence of share restrictions
(similar to mutual funds), but exhibit a concave relation in the
presence of restrictions—our evidence is consistent with both a
direct effect of the binding restrictions and an indirect effect
that is due to investors endogenizing expected future binding
restrictions when investing their money.
Further, we find that live funds exhibit a concave
flow-performance relation due to stricter flow restrictions than
defunct funds, which display a convex relation.
Finally, we find that money is “smart,” that is, fund
flows predict future hedge fund performance; however, this
“smart money” effect is eliminated among funds with greater
share restrictions.
Convertible Bond Arbitrage, Liquidity Externalities and
Stock Prices
with Darwin Choi and Heather Tookes, Journal
of Financial Economics, Volume 91, Issue 2, February 2009, Pages
227-251.
Full paper
(pdf)
Abstract: In the context of convertible
bond issuance, we examine the impact of arbitrage activity on
underlying equity markets. In particular, we use changes
in equity short interest following convertible bond issuance to
identify convertible bond arbitrage activity and analyze its
impact on stock market liquidity and prices for the period 1993
to 2006. There is considerable evidence of
arbitrage-induced short selling resulting from issuance.
Moreover, we find strong evidence that this activity is
systematically related to liquidity improvements in the stock.
These results are robust to controlling for the potential
endogeneity of arbitrage activity.
Non-Parametric Analysis of Hedge Fund Returns: New
Insights from High Frequency Data
with Monica Billio and
Loriana Pelizzon, Journal of Alternative Investments
(forthcoming)
Full paper (pdf)
Abstract: This paper examines four daily
hedge fund return indices: MSCI, FTSE, Dow Jones, and HFRX, all
based on investable hedge funds, and three monthly hedge fund
return indices: CSFB Tremont, CISDM, and HFR, which comprise
both investable and non-investable hedge funds. Our study, based
on standard statistical analysis, non-parametric analysis of the
return distribution, and non-parametric regressions with respect
to the S&P 500 index shows that key biases like fund selection,
asset liquidity, data frequency, sample period, and index
construction methodologies are responsible for different
statistical properties of hedge fund indices.
One key variable that
highly affects the statistical properties of hedge fund index
returns is the “investability” of hedge fund indices.
Systemic Risk and Hedge Funds
with Nicholas Chan,
Shane M. Haas and Andrew W. Lo, 2005 (NBER Book Chapter, The
Risks of Financial Institutions)
Full paper (pdf)
Abstract: Systemic risk is commonly
used to describe the possibility of a series of correlated
defaults among financial institutions---typically banks---that
occur over a short period of time, often caused by a single
major event. However, since the collapse of Long Term Capital
Management in 1998, it has become clear that hedge funds are
also involved in systemic risk exposures. The hedge-fund
industry has a symbiotic relationship with the banking sector,
and many banks now operate proprietary trading units that are
organized much like hedge funds. As a result, the risk exposures
of the hedge-fund industry may have a material impact on the
banking sector, resulting in new sources of systemic risks.
In this paper, we attempt to quantify the potential impact of
hedge funds on systemic risk by developing a number of new risk
measures for hedge funds and applying them to individual and
aggregate hedge-fund returns data. These measures include:
illiquidity risk exposure, nonlinear factor models
for hedge-fund and banking-sector indexes, logistic regression
analysis of hedge-fund liquidation probabilities, and aggregate
measures of volatility and distress based on regime-switching
models. Our preliminary findings suggest that the
hedge-fund industry may be heading into a challenging period of
lower expected returns, and that systemic risk is currently on
the rise.
What Drives Hedge Fund Returns? Models of Flows,
Autocorrelation, Optimal Size, Limits to Arbitrage and Fund
Failures
MIT Sloan School of Management Thesis, May 2004
Full paper (pdf)
Abstract: Hedge funds provide an opportunity
for investing with few government regulations and high potential
returns. Since 1980 this has lead to a dramatic 25% annual
increase in the number of hedge funds, with nearly $700 billion
managed by hedge funds in 2003. However, high risks associated
with hedge fund strategies, competition and limited arbitrage
opportunities contributed to an annual attrition rate of 7.10%.
In this thesis, models were developed and tested that describe
the characteristics of fund returns, fund flows, optimal size
and hedge fund life cycles. The TASS hedge fund database
provided by the Tremont Company was used for analysis. In Essay
One, it was found that hedge fund returns are highly serially
correlated compared to the returns of more traditional
investment vehicles such as mutual funds. Several sources of
such high serial correlation were explored and the research
illustrated that the most likely explanation of this derived
from asset illiquidity and smoothing of returns. Illiquid
securities are not actively traded and market prices are not
always available for them. In the case of smoothing, brokers or
managers have the flexibility to report partial returns.
Consequently, for portfolios of illiquid or smoothed securities,
reported returns will tend to be smoother than true economic
returns, thereby understating volatility and increasing
risk-adjusted performance measures such as the Sharpe ratio. An
econometric model of illiquidity exposure was further proposed
and estimators for the smoothing profile as well as a
smoothing-adjusted Sharpe ratio were developed. Estimated
smoothing coefficients were found to vary considerably across
hedge-fund style categories and may be a useful proxy for
quantifying illiquidity exposure. In Essay Two, the life cycles
of hedge funds were analyzed. The findings show that in general,
investors chasing individual fund performance decrease the
probability of an individual hedge fund liquidating. However,
when investors pursue a category of hedge funds that has
performed well, the probability of hedge funds liquidating
within that category increases because of growing competition
among hedge funds; and in such environment, marginal funds are
more likely to be liquidated than funds that deliver superior
risk-adjusted returns. In the Essay, a model was proposed for
calculating an optimal asset size by balancing out the effects
of past returns, fund flows, market impact, competition and
favorable category positioning.
An Econometric Model of Serial Correlation and Illiquidity
in Hedge Fund Returns
with Andrew W. Lo and Igor Makarov,
2004 (Journal of Financial Economics, 74 (3), pp.529-610)
Full paper (pdf)
Abstract: The returns to hedge funds and
other alternative investments are often highly serially
correlated in sharp contrast to the returns of more traditional
investment vehicles such as long-only equity portfolios and
mutual funds. In this paper, we explore several sources of such
serial correlation and show that the most likely explanation is
illiquidity exposure, i.e., investments in securities that are
not actively traded and for which market prices are not always
readily available. For portfolios of illiquid securities,
reported returns will tend to be smoother than true economic
returns, which will understate volatility and increase
risk-adjusted performance measures such as the Sharpe ratio. We
propose an econometric model of illiquidity exposure and develop
estimators for the smoothing profile as well as a
smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds
drawn from the TASS database, we show that our estimated
smoothing coefficients vary considerably across hedge-fund style
categories and may be a useful proxy for quantifying illiquidity
exposure.
Sifting Through the Wreckage: Lessons from Recent
Hedge-Fund Liquidations
with Andrew W. Lo and Shauna X.
Mei, 2004 (Journal of Investment Management, 2(4), Fourth
Quarter, pp.6-38)
Full paper (pdf)
Abstract: We document the empirical
properties of a sample of 1,765 funds in the TASS Hedge Fund
database from 1994 to 2004 that are no longer active. The
TASS sample shows that attrition rates differ significantly
across investment styles, from a low of 5.2% per year on average
for convertible arbitrage funds to a high of 14.4% per year on
average for managed futures funds. We relate a number of
factors to these attrition rates, including past performance,
volatility, and investment style, and also document differences
in illiquidity risk between active and liquidated funds.
We conclude with a proposal for the U.S. Securities and Exchange
Commission to play a new role in promoting grater transparency
and stability in the hedge-fund industry.
The Life Cycle of Hedge Funds: Fund Flows, Size and
Performance,
2004 (Job Market Paper)
Full paper (pdf)
Abstract: Since the 1980s we have seen a 25%
yearly increase in the number of hedge funds, and an annual
attrition rate of 7.10% due to liquidation. This paper analyzes
the life cycles of hedge funds. Using the TASS database provided
by the Tremont Company, it studies industry and fund specific
factors that affect the survival probability of hedge funds. The
findings show that in general, investors chasing individual fund
performance decrease probabilities of hedge funds liquidating.
However, if investors follow a category of hedge funds that has
performed well, then the probability of hedge funds liquidating
in this category increases. We interpret this finding as a
result of competition among hedge funds in a category. As
competition increases, marginal funds are more likely to be
liquidated than funds that deliver superior risk-adjusted
returns. We also find that there is a concave relationship
between performance and assets under management. The implication
of this study is that an optimal asset size can be obtained by
balancing out the effects of past returns, fund flows, market
impact, competition and favorable category positioning that are
modeled in the paper. Hedge funds in illiquid categories are
subject to high market impact, have limited investment
opportunities, and are more likely to exhibit an optimal size
behavior compared to those in more liquid hedge fund categories.
Limits to Arbitrage: Understanding How
Hedge Funds Fail
with Andrew W. Lo, 2004
Abstract: Even if arbitrage opportunities can
be found in statistical sense, they might not be exploitable.
This paper models such limits to arbitrage in the framework of a
hedge fund. In particular, the paper explores how hedge funds
fail given arbitrage opportunities. Dynamic relationships
between a hedge fund, dealers, a bank, and market are modeled.
As a case study, Long Term Capital Management is studied. The
model explores a phenomenon that a fund manager who engages in
arbitrage and uses high leverage might lose all his money before
realizing positions at a profit. As assets go down in value, the
firm has to post more collateral. If it is unavailable, this
often leads to a hedge fund collapse. However, given that
positions are well diversified and not closely correlated,
leverage by itself does not lead to collapse of a fund.
Correlated positions in the absence of leverage might lead to a
loss, but are not subject to collateral collapse. However, the
superimposition of both leverage and induced high correlation
between assets can lead to collapse. The paper explores these
"flight to quality" and "collateral collapse" dynamics.
The Dynamics of Global Financial Crises
with Kevin
Amonlidviman, Andrew W. Lo, and Rishi Kumar, 2003
Full paper (pdf)
Abstract: This paper presents a Markov chain
model of the transmission of financial crises. Using bilateral
trade data and a measure of exchange market pressure, a method
to determine a set of transition probabilities that describes
the crisis transmission dynamics is developed. The dynamics are
characterized by one-month conditional crisis probabilities and
the probability of a crisis occurring within one year. The
framework allows for modeling and comparing various channels of
contagion, such as investments and bilateral trade. Using
macroeconomic data on 45 countries, the model predicts and gives
insights into all of the financial crises that we studied:
Mexico (1994), Asia (1997), Russia (1998), Brazil (1999), Turkey
(2001), and Argentina (2002).
Extrapolation Expectations: An Explanation for Excess
Volatility and Overreaction
with Jannette Papastaikoudi,
2002
Abstract: In this paper, we explain excess
market volatility by means of momentum and acting on analysts'
forecasts. We show excessive price movements with respect to
fundamentals can be caused either by "irrational" trend chasing
behavior of investors, or by trading too often based on
experienced analysts' forecasts (in case of continuous
earnings). Price volatility depends on the prevalent investor
type and on the type of analysts an investor listens to. Within
our market framework, price setting mechanisms are introduced
based on demand/supply balance and on trading strategies. In
forming their demand, investors consider three factors: their
beliefs about the intrinsic value of the marketed assets, past
stock performance, and predictions of financial analysts of
assets' price targets.
Understanding Hedge Fund Failure, 2007
Abstract: This paper studies structural and
statistical properties of major hedge fund collapses. Several
variables such as investment and accounting strategy, crisis
outcome, internal dynamics, fee structure, performance,
leverage, asset types, geographical location of investments,
transparency, personal characteristics of a hedge fund manager
and relationships with brokers are analyzed.
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