Idiosyncratic risk and long-run stock performance following seasoned equity offerings

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Idiosyncratic risk and long-run stock performance
following seasoned equity offerings

• Presented by Ju-Fang Yen
• Co-author with Chia-Wei Huang
• 
  Po-Hsin Ho
• 
  Chih-Yung Lin

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SEO Underperformance (1/2)

• New Issues Puzzle Loughran and Ritter (1995)
  and Spiess and Affleck-Graves (1995) report that
  SEO firms underperform their benchmarks by 40-60
  over the three-to-five years following the
  offering date.

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SEO Underperformance (2/2)

• This puzzle can be explained by
• Free cash flow problems (Lee, 1997)
• Insiders exploiting windows of opportunity
  (Clarke, Dunbar, and Kahle, 2001)
• Earnings management (Teoh, Welch, and Wong,
  1998)
• Small firm (Brav, Geczy, and Gompers, 2000)
• Lower systematic risk exposure (Eckbo, Masulis,
  and Norli, 2000 Carlson, Fisher, and Giammarino,
  2010)
• Rise in stock liquidity (Eckbo and Norli, 2005).

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Corporate Lifecycle

• Lifecycle theory that predicts young firms with
  high market-to-book (M/B) ratios and low
  operating cash flows sell stock to fund
  investment, whereas mature firms with low M/B
  fund investment internally.
• DeAngelo, DeAngelo and Stulz (2010) find that
  55.00 of equity issuers are listed for less than
  five years, and 70.43 are listed for less than
  ten years, implying that
• young firms dominate the SEO market !

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Young Firms

• According to Pastor and Veronesis (2003)
  rational learning model, a young firm has higher
  uncertainty about its future mean profitability,
  resulting in higher cross-sectional idiosyncratic
  return volatility.
• Young firms generally face higher uncertainty of
  mean profitability, which they resolve more
  quickly due to learning and therefore experiences
  a larger reduction in its idiosyncratic return
  volatility over time. .

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Idiosyncratic Risk and Stock Return

• Several studies state that investors find it
  difficult to hold a perfectly diversified
  portfolio as suggested by modern portfolio
  theory. Thus, under-diversified investors should
  require greater returns to compensate for bearing
  idiosyncratic risk (Levy, 1978 Merton, 1987, and
  Malkiel and Xu, 2002).
• Fu (2009) empirically finds a positive relation
  between idiosyncratic risk and expected stock
  returns in the cross section.

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Learning Hypothesis

• The SEO market is almost entirely dominated by
  young firms with high uncertainty, the long-run
  stock underperformance of SEOs can be ascribed to
  the abnormal decline in idiosyncratic return
  volatility over time due to learning.

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Contributions

1. This is the first study to investigate the
   association between learning effect and the
   long-run performance of SEOs.
2. Our results contribute to the linkage between
   idiosyncratic return volatility and explanations
   for the long-run underperformance of SEOs

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Data (1/2)

1. SEO sample is drawn from Securities Data
   Corporations (SDCs) Global New Issue Database
   for common stocks (CRSPs share type code10 or
   11) by completed U.S. issuers that are traded on
   the NYSE, Amex, or NASDAQ markets over the 1983
   to 2007 period.
2. SEOs are restricted to using a firm commitment
   method

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Data (2/2)

1. We exclude samples when SEOs have the following
   conditions (1) offer prices less than 5 (2)
   spin-offs (3) reverse LBOs (4) closed-end
   funds, unit investment trusts, REITs and limited
   partnerships (5) rights and standby issues (6)
   simultaneous or combined offers of several
   classes of securities (i.e., unit offers of
   stocks and warrants) (7) nondomestic and
   simultaneous domestic-international offers (8)
   pure secondary offerings and (9) SEOs lacking
   CRSP data to compute idiosyncratic volatility for
   the year subsequent to the SEO issue date.

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Idiosyncratic Risk (IVOL)

• Following Ang, Hodrick, Xing, and Zhang (2006)
  and Fu (2009), we estimate the idiosyncratic risk
  of a stock as follows. For each firm-month, we
  estimate the following model created by Fama and
  French (1993, 1996)

The idiosyncratic risk is the standard deviation
of the regression residuals multiplied by the
square root of the number of trading days in that
month.
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Post-Issue Abnormal Stock Returns

1. BHAR approach (adjusted for firm size,
   book-to-market ratio, and exchange)
2. Calendar-time portfolio approach (Fama and French
   (1993) and Carhart (1997))

a is the average monthly abnormal return on the
portfolio of SEO firms over the 36-month
post-event period.
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Summary Statistics
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IVOL around SEOs Offering Date
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Median Change in IVOL (1/3)
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Classified by Years Listed
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Median Change in IVOL (2/3)
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Median Change in IVOL (3/3)
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Determinants of IVOL
Dep. Variable
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Three-Year Buy-and-Hold Return () (1/3)
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Three-Year Buy-and-Hold Return () (2/3)
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Three-Year Buy-and-Hold Return () (3/3)
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Calendar-Time Portfolio Approach (1/2)
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Calendar-Time Portfolio Approach (2/2)
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Regressions (Young SEO Firms)

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Discussion-Leverage (1/5)

• Previous studies find evidence of a positive
  relation between leverage and total and
  idiosyncratic volatility of equity return (Black,
  1976 Christie, 1982 and Dennis and Strickland,
  2004).
• Therefore, the immediate reduction in leverage
  resulting from raising equity (hereafter leverage
  effect) could diminish idiosyncratic stock
  volatility, providing an alternative potential
  explanation for the long-run post-issue stock
  underperformance.

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Discussion-Leverage (2/5)
Event Year
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Discussion-Leverage (3/5)
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Discussion-Analyst Forecast (4/5)

• While we conjecture that the post-issue stock
  underperformance is associated with the abnormal
  decline in idiosyncratic stock volatility due to
  learning, it should be necessary and interesting
  to investigate whether and how financial analysts
  improve their accuracy of earnings forecasts via
  learning about the firm-specific information over
  time.
• Mikhail, Walther, and Willis (1997) and Markov
  and Tamayo (2006) document that the analysts
  rationally learn about the earnings process over
  time.

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Discussion-Analyst Forecast (5/5)
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Conclusion

• The long-run stock underperformance of SEOs can
  be explained by steeper declines in idiosyncratic
  return volatility over time due to young firms
  faster learning about their long-term average
  profitability.
• Our results indicate that SEO firms do not truly
  underperform their benchmarks following the
  offering date. Instead, it could imply that
  investors in the SEO market rationally and more
  quickly update their beliefs about future mean
  profitability

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Thank you !Comments are welcome.