Transparency and the Pricing of Market Timing

Xin Chang

Nanyang Technological University

Zhihong Chen

City University of Hong Kong

Gilles Hilary

INSEAD

Research Questions

• Can managers lower the cost of equity by actively timing the market when they issue external capital?

• What is the role played by corporate transparency in this process?

Can Firm Time The Market? • The “market timing theory” relies on the idea that

managers know more about the fundamental value of their firm than outside investors, – Managers detect temporary mispricings.

• Managers can try to take advantage of the mispricing by issuing or buying back capital.

Can Firm Time The Market?

• If new investors take the issuance of capital as a signal that a firm is overvalued, the price should adjust. (e.g., Myers and Majluf, 1984).– If true, managers and current shareholders cannot

take advantage of mispricings.

• If quasi-rational investors buy the new capital at the inflated price, managers can transfer wealth from these new investors to current shareholders.

Can Firms Time The Market?

• There is a positive correlation between good market conditions and equity issuances (e.g., Loughran et al. 1994, Graham and Harvey 2001).

• It is not clear if this reflecting managers’ private information or something else such as time-varying investment opportunities (Schultz 2003, Baker, et al. 2007).

Pricing of Market Timing

• If current investors believe this is true, these issuance gains should be reflected in the firm valuation.

• The price of successful market timers should be higher for a given level of expected earnings.– Equivalently, holding profitability and risk

constant, the discount rate implied by a price and a given stream of expected earnings is lower.

Market Timing Pricing

• H1: Firms that are expected to time the market when they issued or repurchased capital should have a lower expected cost of equity capital.

Are SEOs overvalued on average?

• Firm level (Ritter 2003) and aggregate level (Baker and Wurgler 2000) evidence on abnormal performance after SEOs.

• But, all studies use ex-post returns and complex procedures to address associated econometric problems.

• Ritter (2003) indicates that “the conclusions regarding abnormal performance are hotly debated and sensitive to the methodology employed and the sample used”.

Broader View

• We rely on the aggregate amount of capital issued by firms, rather than focusing on special and rare events such as IPOs or SEOs.

• Takeuchi (2008) reports that – firms making SEOs represent only 6% of firms

with net increases in equity– 18% of firms with net increases in equity of

more than 10% of assets in a given year.

Transparency

• Transparency affects financial policy.– Poor accounting quality is associated with higher

SEO issuance costs (Lee and Masulis (2009)).

– Transparent firms have more flexibility to issue equity (rather than debt), have a greater control over the issuance size and are less influenced by market conditions (Chang et al. (2006, 2009)).

Transparency

• Transparent firms obtain a fair price when they issue equity in periods of low sentiment and capture excess value in periods of high sentiment.

• Opaque firms “break-even” in periods of high sentiment and abstain from issuing equity in periods of low sentiment.

• H2: The effect of past market timing on the expected cost of capital should be stronger for transparent firms than for opaque firms.

Main Specification

• Measure of market timing:

MTCov = Cov(EF,MB) / Assets

where

EF: sum of net debt and equity issues for a given year.

MB: market to book ratio for the year.

tititfti eCMTCovRR ,],0[,1,*,

Estimate Implied Cost of Equity

• Four implied cost of equity models

• All based on dividends discount model but make different assumptions on future earnings growth.

• Use the average of the four estimates to mitigate model-specific measurement errors.

Why not ex post returns?• Market timing ability relies on the existence of quasi-

rational investors and information asymmetry between different classes of investors. – Properties of market equilibrium models in this complex setting are not

well-known.

• Debatable whether the ex post return is an appropriate proxy for a firm’s cost of capital. – May reflect the shocks to a firm’s growth opportunities, expected

growth rates or investors’ risk aversion. – Fama and French (1997) conclude that expected returns estimated by

ex post returns are imprecise because of the uncertainty of factor premiums and factor loading estimates.

• Firms may have a very active financing policy.

Control Variables

• Beta • Size• Book-to-Market• Leverage • Price Momentum • Forecast Errors• Forecast of Long-term Growth• Lagged Industry Risk Premium • Year fixed effects.

Main Specification

• AQ: a measure of accounting quality similar to Francis et al. (2005).

tititititfti eZAQAQxMTCovMTCovRR ,,],1[,],1[,,*,

Data and Sample Selection

• Start from Compustat/CRSP merged file.

• Eliminate utilities and financial firms.

• Require firms to be listed for at least 3 years.

• Require observations to have all four cost of equity estimates and control variables.

• Final sample contains 26,286 firm-year observations from 1981 to 2007.

Descriptive StatisticsVariables N Mean Stdev Q1 Median Q3

R*-Rf 26,286 5.351 3.134 3.362 4.787 6.698

MTCov(1, t) 26,286 0.007 0.114 -0.009 0.003 0.022

AQ 26,286 -0.049 0.034 -0.063 -0.040 -0.026

Beta 26,286 1.161 0.628 0.754 1.084 1.467

LogMV 26,286 6.632 1.659 5.446 6.531 7.674

LogBM 26,286 -0.766 0.704 -1.178 -0.724 -0.299

Leverage 26,286 0.130 0.131 0.016 0.096 0.201

Price Momentum (MMT) 26,286 0.102 0.404 -0.113 0.105 0.323

Forecast error (Ferr) 26,286 -0.017 0.053 -0.019 -0.003 0.003

Long-term earnings growth forecast (Fltg) 26,286 0.163 0.072 0.117 0.150 0.200

Industry risk premium (IndRp) 26,286 5.182 1.448 4.303 5.112 6.030

Is Market Timing a Firm Characteristic?

• For each year from 1970 to 2002 (or 1997), we estimate the following cross-sectional regression

• We try N = 5 and 10.

• β1 is positive and significant at 5% level or below– in 27 (32) of the 33 years at 5% (10%) when N=5

– in 26 (28) of the 28 years at 1% ( 5%) when N=10.

],[,]1,0[,1],[, NttitiNtti eMTCovMTCov

Table 3Dependent variable: R* - Rf

Predicted Signs

OLS Regression

MTCov(1,t) ? -0.293***

(-3.25) Beta + 0.150***

(2.34)

LogMV - -0.315***

(-7.13)

LogBM + 0.657***

(6.59)

Leverage + 3.581***

(11.79)

Price Momentum (MMT) - -1.873***

(-11.98)

Forecast error (Ferr) - -11.493***

(-10.60)

Long-term earnings growth forecast (Fltg) ? 8.009***

(12.46)

Industry risk premium (IndRp) + 0.421*** (8.46)

Year Fixed Effects Yes

Adjusted R2 0.412

N 26,286

Table 4

Predicted Sign

Model 1

MTCov - -0.617*** (-4.97)

AQ×MTCov - -6.040*** (-3.33)

AQ - -5.071*** (-4.23) Beta + 0.098***

(2.71)

LogMV - -0.267***

(-13.44)

LogBM + 0.716***

(14.12)

Leverage + 3.784***

(15.82)

Price Momentum (MMT) - -1.878***

(-35.43)

Forecast error (Ferr) - -10.980***

(-17.73)

Long-term earnings growth forecast (Fltg) + 7.610***

(15.15)

Industry risk premium (IndRp) + 0.411***

(18.94) Year Fixed Effects Yes Adjusted R2 0.419 N 26,286

Table 5

Predicted Sign (I) (II) (III)

MTCov_Sent(1,t) - -0.442***

(-3.63) MTCov_Resid(1,t) - -0.223***

(-3.22) MTCov_Pred(1,t) 0 -0.099

(-1.35) Beta + 0.175*** 0.145** 0.146***

(2.88) (2.22) (3.86)

LogMV - -0.308*** -0.302*** -0.303***

(-7.13) (-6.75) (-15.23)

LogBM + 0.652*** 0.671*** 0.680***

(6.72) (6.60) (13.10)

Leverage + 3.768*** 3.617*** 3.667***

(11.91) (11.91) (14.95)

Price Momentum (MMT) - -1.893*** -1.886*** -1.882***

(-12.04) (-12.00) (-35.04)

Forecast error (Ferr) - -11.477*** -11.425*** -11.439***

(-10.59) (-10.66) (-18.21)

Long-term earnings growth forecast (Fltg) ? 8.117*** 7.942*** 7.859***

(12.27) (11.53) (15.58)

Industry risk premium (IndRp) + 0.414*** 0.422*** 0.419***

(8.50) (8.59) (19.22)

Year Fixed Effects Yes Yes Yes

Adjusted R2 0.413 0.412 0.411 N 26,286 25,935 25,935

Robustness Tests• Estimation of cost of equity

• Estimation of transparency

• Estimation of market timing activity

Table 6 – Panel C

Alternative measure of transparency Coefficient estimates of TRAN*MTCOV

(t-statistic)

TRAN = Innate component of AQ

-7.219*** (-2.21)

TRAN = Discretionary component of AQ

-4.844***

(-2.07)

TRAN = negative absolute value of discretionary revenue

-3.985**

(-1.93)

TRAN = natural logarithm of number of analyst following.

-0.308*** (-3.26)

Table 7 Dependent variable: R* - Rf

Predicted sign

Coefficient Estimate (t-statistic)

Coefficient Estimate

(t-statistic)

MTCov - -1.098*** -0.166 (-4.77) (-1.54) PIN ? -2.557*** (-3.14) MTCov×PIN + 4.722*** (3.94) DedOwn ? -0.290 (-0.55) MTCov*DedOwn - -1.752** (-2.19) Beta 0.171** 0.151** + (2.54) (2.33) LogMV -0.357*** -0.314*** - (-7.41) -(7.26) LogBM 0.789*** 0.880*** + (9.14) (8.25) Leverage 2.496*** 2.433*** + (9.79) (10.68) Price Momentum (MMT) -1.866*** -1.869*** - (-10.59) -(12.00) Forecast error (Ferr) -12.353*** -11.747*** - (-10.15) -(10.89) Long-term earnings growth forecast (Fltg) 7.787*** 7.915*** ? (11.02) (12.27) Industry risk premium (IndRp) 0.387*** 0.424*** + (7.25) (8.52)

Year Fixed Effects Yes Yes

Adjusted R2 0.42 0.41

N 21,092 26,286

Conclusions

• Our results suggest that managers can reduce the cost of equity by timing the market.– Effects are both statistically and economically

significant.– Robust to multiple specifications

• The effects are stronger for transparent firms than for opaque firms.

Thank You