Market uncertainty and earnings guidance

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Market uncertainty and earnings guidance夽 Anna Agapova ∗ , Jeff Madura College of Business, Finance Department, Florida Atlantic University, 777 Glades Rd, Boca Raton, FL 33431, USA

a r t i c l e

i n f o

Article history: Received 29 January 2015 Received in revised form 6 November 2015 Accepted 17 December 2015 Available online xxx Keywords: Market uncertainty VIX Earnings guidance

a b s t r a c t We test a theory about ambiguity surrounding the distribution of fundamental values to determine how market uncertainty affects earnings guidance perception and behavior. We find a more pronounced negative share price response to negative earnings guidance and a lower likelihood that management issues negative guidance under conditions of greater market uncertainty. Yet, we also find that the share price response to positive guidance is not related to the level of market uncertainty, while the likelihood of issuing positive guidance decreases with market uncertainty. The asymmetric effects of market uncertainty on earnings guidance perception and behavior support the ambiguity based pricing theories. © 2015 The Board of Trustees of the University of Illinois. Published by Elsevier B.V. All rights reserved.

JEL classification: G12 G14

1. Introduction A firm issues earnings guidance in an attempt to create more transparency to help investors more properly estimate its market valuation. However, investor interpretation of the increased transparency may depend on the prevailing level of market uncertainty1 . While studies have clearly documented how characteristics of the firm issuing guidance may influence investor perception of earnings guidance and managerial decisions to issue guidance, the studies tend to ignore the potential influence of market uncertainty2 . The scope of the paper is twofold: we examine the effect of market uncertainty on the share price response when the firm management issues positive, negative, or neutral guidance, and analyze the effect of market uncertainty on the likelihood of management guidance releases, accounting for the type of guidance issued. This issue is important because it can explain how investor behavior in response to guidance signals is dependent on the market environment, and how managerial behavior regarding the provision

夽 We wish to thank participants at the 2012 FMA Applied Finance Conference in New York, the 2012 FMA Conference in Atlanta for their valuable suggestions. ∗ Corresponding author. Tel.: +1 561 297 3493; fax: +1 561 297 2956. E-mail address: [email protected] (A. Agapova). 1 For example, see http://www.forbes.com/sites/michaelkay/2014/10/14/theresonly-one-thing-certain-about-market-uncertainty/. 2 Numerous studies such as those by Libby and Tan (1999) and Sinha and Gadarowski (2010) document that earnings guidance elicits a strong share price response.

of guidance is dependent on the market environment. We apply ambiguity models of Hansen and Sargent (2010), and Epstein and Schneider (2008) to hypothesize how market uncertainty could affect earnings guidance perception and behavior. Based on the models, if market uncertainty clouds the interpretation of earnings guidance, it can cause a more pronounced negative impact on the fundamental value of the firm, even after controlling for the firm-specific characteristics that cause uncertainty about the firm. Specifically, investors may interpret a given level of firmspecific negative news more negatively when market uncertainty is relatively high, as they recognize that adverse effects of negative information may be more pronounced if market conditions are more uncertain. Yet, they will not necessarily interpret a given level of firm-specific news more positively when market uncertainty is relatively high, because they assign more emphasis to the potential downside than upside. Consequently, the adverse market reaction to negative earnings guidance should be more pronounced when the degree of market uncertainty is relatively high. We test our hypothesis about how market uncertainty affects earnings guidance perception and behavior using a large sample of U.S. companies that issue guidance regarding future earnings during 1996–2011. We find that higher relative levels of market uncertainty result in a more pronounced negative share price response to negative earnings guidance releases. These results are consistent with ambiguity models. We also find that market uncertainty does not affect the market response to positive guidance in the manner that it affects the market response to negative guidance, which supports Epstein and Schneider’s (2008) theory about asymmetry of investor’s response to negative versus positive news.

http://dx.doi.org/10.1016/j.qref.2015.12.001 1062-9769/© 2015 The Board of Trustees of the University of Illinois. Published by Elsevier B.V. All rights reserved.

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Next, we investigate whether market uncertainty is related to the managerial decision to issue guidance. Firms may be more willing to issue negative guidance under more uncertain market conditions, so that they can avoid potential litigation costs3 and maintain their credibility. Yet, to the extent that firms expect the adverse share price response to negative guidance would be more pronounced during periods of high market uncertainty, they may only issue negative guidance when they possess information that must be released in order to avoid litigation. Results of our analysis show that the likelihood of issuing negative guidance (while controlling for other factors) is significantly lower during periods of increased market uncertainty. We also find that the relationship between some firm-specific characteristics and the likelihood of issuing positive and negative guidance differs in the high market uncertainty environment versus the low market uncertainty environment. Thus, market uncertainty is not only related to the firm’s likelihood of issuing guidance, but can also influence other characteristics that are associated with the firm’s decision to issue guidance. The rest of the paper is organized as follows. Section 2 provides a literature review, and Section 3 presents our hypotheses. Section 4 discusses the data and Section 5 reports empirical results. Section 6 concludes the paper. 2. Review of literature 2.1. Share price response to earnings guidance Prior studies document that new information about asset fundamentals has a significant impact on asset prices. Studies have examined various types of company-specific information releases. The most widely examined type is the market reaction to periodic earnings announcements4 . Another company-specific event that can impact asset valuation is voluntary managerial earnings guidance, which typically occurs in periodic intervals, but the timing is not certain. Studies by Ajinkya and Gift (1984), Libby and Tan (1999), Anilowski, Feng, and Skinner (2007), Sinha and Gadarowski (2010), and Agapova and Madura (2011) show that guidance has a strong effect on the company’s value. Furthermore, some studies have determined that the impact of earnings guidance on a firm’s value can be conditioned on a firm’s characteristics, or on the properties of the guidance. In particular, Das, Kim, and Patro (2012) and Ng, Tuna, and Verdi (2013) find stronger price reaction to negative earnings guidance than to positive one. However, no study to our knowledge attempts to determine whether the share price response to guidance announcements is conditioned on market uncertainty. We explain below why the effect of uncertainty on outcome of guidance releases is an important empirical question. Some studies have demonstrated that external market conditions can influence the means by which share prices respond to new information. Perez-Quiros and Timmermann (2000) suggest that small firms are more exposed to bad news when there is a high degree of market uncertainty, because their valuations are more sensitive when credit is restricted. They suggest that the risk premium of small firms may increase during a weak economy. Conrad, Cornell, and Landsman (2002) suggest that stock prices are more responsive to negative earnings surprises in good periods, consistent with David (1997) and Veronesi (1999) models. Williams (2015) proposes that an increase in market uncertainty creates a more pronounced response to negative versus positive

3 See, for example, Kasznik and Lev (1995), Skinner (1994, 1997), and Baginski, Hassell, and Kimbrough (2002). 4 See Kothari (2001) for a comprehensive review of capital market research in the areas of tests of capital markets inefficiencies surrounding earnings announcements.

earnings announcements, which is consistent with the Epstein and Schneider (2008) model. Kurov (2010) suggests that the stock price response to a particular monetary policy may be dependent on prevailing investor sentiment and market conditions. However, these studies do not offer direct inferences on how market uncertainty relates the share price response to earnings guidance because the characteristics of guidance are unique, even in comparison to an earnings release. While earnings releases are mandatory and the timing of the announcement is usually known in advance, firms have discretion whether to issue guidance, and when to issue guidance. Furthermore, the mean impact of guidance prior to an earnings release is much stronger than the impact of a surprise due to an earnings release. Agapova, Madura, and Mailibayeva (2012) show that absolute value of market response three days around guidance release is about 30% larger than that of impending earnings releases after 2001 and is about 100% larger before 2001. Therefore, positive or negative guidance reduces the firm’s asymmetric information to a greater degree than an earnings release. Hansen and Sargent’s (2010) and Epstein and Schneider’s (2008) models predict that when market uncertainty increases, investors will assign higher probability to more negative possible outcomes when interpreting information. Under conditions of high uncertainty, a signal relayed by managerial earnings guidance, normally viewed as high quality, could be distorted, which prompts investors to assign a relatively low value to an asset. Thus, market participants should react more strongly to negative guidance than to positive guidance. 2.2. Decision to issue earnings guidance There is a large body of literature that examines various reasons why management provides guidance. Common explanations for providing earnings guidance include reducing litigation risks (Skinner, 1994, 1997; Kasznik, 1999), building a reputation for credible and transparent reporting (Graham, Harvey, & Rajgopal, 2005; Hutton & Stocken, 2009), reducing information asymmetry (Diamond & Verrecchia, 1991; Verrecchia, 2001), and aligning analysts’ forecasts toward beatable earnings targets (Richardson, Teoh, & Wysocki, 2004; Cotter, Tuna, & Wysocki, 2006)5 . Factors examined in the literature that influence guidance decisions include firm-specific characteristics and relative or absolute performance of a firm. For example, Kross, Lewellen, and Ro (1994) find that firm-specific characteristics such as firm size, leverage, strength of earnings, and stability of earnings increase the likelihood of issuing guidance. Feng and Koch (2010) find that management is less likely to provide guidance when their past guidance was too optimistic. Houston, Lev, and Tucker (2010) find that firms cease guidance due to poor performance. Surveys of managers about their ongoing communication with investors (e.g., Graham et al., 2005) indicate that managers are often concerned about share price volatility. Managers also mention earnings guidance effectiveness in limiting price volatility (Graham et al., 2005; Johnson, 2009; National Investor Relations Institute, 2005). Rogers, Skinner, and Van Buskirk (2009) examine implied volatility of a firm and find that earnings guidance increases short-term volatility. Though, Billings, Jennings and Lev (2015) find an opposite results and document greater postannouncement decline in volatility for guidance firms. While no study to our knowledge, explicitly examines whether managers’ decision to issue guidance is related to market uncertainty, it is an important empirical question.

5 National Investor Relations Institute study in 2006 finds that 62% of 654 managers responded that they provide guidance to decrease the volatility of the stock price. Thus, an objective for managers is to minimize earnings surprises.

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On one hand, due to possible negative effect of high market uncertainty on market response to earnings guidance, firms may prefer to defer the announcement until the formal earnings announcement. On the other hand, earnings guidance under high market uncertainty may also reduce litigation risk (Skinner, 1994; Field, Lowry, and Shu, 2005), sustain managerial reputation, and reduce information asymmetry (Lang, Lins, and Maffett, 2012). 3. Hypotheses 3.1. Relationship between market uncertainty and the share price response to guidance Several theoretical models propose how to value assets in a rational and irrational setting of investor behavior. Most equilibrium asset pricing models assume that all relevant information is tangible, whereby prices depend only on past and present consumption or dividends6 . However, some of these models try to account for uncertainty surrounding the valuation process. In particular, Hansen and Sargent (2010) suggest that model uncertainty is priced. Their model incorporates uncertainty about a state realization, i.e. information quality, and about valuation model uncertainty. According to the model, the consumer deals with uncertainty by skewing probabilities pessimistically. Consequently, an increase in uncertainty causes investors to devalue assets. Epstein and Schneider (2008) offer an alternative explanation based on learning in the presence of model ambiguity. They directly model the role of uncertain information quality in financial markets and show that when ambiguity-averse investors process news of uncertain quality, they act as if they take a worst-case assessment of quality. One of the model’s implications is that investors require compensation for low future information quality. Another result of the model is that investors react more strongly to bad news than to good news. Based on predictions of Hansen and Sargent’s (2010) and Epstein and Schneider’s (2008) models, we expect that with increased market uncertainty, investors will use the worst case scenario probabilities in interpreting information arriving to the market. Thus, we expect that a high level of market uncertainty results in a devaluation of assets for all types of news. Even a signal relayed by managerial earnings guidance that might normally be viewed as high quality could be distorted under conditions of high uncertainty, which prompts investors to assign a lower value to an asset7 . Thus, market participants should react more strongly to bad news than to good news. Consistent with both models, we expect that effect of market uncertainty on the share price response to earnings guidance is asymmetric for negative versus positive news. Since the decision to issue guidance is under the control of the firm, it is possible that market uncertainty could influence that decision. In particular, if firms expect that the adverse share price response to negative guidance is exacerbated by a high level of market uncertainty (in line with our first hypothesis), they may be less willing to issue negative guidance when market uncertainty is high. Thus, they might only issue negative guidance when they possess information that they must reveal in order to avoid litigation. Under these conditions, the adverse share price

6 Many valuation models use earnings as key inputs in determining the price of the stock. Residual income valuation models (Feltham and Ohlson, 1995, Ohlson, 1995) use abnormal earnings; discounted cash flow valuation models use earnings as proxies for cash flows. 7 To proxy for market uncertainty we use CBOE S&P 500 Volatility Index (VIX). Drechsler (2010) provides evidence that VIX contains an important uncertaintyrelated component.

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response to negative guidance may be more pronounced. Such an indirect impact differs from our original explanation of why market uncertainty could influence the share price response to earnings guidance, but leads to the same hypothesis. H1A. Relatively high levels of market uncertainty negatively affect the share price response to managerial earnings guidance. H1B. Under high levels of market uncertainty, the investor response to negative earnings guidance is more pronounced than the investor response to positive earnings guidance.

3.2. Market uncertainty and the propensity to issue guidance As explained above, the decision by a firm’s management to issue guidance could be influenced by the prevailing level of market uncertainty. Studies by Houston et al. (2010) and Chen, Matsumoto, and Rajgopal (2011) assess firms that stopped issuing guidance and find that their decision is triggered by bad performance. According to Libby and Rennekamp (2012), the decision by firms to issue guidance is influenced by their ability to forecast earnings, as they are less comfortable issuing guidance when forecast accuracy declines. We examine whether the propensity to issue guidance is related to prevailing market uncertainty, for which the firm has no control. Francis, Philbrick, and Schipper (1994) find that firms subject to litigation risk do not disclose negative earnings news until formal earnings announcements. To the extent that high market uncertainty may exacerbate the signal relayed by negative information, firms may prefer to defer the announcement until the formal earnings announcement. Furthermore, to the extent that firms are less willing to issue guidance when their forecasts are less accurate (Libby and Rennekamp, 2012), increased market uncertainty might discourage firms from issuing guidance because it could hamper their ability to forecast earnings accurately. Even if litigation risk is not a concern, firms may decide to defer negative announcements during periods of high uncertainty, with the hope that conditions will improve prior to formal earnings announcements. However, there are counter arguments that deserve consideration. While issuing negative guidance during periods of high level of market uncertainty might elicit a pronounced negative share price response (as we explain above), it may also reduce litigation risk, sustain managerial reputation, and reduce information asymmetry. Skinner (1994) argues that voluntary disclosure of negative information can reduce the likelihood of litigation risk and the costs associated with litigation. Field et al. (2005) offer evidence that voluntary disclosure of negative information can deter litigation. Furthermore, conditions of high market uncertainty may increase the desire of firms to be more transparent. While they cannot control market uncertainty, they have some control over their level of asymmetric information. A cross-country study by Lang, Lins, and Maffett (2012) find that corporate transparency is most beneficial to a firm during periods of high volatility, when the information environment is more uncertain. Earnings guidance is a means by which a firm can demonstrate its credibility by quickly disclosing information under conditions of high market uncertainty. This preference may be especially strong when they have negative information to disclose during periods of high market uncertainty, so that they can maintain credibility in case investors become more suspicious about financial reporting during periods of high market uncertainty. H2A. Market uncertainty increases the propensity of earnings guidance issues. H2B. Market uncertainty increases the propensity of negative versus positive earnings guidance issues.

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VIX, Jan 1993 - Dec 2011, daily 90 80 70 60 50 40 30 20 10 0 Jan-93

Jan-95

Jan-97 VIX

Jan-99

Jan-01 VIX average

Jan-03

Jan-05

Jan-07

Jan-09

Jan-11

VIX 3 year moving average

Fig. 1. Plot of VIX. The figure shows the VIX index plotted at a daily frequency. The sample period is January 1993 to December 2011.

4. VIX as a measure of uncertainty The VIX index, extracted from options on the stock market index traded on the Chicago Board Options Exchange, has served as a convenient measure of implied stock market volatility (Whaley, 2000). In a review of implied volatility indices, Siriopoulos and Fassas (2009) find that implied volatility indices (including VIX) contain relevant information about future volatility that is above and beyond information contained in past volatility. Drechsler and Yaron (2011) demonstrate that VIX captures market attitudes about stock market uncertainty. Several studies have used VIX as a measure of uncertainty surrounding the stock market. Bloom (2009) uses the VIX index to determine how productivity is associated with stock market volatility. Bekaert, Hoerova, and LoDuca (2012) assess how the Federal Reserve’s monetary policy actions are influenced by conditions of high market uncertainty as measured by VIX. Baker, Bloom, and Davis (2013) use VIX to determine how stock market uncertainty is associated with economic policy uncertainty, while Goodell and Vahamaa (2013) use VIX to determine how stock market uncertainty is associated with political uncertainty. We measure market uncertainty by the VIX level and changes in the VIX level so that we can determine whether the share price response to earnings guidance is associated with stock market uncertainty. We use the CBOE S&P 500 Volatility Index (VIX) as a proxy for market uncertainty. VIX data come from CBOE (Chicago Board Options Exchange) indexes as provided by WRDS. 4.1. Behavior of implied volatility over time Since implied volatility plays a major role in our study, we review its path over time before assessing how it is associated with the share price response to guidance. Fig. 1 shows movements in VIX from January 1993 through December 2011. Notice the wide variation in VIX over time. In the 1993–1997 period, it was relatively low. In 1998, its level doubled, but then declined substantially before it more than doubled in 1999. It remained relatively high in the 2000–2003 period relative to its long-term average. It declined in the 2004–2007 period, while rising dramatically in 2008. It remained relatively high compared to its long-term average in the 2008–2011 period. These generalizations about implied volatility could also be made about economic conditions. The VIX levels tend to be higher

in periods when GDP growth is lower, and when the stock market performance is relatively weak. While the correlation between GDP growth and stock market performance is 0.3202, the correlation between SP500 and VIX is −0.2994, and between GDP growth and VIX is −0.4728 based on quarterly data. Fig. 2 illustrates the time series pattern of VIX, GDP growth, stock market performance, and business cycles8 . The inverse relationship between VIX and either GDP growth or stock market performance is especially evident when VIX reached temporary peaks, such as in the 2nd quarter of 1998, the 4th quarter of 2002, the 4th quarter of 2008, and the 2nd quarter of 2010. However, the relationship between VIX and GDP growth or stock market performance is not perfect, and varies in other periods. Therefore, we believe market uncertainty is not fully captured by variables measuring GDP growth or stock market performance, and offers additional information beyond these economic variables. We use measures of VIX as proxies of market uncertainty, while controlling for stock market performance.

5. Data and sample description We obtain U. S. company issued (managerial) guidance from Thomson Reuters I/B/E/S Guidance dataset, previously called First Call database from 1996 through 2011. The database provides historical data in textual format from I/B/E/S preannouncement—1994–Dec 2002 (EPS, SAL for US), in numeric fielded format from I/B/E/S preannouncement—Dec 2002–Oct 2007 (EPS, FFO, SAL for US), and in numeric fielded format from I/B/E/S preannouncement and Street Events collection starting from Oct 2007 (14 measures, global). We also collect quarterly earnings per share (EPS) analyst forecasts for the period Jan 1996–Dec 20119 . Following Anilowski, Feng, and Skinner (2007), we retain the last forecast for firm/periods with multiple forecasts. We use company issued guidance (CIG) only for the most recent quarterly forecasts and omit annual forecasts and earlier quarterly forecasts

8 GDP data come from National bureau of economic research website http://www.nber.org/cycles/cyclesmain.html. Business cycles period indicators come from US department of commerce, Bureau of Economic Analysis website http://www.bea.gov/iTable/iTable.cfm?ReqID=9&step=1. 9 Even though the database has starting period of 1994, it has scattered data prior to 1996.

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VIX, SP500 return and GDP growth, Jan 1993 - Dec 2011, quarter SP500, 70

VIX

GDP

15

VIX

201104

201002

201101

200903

200804

200801

200603

200702

200501

200504

200402

200204

SP500

200303

-20 200102

0 200201

-15

200003

10

199901

-10

199904

20

199802

-5

199703

30

199604

0

199502

40

199601

5

199403

50

199304

10

199301

60

GDP growth

Fig. 2. Plots of VIX and S&P 500 Return, GDP Growth, Business Cycles. This figure shows VIX index values, S&P 500 return (%) and GDP growth (%) at a quarterly frequency, also highlighting the peaks (solid vertical lines) and trough (dashed vertical lines) of a business cycle. The sample period is January 1993 to December 2011.

in multiple issues for the same quarter10 . To examine differences in market response to types of news, we divide forecasts into those that convey downward, upward, neutral and undefined guidance. This practice is common in the literature; see for example Anilowski, Feng, and Skinner (2007), and Hutton and Stocken (2009) among others11 . We use Thomson Reuters I/B/E/S Guidance dataset guidelines to determine a type of guidance news12 . We obtain return data from the Center for Research in Securities Prices (CRSP) daily stocks, company characteristics from Compustat North America Fundamentals quarterly set, average financial analyst forecasts from I/B/E/S database, and institutional holdings from Thomson Reuters Institutional holdings 13-f filings database. After merging all data that are required for our analysis we have 41,279 firm/quarter total guidance observations, and segment them by type of guidance as shown in Table 1. Our sample consists of 5750 observations (13.93% of the total sample) representing positive guidance, 15,459 (37.45%) negative guidance, 16,616 (40.25%) neutral guidance, and 3454 (8.37%) undefined guidance for the whole period of 1996–2011. This result is generally consistent with other studies on guidance, such as Anilowski, Feng, and Skinner (2007) and Agapova and Madura (2011). Table 1 also shows the proportion of positive, negative, neutral, and undefined guidance during periods of low versus high market uncertainty, measured whether average VIX level 5 days prior to guidance release was below or above average daily VIX over 1996–2011 period, respectively. Notice that the distribution of

10 Anilowski et al. also find that 86% of firm/quarters with quarterly forecasts are cases where the firm issues only one forecast for the quarter while 12% of firm/quarters have two forecasts over 1993–2004 sample period. Other studies also use the same methodology of retaining the last forecast for firm/periods with multiple forecasts; see, for example, Lin and Yang (2006) and Chaney, Hogan, Chris, and Jeter (1999). 11 Sinha and Gadarowski (2010) examine CARs around management issued guidance for the five news portfolios (very bad, moderately bad, negligible, moderately good, and very good news). 12 Using their own algorithm based on whether announced guidance range or point estimate is above, below or equal to analysts’ mean forecast for the date, Thomson Reuters assigns four codes: 1—Earnings Shortfall (The company is not expected to meet earnings for the period indicated.), 2—Beat Consensus (The company is expected to beat earnings for the period indicated.), 3—Match Consensus (The company is expected to meet earnings for the period indicated.), and 6—Management Guidance (The company has provided guidance but not specified whether they will meet, bear or miss the street.) Source is I/B/E/S Guidance User Guide July 2009.

guidance reflecting positive, negative, neutral or undefined news is dependent on the level of market uncertainty. When market uncertainty is low, the proportion of guidance observations reflecting negative news is relatively low, while the proportion of guidance observations reflecting positive news is relatively high. Conversely, when market uncertainty is high, the proportion of guidance observations reflecting negative news is relatively high, while the proportion of guidance observations reflecting positive news is relatively low. Table 2 shows the frequency distribution of guidance. For the subsamples of positive, negative, and neutral guidance, the propensity to guide is significantly higher when market uncertainty is low. This result offers preliminary support to the hypothesis that firms may be more proactive in releasing information when market uncertainty is low. 6. Empirical analysis 6.1. Relationship between market uncertainty and share price response to guidance While market uncertainty may influence the proportion of positive guidance versus negative guidance observations (as shown in Table 1), we are interested in whether it is related to the share price response to a particular type of guidance. We perform a univariate analysis in which we separate guidance announcements by type, and also according to whether they occur during relatively low versus high levels of market uncertainty, measured by VIX being below or above its mean value over the sample period. We report the cumulative abnormal return (CAR) over the three-day period (−1, +1) surrounding the guidance in Table 3. Notice that the CAR in response to all types of guidance is −2.30% on average. The CAR in response to guidance during low market uncertainty is −1.60%, while the mean CAR in response to guidance during high market uncertainty is −3.04%, and the difference is significant. For the subsample of positive guidance observations, the mean CAR is higher when market uncertainty is higher (6.23% versus 5.43%), and the difference is significant. For the subsample of negative guidance observations, the mean CAR is −7.00% when market uncertainty is low, versus −9.16% when market uncertainty is high, and the difference is significant. For the subsample of neutral guidance observations, the mean CAR is

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Table 1 Descriptive statistics of earnings guidance sample by type of news. This table presents the sample descriptive statistics of guidance distribution by type of news released: positive, negative, neutral or undefined company guidance. Low (high) VIX indicates market conditions when average level of VIX 5 days prior to guidance is lower (higher) than the average VIX during 1996–2011 period. The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively. Whole period N

Mean (%)

Positive Negative Neutral Undefined

5750 15,459 16,616 3454

Total

41,279

13.93 37.45 40.25 8.37

Low VIX Std dev (%) 34.63 48.40 49.04 27.64

N

Mean (%) 3257 7674 9264 1015

100

15.36 36.18 43.68 4.79

21,210

High VIX Std dev (%) 36.05 48.05 49.60 21.32

N

Mean (%) 2493 7785 7352 2439

100

12.42 38.79 36.63 12.15

20,069

High–low (%) Std dev (%) 32.98 48.73 48.18 32.62

−2.93*** 2.61*** −7.04*** 7.36***

100

Table 2 Frequency distribution of guidance issues. This table reports frequency distribution of decision to issue guidance and types of guidance by type of news released: positive, negative, neutral and undefined over whole period and in low and high VIX environment by firms that are classified as issuers over 1996–2011 period. Low (High) VIX indicates market conditions when average level of VIX 60 days prior to earnings releases is lower (higher) than the average VIX during 1996–2011 period. The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively. Low VIX Frequency Do not guide Guide Total Do not guide Positive guide Negative guide Neutral guide Undefined Total

160,831 41,768 202,599 160,831 5817 15,675 16,811 3465 202,599

High VIX

High–low

%

Frequency

%

Frequency

%

79.38 20.62

73,393 22,788 96,181 73,393 3337 8294 9808 1349

76.31 23.69

87,438 18,980 106,418 87,438 2480 7381 7003 2116

82.16 17.84

5.85***

82.16 2.33 6.94 6.58 1.99

1.86*** −0.79*** −0.12*** −2.2*** 1.24***

79.38 2.87 7.74 8.30 1.71

76.31 3.47 8.62 10.2 1.40

%

Table 3 Univariate analysis of market response to guidance. This table presents a market response to earnings guidance measured by average cumulative abnormal return (CAR) three days (−1, +1) around company guidance release (%) for whole sample and by type of news released: positive, negative, neutral and undefined. Low (High) VIX indicates market conditions when average level of VIX 5 days prior to guidance is lower (higher) than the average VIX during 1996–2011 period. The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively. Whole period

Low VIX

High VIX

High–low (%)

CAR(−1, +1)

Mean (%)

Std dev (%)

Mean (%)

Std dev (%)

Mean (%)

Std dev (%)

All Positive Negative Neutral Undefined

−2.30 5.78 −8.08 0.54 −3.49

13.22 10.07 13.80 9.70 17.81

−1.60 5.43 −7.00 0.51 −2.55

10.97 8.98 11.66 8.22 13.84

−3.04 6.23 −9.16 0.58 −3.89

15.21 11.31 15.55 11.29 19.21

lower when market uncertainty is lower, but the difference is not significant. For the sample of undefined guidance observations, the mean CAR is negative for high and low levels of market uncertainty but lower (more pronounced negative) when market uncertainty is higher. Overall, the share price response to guidance appears to be more pronounced in periods of high market uncertainty. However, since this analysis does not include other potential confounding effects, the conclusion at this point is incomplete. To account for possible confounding effects, we continue our analysis of the share price response to guidance under different environments of market uncertainty while controlling for firm and guidance characteristics. Our main explanatory variables are measures of market uncertainty. Since market uncertainty can be defined in various ways, we consider three different measures of market uncertainty. First, we use the average VIX value over the 5 days prior to company guidance (VIX5). Second, we consider a change in the level of VIX 2 days before guidance, relative to the mean level of VIX over the 30 days before guidance (VIX). We consider these proxies as substitutes, and therefore only employ one of these proxies at a time within any multivariate model. Third, we consider a general long-term measure of VIX, which is set equal to 1 when average VIX 5 days prior to guidance is above the mean level over the entire sample period

−1.44*** 0.80*** −2.16*** 0.07 −1.34**

(1996–2011), and 0 when it is below the mean level (VIXhigh). Since this proxy is quite different from the other two measures of market uncertainty, we include it along with either of the other two measures within the multivariate analysis. In addition to the proxies for market uncertainty, we include several control variables. We control for effect of Regulation of Fair Disclosure with a dummy variable RFD, which is set to 1 for guidance announcements after October 23, 200013 , and for market performance with the return on the S&P500 on the day in which guidance is announced (drSP500). We also control for the following firm and industry characteristics used in other studies to explain the share price response to guidance: proportion of firm ownership by managers (Man); analyst coverage measured as log (1 + number of analysts that follow the firm) (Analyst); proportion of firm ownership by institutional investors (Insthold); change of institutional ownership in the firm in quarter t (Insthold); log of the market capitalization of the

13 Prior studies (e.g., Wang, 2007, Sinha and Gadarowski, 2010, Agapova and Madura, 2011, Agapova, Madura, and Mailibayeva, 2012) show Reg. FD had an impact on market reaction to guidance releases and managerial decisions to issue guidance.

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firm (Size); trading volume of shares of the firm measured as log of average per day trading volume of shares in quarter t divided by number of shares outstanding (Vol); systematic risk of the firm measured as beta from the market model over the estimation period of (−255, −46) days prior to guidance announcement (Beta); unsystematic risk of the firm measured as a standard deviation of the error term from the market model over the estimation period prior to guidance announcement (ResStd); dummy variable set equal to 1 when the firm is classified within the technology industry and zero otherwise (Tech); duration in days from the previous quarter end to guidance date (Duration); precision of company issued guidance equal 3 if a point estimate, 2 if a range estimate, 1 if an open interval, and 0 if qualitative guidance estimate (Precision); and dispersion in the industry price-to-book ratio, measured as standard deviation of ratios among firms within the corresponding industry of the guiding firm (Dispersion). To test our main hypothesis regarding the effects of market uncertainty on share price response to guidance, we employ the following regression model with year fixed effects to subsamples of guidance classified as positive, negative, or neutral news: CARi,t

7

versus 0.55 in the high market uncertainty environment, and the difference in means between the two environments is significant. Many characteristics of the firm issuing guidance have a significantly different mean when market uncertainty is low than when market uncertainty is high. Thus, to the extent that these characteristics influence the share price response to guidance, market uncertainty could have an indirect effect on the share price response to guidance if it is related to these characteristics. Management ownership (Man) is marginally significantly higher for firms issuing guidance when market uncertainty is lower. Mean analyst coverage (Analyst) is significantly lower when market uncertainty is higher, which may imply that some analysts are less willing to take a position under such conditions. The proportion of institutional holdings (Insthold) is significantly lower when market uncertainty is higher. The mean size (Size) and the mean trading volume (Vol) of the issuing firm are sig-

= ˛ + ˇ1 VIXi,t + ˇ2 VIXhighi,t + ˇ3 RFDi,t + ˇ4 drSP500i,t + ˇ5 Mani,t + ˇ6 Analysti,t + ˇ7 Instholdi,t + ˇ8 Instholdi,t + ˇ9 Sizei,t + ˇ10 Voli,t + ˇ11 Betai,t + ˇ12 ResStdi,t +

(1)

ˇ13 Techi,t + ˇ14 Durationi,t + ˇ15 Precisioni,t + ˇ16 Dispersioni,t + εi,t where the dependent variable is market response to guidance release measured by the signed cumulative abnormal return calculated over the three days around company issued guidance, CAR(−1, +1) for firm i in quarter t. For a subsample of guidance-firm observations that issue guidance as point or range estimate we include an additional explanatory variable, guidance surprise (Surprise), measured as the difference between the management earnings forecast per share (or midpoint for the range forecast) and the prevailing median analyst forecast, scaled by prior quarter stock price14 . Before reporting results of the multivariate analysis, we provide descriptive statistics for the VIX5, main independent variable implemented, as well as the other independent variables in Table 4. Panel A reports statistics for entire sample. The first three columns show the number of observations, mean and standard deviation for all characteristics based on the entire sample of earnings guidance observations. The next three columns provide similar statistics for the subsample of guidance observations during low market uncertainty (low VIX) periods, while the following three columns focus on the subsample of guidance observations during high market uncertainty (high VIX) periods15 . The final two columns show the conclusions from a test for a difference in the means of each characteristic for corresponding guidance during low market uncertainty versus high market uncertainty. The mean VIX5 level for guidance observations classified within the low market uncertainty periods is 15.70, while the mean VIX5 level for guidance observations classified within the high market uncertainty periods is 28.19. Thus, the mean VIX5 level for guidance observations during high market uncertainty is almost double that of the mean VIX5 level for guidance observations during low market uncertainty. The mean level of VIX in the low market uncertainty environment is −0.24,

14 We break down the forecasts by forecast type (point estimate, range estimate, open interval, and qualitative guidance estimate), as is common in the literature (Anilowski, Feng, and Skinner, 2007, Hutton et al., 2003; Miller, 2002). The subsample containing earnings forecasts with point or range estimate represents 67.34% of whole sample. 15 Periods of low and high VIX are measured whether average VIX level 5 days prior to earnings guidance was below or above average daily VIX over 1996–2011 period, respectively.

nificantly larger during periods of low market uncertainty. The proportion of tech firms relative to all firms that issue guidance (Tech) is significantly higher when market uncertainty is low. The duration of days from the previous quarter to the guidance date is significantly shorter while the mean precision level is higher for guidance observations occurring when market uncertainty is low. The dispersion in the industry priceto-book ratio is significantly higher when market uncertainty is high. Table 4 Panels B discloses the relationship between market uncertainty and these characteristics for subsamples classified by type of guidance (positive, negative, or neutral). This allows us to reassess the relationship between market uncertainty and these characteristics while directly controlling for the type of guidance. For characteristics such as Analyst, Insthold, Insthold, Size, and, Precision, the comparison of means between periods of high versus low market uncertainty yields the same results as described earlier. However, some characteristics are different depending on type of guidance . For example, guidance surprise (Surprise) is significantly more negative in subsample of negative guidance when market uncertainty is high, while insignificantly different from zero for the other subsamples. The comparisons up to this point suggest that many firm-specific characteristics are conditioned on the level of market uncertainty. Thus, by affecting these characteristics, market uncertainty may indirectly affect the valuation effects due to guidance. Furthermore, market uncertainty may directly affect the valuation effects from guidance, above and beyond the effects of the firm-specific characteristics. Table 5 presents results of multivariate cross-sectional analysis. Panel A of Table 5 shows results of the model without the guidance surprise variable (Surprise), while Panel B reports results of the model that includes observations with Surprise variable. We first apply the model including VIX5 to each of the guidance news type subsamples (see Columns 1 through 3), and then we repeat the analysis after replacing VIX5 with VIX (see Columns 4 through 6), while also controlling for the level of VIX relative to historical average (VIXhigh). The results in the first three columns show that the coefficient of the VIX5 variable is not

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Table 4 Characteristics of earnings guidance sample. This table presents descriptive statistics of the following variables for the whole sample (Panel A) and by the type of guidance (positive, negative, and neutral) (Panel B): average VIX value over 5 days prior to company guidance release (VIX5), change in level of VIX 2 days before relative to 30 days before guidance release (VIX), a dummy variable representing whether the guidance occurred after Regulation FD (RFD), daily return of S&P500 on guidance announcement day (drSP500, %), guidance surprise measured as the difference between the forecast EPS (or midpoint of the range forecast) and the prevailing median analyst forecast, scaled by prior quarter stock price (Surprise, %), proportion of firm ownership by managers (Man, %), analyst coverage measured as log(1+ number of analysts following the firm) (Analyst), proportion of firm ownership by institutional investors (Insthold, %), change in proportion of institutional ownership in the report quarter (Insthold, %), log of the market capitalization of the firm (Size), log of average trading volume of shares in the report quarter divided by number of shares outstanding (Vol), firm systematic risk (Beta), firm unsystematic risk (ResStd), percentage of firms that are in a tech industry (Tech), duration in days from the previous quarter end to guidance date (Duration), precision of company issued guidance (Precision), and dispersion in industry price-to-book ratio (Dispersion) for the January 1996–December 2011 period. The statistics is also provided separately for periods of low and high VIX, measured whether average VIX 5 days prior to guidance release was below or above average daily VIX over 1996–2011 period, respectively. High–low columns report difference in means and statistical significance of the difference. The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively. Panel A

Whole period N

VIX5 VIX RFD drSP500 Surprise Man Analyst Insthold Insthold Size Vol Beta ResStd Tech Duration Precision Dispersion Panel B

41,279 41,279 41,279 41,279 23,106 36,132 41,279 36,132 36,132 36,124 36,123 41,279 41,279 41,279 40,976 41,279 36,416

Low VIX

Mean

Std dev

21.77 0.15 77.22 0.013 −0.03 2.17 1.89 51.73 −1.14 6.77 8.48 1.09 3.05 35.21 54.87 1.97 1.42

8.79 3.38 41.94 1.28 16.08 9.52 0.90 37.01 19.01 1.79 0.88 0.62 1.71 47.76 57.05 0.74 0.83

21,210 21,210 21,210 21,210 15,303 18,342 21,210 18,342 18,342 18,337 18,337 21,210 21,210 21,210 21,000 21,210 18,486

Mean

Std dev

15.70 −0.24 85.32 0.003 −0.14 2.26 1.99 56.64 −5.17 6.97 8.52 1.17 2.59 37.04 52.12 2.06 1.38

3.04 1.61 35.39 0.79 1.70 12.02 0.83 36.80 25.35 1.68 0.81 0.60 1.42 48.29 53.83 0.57 0.63

Positive

N 20,069 20,069 20,069 20,069 7,803 17,790 20,069 17,790 17,790 17,787 17,786 20,069 20,069 20,069 19,976 20,069 17,930

High VIX–low VIX

Mean

Std dev

28.19 0.55 68.66 0.025 0.18 2.08 1.78 46.68 3.02 6.56 8.44 0.99 3.54 33.28 57.77 1.88 1.46

8.30 4.52 46.39 1.64 27.57 5.93 0.95 36.54 6.14 1.88 0.94 0.63 1.85 47.12 60.11 0.87 0.99

12.49*** 0.79*** −16.66*** 0.022* 0.32 −0.18* −0.21*** −9.96*** 8.19*** −0.41*** −0.08*** −0.18*** 0.95*** −3.76*** 5.65*** −0.18*** 0.07***

Negative Low VIX

VIX5 VIX RFD drSP500 Surprise Man Analyst Insthold Insthold Size Vol Beta ResStd Tech Duration Precision Dispersion

N

High VIX

High VIX

High–low

N

Mean

Std dev

N

Mean

Std dev

3257 3257 3257 3257 2623 2866 3257 2866 2866 2866 2866 3257 3257 3257 3245 3257 2879

15.59 −0.2 91.83 0.004 0.42 2.4 2.02 58.66 −4.83 7.17 8.66 1.19 2.48 33.83 56.88 2.07 1.28

2.91 1.63 27.39 0.79 2.34 12.54 0.79 36.66 25.66 1.54 0.81 0.58 1.29 47.32 52.62 0.48 0.53

2493 2493 2493 2493 1349 2272 2493 2272 2272 2272 2272 2493 2493 2493 2488 2493 2281

27.66 0.47 77.46 0.029 2.96 2.56 1.89 49.77 3.7 6.79 8.63 1.02 3.51 35.5 59.17 2.03 1.34

7.61 4.43 41.79 1.63 66.19 6.49 0.89 38.3 7.04 1.66 0.93 0.59 1.87 47.86 60.83 0.58 0.91

Low VIX

12.07*** 0.67*** −14.38*** 0.024 2.54 0.16 −0.13*** −8.89*** 8.54*** −0.38*** −0.03 −0.17*** 1.03*** 1.66 2.28 −0.04** 0.06***

High VIX

High–low

N

Mean

Std dev

N

Mean

Std dev

7674 7674 7674 7674 5276 6646 7674 6646 6646 6643 6643 7674 7674 7674 7661 7674 6699

15.72 −0.24 81.24 −0.01 −0.6 2.08 1.92 54.94 −5.28 6.63 8.52 1.19 2.68 36.28 57.71 2.04 1.42

3.11 1.6 39.05 0.8 2.23 6.93 0.81 37.01 25.21 1.61 0.83 0.62 1.4 48.08 63.34 0.54 0.7

7785 7785 7785 7785 2918 6897 7785 6897 6897 6897 6897 7785 7785 7785 7775 7785 6952

28.8 0.74 68.3 0.013 −0.87 1.94 1.76 46.86 2.9 6.33 8.43 1.01 3.54 33.71 63.28 1.98 1.44

9.33 4.76 46.53 1.71 1.71 5.6 0.89 35.54 5.71 1.77 0.94 0.65 1.74 47.27 51.23 0.68 0.98

13.08*** 0.98*** −12.94*** 0.023 −0.27*** −0.14 −0.15*** −8.08*** 8.18*** −0.3*** −0.09*** −0.18*** 0.86*** −2.57*** 5.56*** −0.06*** 0.02

Neutral Low VIX

VIX5 VIX RFD drSP500 Surprise Man Analyst Insthold Insthold Size Vol Beta ResStd Tech Duration Precision Dispersion

High VIX

High–low

N

Mean

Std dev

N

Mean

Std dev

9264 9264 9264 9264 7040 8139 9264 8139 8139 8138 8138 9264 9264 9264 9258 9264 8207

15.66 −0.23 87.03 0.02 −0.01 2.39 2.13 58.28 −5.55 7.23 8.49 1.18 2.44 39.37 45.67 2.16 1.37

3.02 1.61 33.6 0.79 0.12 15.05 0.79 36.74 25.78 1.69 0.78 0.57 1.26 48.86 42.88 0.51 0.56

7352 7352 7352 7352 3414 6604 7352 6604 6604 6603 6603 7352 7352 7352 7332 7352 6643

28.03 0.42 75.35 0.025 −0.02 2.13 1.97 49.87 3.09 7.01 8.47 1 3.24 33.43 51.24 2.13 1.39

8 4.5 43.1 1.62 0.45 5.9 0.91 37.45 6.44 1.83 0.89 0.59 1.68 47.18 55.73 0.75 0.84

12.37*** 0.65*** −11.67 0.004 −0.01 −0.26 −0.16*** −8.41*** 8.64*** −0.22*** −0.02 −0.18*** 0.81*** −5.93*** 5.57*** −0.04*** 0.01

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Table 5 Relationship between VIX and market response to company issued guidance. This table reports results of year fixed effect regression of CAR(−1, +1) around company issued guidance on right-hand-side variables of the eq. (1) for period 1996–2011. Right-hand-side variables: average VIX value over 5 days prior to company guidance release (VIX5) or change in level of VIX 2 days before relative to 30 days before guidance release (VIX), indicator of High level of VIX (dummy) if VIX is higher than average VIX over 1996–2011 (VIXhigh), indicator (dummy) of a period after Regulation Fair Disclosure (RFD), daily return of S&P500 on guidance announcement day (rSP500), guidance surprise measured as the difference between the forecast EPS (or midpoint of the range forecast) and the prevailing median analyst forecast, scaled by prior quarter stock price (Surprise), proportion of firm ownership by managers (Man), analyst coverage measured as log(1 + number of analysts following the firm (Analyst), proportion of firm ownership by institutional investors (Insthold), change in proportion of institutional ownership in the report quarter (Insthold), log of the market capitalization of the firm (Size), log of average trading volume of shares in the report quarter divided by number of shares outstanding (Vol), firm systematic risk (Beta), firm unsystematic risk (ResStd), dummy variable that classifies whether the firm is in a tech industry (Tech), duration in days from the previous quarter end to guidance date (Duration), precision of company issued guidance (Precision), and dispersion in industry price-to-book ratio (Dispersion). t-statistics are reported in parentheses. The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively. Panel A

Positive

Negative

Neutral

Positive

Negative

Neutral

Intercept

3.00 (1.21) 0.01 (0.22)

14.79*** (8.83) 0.02 (0.90)

3.11** (2.33) 0.07*** (4.94)

3.08 (1.27)

15.10*** (9.17)

4.44*** (3.40)

−0.06* (−1.93) −0.51 (−1.57) 2.99*** (3.19) 0.119 (1.51) 0.048*** (2.80) 0.07 (0.41) 0.011*** (3.22) −0.013* (−1.82) 1.00*** (10.59) −3.09*** (−19.96) 0.001 (0.40) −0.229** (−1.96) −0.95*** (−3.56) −0.02*** (−8.42) −0.29 (−1.59) −0.80*** (−5.11) 17.40% 13,537

−0.05* (−1.90) 0.31 (1.32) 0.61 (0.76) 0.149** (2.35) 0.019*** (2.92) −0.14 (−1.00) 0.001 (0.30) −0.004 (−0.85) −0.01 (−0.08) −0.45*** (−3.88) −0.001 (−0.78) 0.142 (1.56) 0.30 (1.60) 0.00 (−0.39) 0.40*** (3.17) −0.40*** (−2.98) 1.79% 14,738

VIX5 VIX

−0.07 (−1.61) −0.27 (−0.62) 0.23 (0.15) 0.364*** (3.30) −0.012 (−0.93) 0.14 (0.57) −0.001 (−0.14) −0.004 (−0.41) −0.58*** (−4.48) 0.37* (1.87) 0.006** (2.07) 0.594*** (4.20) 1.52*** (4.61) 0.01*** (3.95) 0.08 (0.32) −0.02 (−0.10) 5.34% 5,138

Adj. R2 N obs.

−0.46 (−0.95) 0.23 (0.15) 0.348*** (3.15) −0.013 (−0.94) 0.14 (0.57) −0.001 (−0.14) −0.004 (−0.47) −0.58*** (−4.47) 0.38* (1.88) 0.006** (2.09) 0.589*** (4.16) 1.52*** (4.60) 0.01*** (3.96) 0.08 (0.31) −0.02 (−0.07) 5.29% 5138

Panel B

Positive

Negative

Neutral

Positive

Negative

Neutral

Intercept

4.94** (2.48) 0.02 (0.83)

11.37*** (7.76) 0.05*** (3.03)

3.10*** (2.72) 0.09*** (6.49)

5.40*** (2.83)

12.22*** (8.49)

4.78*** (4.30)

−0.02 (−0.55) −0.58 (−1.29) 0.202* (1.76) −0.35 (−0.96) −0.009 (−0.72) 0.13 (0.42) 0.003 (0.81) −0.003 (−0.42) −0.60*** (−4.04) 0.13 (0.58)

0.00 (−0.02) −0.19 (−0.59) 0.056 (0.74) 19.89*** (3.77) 0.019 (1.20) −0.35 (−1.46) 0.010*** (3.23) −0.011** (−2.00) 1.01*** (9.14) −2.49*** (−14.50)

0.00 (0.02) 0.10 (0.41) 0.018 (0.29) 190.42*** (6.68) 0.013** (2.19) −0.22 (−1.23) 0.002 (0.88) −0.002 (−0.43) −0.06 (−0.76) −0.28** (−2.16)

VIXhigh RFD drSP500 Man Analyst Insthold Insthold Size Vol Beta ResStd Tech Duration Precision Dispersion

VIX5

−0.75** (−2.12) 3.02*** (3.22) 0.109 (1.38) 0.048*** (2.81) 0.07 (0.37) 0.011*** (3.21) −0.014* (−1.91) 1.00*** (10.63) −3.09*** (−19.96) 0.001 (0.38) −0.231** (−1.98) −0.96*** (−3.59) −0.02*** (−8.41) −0.28 (−1.56) −0.79*** (−5.00) 17.38% 13,537

−0.41 (−1.53) 0.59 (0.73) 0.147** (2.31) 0.019*** (2.89) −0.13 (−0.95) 0.001 (0.41) −0.005 (−0.96) 0.00 (0.04) −0.48*** (−4.07) −0.001 (−0.80) 0.146 (1.61) 0.31* (1.62) −0.001 (−0.50) 0.41*** (3.23) −0.36*** (−2.69) 1.93% 14,738

VIX VIXhigh drSP500 Surprise Man Analyst Insthold Insthold Size Vol

−0.82 (−1.64) 0.191* (1.67) −0.36 (−0.99) −0.009 (−0.72) 0.11 (0.37) 0.003 (0.84) −0.004 (−0.45) −0.59*** (−3.96) 0.12 (0.57)

−0.66* (−1.83) 0.050 (0.65) 20.20*** (3.83) 0.019 (1.20) −0.38 (−1.57) 0.010*** (3.35) −0.012** (−2.07) 1.02*** (9.30) −2.52*** (−14.67)

−0.76*** (−2.87) 0.023 (0.37) 195.38*** (6.87) 0.013** (2.16) −0.25 (−1.34) 0.003 (1.13) −0.002 (−0.48) −0.04 (−0.50) −0.33** (−2.54)

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10 Table 5 (Continued) Panel B Beta ResStd Tech Duration Dispersion Adj. R2 N obs.

Positive 0.005 (1.55) 0.679*** (4.09) 1.07*** (3.32) 0.01* (1.85) 0.48 (1.18) 5.32% 3959

Negative ***

0.008 (3.43) −0.356** (−2.54) −1.39*** (−5.80) −0.04*** (−13.50) 0.43 (1.39) 9.75% 8153

Neutral 0.003 (1.43) −0.095 (−0.89) 0.19 (1.07) −0.01*** (−5.27) 0.33 (1.41) 1.69% 10,389

significant when the model is applied to subsamples classified as positive or negative guidance16,17 . The coefficient of VIXhigh is negative and significant when the model is applied to subsample of negative guidance. Investors penalize firms to a greater degree in response to negative guidance when the level of VIX is higher than the historical average. This result is consistent with our hypothesis that the negative share price response to negative guidance is more pronounced during periods of high market uncertainty. Columns 3 through 6 show that when VIX5 is replaced with VIX, the coefficient is not significant for the positive guidance subsample. However, the coefficient of VIX is negative and significant when the model is applied to the negative guidance subsample, which supports the hypothesis that the negative share price response to negative guidance is more pronounced during periods of high market uncertainty. The VIXhigh variable is not significant in this specification of the model (columns 3–6). Panel B shows that while controlling for guidance surprise relative to prevailing analyst forecast (Surprise) for a subsample of guidance observations that have point or interval estimates, the coefficient of VIX5 is not significant when the multivariate model is applied to positive guidance subsample. However, it is positive and significant when the multivariate model is applied to the negative guidance subsample. This implies a less pronounced impact to a negative signal under conditions in which the market uncertainty is relatively high. Similar results are found for the neutral guidance subsample18 . However, coefficient of VIXhigh variable is negative and significant when the model is applied to subsample of negative guidance. The results indicate that while VIX level just prior guidance release may have positive effect on market reaction to negative news, if this level of VIX is above historical VIX average then market participants place lower valuation on the assets with negative news. This result is consistent with our hypothesis that the negative share price response to negative guidance is more pronounced during periods of high market uncertainty19 .

16 VIX5 is positive and significant, while VIX is negative and significant when the model is applied to the subsample of neutral guidance observations. This indicates that the higher current level of uncertainty is perceived as a positive signal in case of neutral guidance interpretation as it could be perceived as confirmation of the prevailing valuation, while the increase in uncertainly relative to the prior 30 days level may create more anxiety among investors, which can negatively affecting security valuation. 17 We also apply a model with controls for firm and year fixed effects and confirm that our results are robust. The coefficient of VIX5 remains positive and significant for the subsample of neutral guidance and insignificant for positive and negative guidance. VIXhigh is negative and significant for the subsample of negative and neutral guidance, and insignificant for the subsample of positive guidance. 18 Surprise variable is available for the sample period 2002–2011. 19 The coefficient of VIXhigh variable is also negative and significant when applied to neutral guidance subsamples, which indicates that high market uncertainty

Positive 0.005 (1.52) 0.682*** (4.11) 1.07*** (3.32) 0.01* (1.82) 0.45 (1.10) 5.31% 3959

Negative ***

0.008 (3.33) −0.357** (−2.54) −1.38*** (−5.73) −0.04*** (−13.53) 0.31 (1.02) 9.65% 8153

Neutral 0.002 (1.22) −0.094 (−0.87) 0.19 (1.11) −0.01*** (−5.33) 0.17 (0.73) 1.29% 10,389

The coefficient of Surprise is positive and significant in a model applied to negative and neutral guidance, and insignificant in a model applied to positive guidance. The results are consistent with an expectation that more negative surprise results in more pronounced negative reaction. The coefficient of RFD is positive and significant only for the negative guidance observations, which implies that Regulation FD mitigated the share price response to negative guidance announcements (Panel A). The control variable for market performance (drSP500) is positively related to share price response to positive and neutral guidance announcements in Panel A, and marginally significant for positive guidance announcements in Panel B. Since this variable controls for prevailing stock market performance, our VIX variables capture relationships between market uncertainty and the asset valuation process beyond the effects of stock market performance. The coefficient of the Man variable is not significant for the positive guidance subsample. Yet, it is positive and significant for the negative guidance subsample, which implies that the adverse effect of negative guidance is attenuated when the firm issuing guidance has a relatively high level of managerial ownership (Panel A). Several control variables suggest that firms characterized as having higher asymmetric information exacerbates the share price response to guidance announcements. The degree of asymmetric information can be represented by a firm’s size, risk, sector (technology or not), and dispersion of industry price to book ratios. The coefficient of Size is negative and significant for the positive guidance subsample and positive and significant for the negative guidance subsample, which implies more pronounced effects on smaller stocks in response to guidance in either direction. The coefficient of ResStd is positive and significant for the positive guidance subsample and negative and significant for the negative guidance subsample, which implies more pronounced effects on firms that exhibit higher levels of unsystematic risk in response to guidance in either direction. The coefficient of Tech is positive and significant for the positive guidance subsample and negative and significant for the negative guidance subsample, which implies more pronounced effects on firms in the technology sector in response to guidance in either direction. The coefficient of Duration is positive and significant for the positive guidance subsample and negative and significant for the negative guidance subsample, which implies that the longer firms wait to provide guidance the more pronounced effect is in response to guidance in either direction. The coefficient of Dispersion is negative and significant for the negative subsample, which implies more pronounced effects on firms whose corresponding

oppresses valuation for neutral guidance too, while insignificant when applied to the positive guidance subsample. When using VIX as the measure of market uncertainty while controlling for the magnitude of guidance surprise, the coefficient is not significant in any of the subsamples isolating particular types of guidance.

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ARTICLE IN PRESS High VIX

0.24*** 10.78*** −0.73*** 0.47*** 0.66*** 11.46*** 2.44 0.88*** 0.50*** 0.16*** −0.43*** 8.89*** −0.07 0.73*** −0.83 20.13*** −0.45*** −−0.95 0.85*** 19.06*** −3.87*** 0.98*** 0.53*** 0.22*** −0.54*** 10.46*** 0.18*** −0.12 11.63 −14.84*** −4.66*** −0.10 −0.18*** −8.37*** 8.96*** −0.37*** −0.03*** −0.19*** 1.02*** −0.53 1.29*** 1.38*** 6.61 45.01 7.60 6.06 0.91 37.20 6.22 1.88 0.94 0.61 1.85 47.72 9.18 19.85 27.21 71.78 −2.06 2.14 1.85 48.21 3.10 6.60 8.47 0.99 3.47 35.08 3.33 4.11 18,980 18,980 18,980 18,842 18,980 18,842 18,842 18,838 18,837 18,949 18,949 18,980 18,975 18,980 2.94 34.04 3.44 12.34 0.79 36.29 26.15 1.66 0.81 0.57 1.23 47.89 1.56 16.29 15.58 86.62 2.60 2.24 2.03 56.58 −5.86 6.97 8.50 1.18 2.45 35.61 2.04 2.73 17,113 17,113 17,113 16,984 17,113 16,984 16,984 16,981 16,981 17,100 17,100 17,113 17,109 17,113 10.56 −5.49*** −4.37*** −1.52 0.01* −0.78 2.65 −0.27*** 0.00 −0.13*** 0.91*** 1.04*** 1.55*** 0.54*** 73,393 73,393 73,393 72,108 73,393 72,108 72,108 71,020 70,989 68,390 68,390 73,393 73,329 73,393

16.41 66.49 3.04 3.19 1.18 37.52 −1.99 5.99 7.97 0.96 2.99 25.15 1.86 2.85

3.03 47.20 3.86 420.87 1.03 34.77 19.56 2.05 1.06 0.71 1.96 43.39 1.97 16.63

87,438 87,438 87,438 85,965 87,438 85,965 85,965 84,791 84,656 81,847 81,847 87,438 87,383 87,438

26.97 61.00 −1.33 1.66 1.19 36.74 0.66 5.72 7.97 0.83 3.90 26.19 3.40 3.38

6.06 48.78 7.30 6.03 1.02 284.94 528.78 2.15 1.14 0.62 2.46 43.97 9.60 18.08

***

Std dev Mean

High VIX

N Std dev Mean

Low VIX

***

Low VIX Mean

High–low

N

Mean

Low VIX

Std dev

N

High VIX

Std dev

***

High–low

Guide–no guide

11

VIX60 RFD qrSP500 Man Analyst Insthold Insthold size Vol Beta ResStd Tech Dispersion Litigation

20 We also do analysis with VIX over 30 days before earnings announcement. Results are the same. 21 We select 60 day period before earnings announcement for VIX measure in order to capture guidance announcement period for firms that decide to guide prior to earnings releases. Duration measure that captures days from the previous quarter to the guidance date ranges from 50 to 70 days as reported in Table 4. Therefore, guidance happens on average between 20 and 40 days before quarter end or 50 and 70 days before earnings release.

N

Next, we assess the association between market uncertainty and the decision to issue guidance. For this purpose, we create a sample of firms that guided at least once during the sample period, and then for each quarter we classify each firm according to whether it issued guidance prior to earnings announcement (Guide = 1) or it did not issue guidance (Guide = 0) during the quarter. The conditions of market uncertainty are identified prior to earnings announcements for both guiders and non-guider for each quarter as average VIX over 60 days before the earnings announcement20 . We examine this relationship with a multivariate analysis that controls for other characteristics that could also affect the likelihood of issuing guidance. Since the results just described do not control for confounding effects, we retest the impact of market uncertainty, while controlling for several firm-specific characteristics defined in prior studies that could be associated with the propensity of firms to issue guidance. Our main explanatory variable is VIX60, which is a level of market uncertainty measured as average of VIX 60 days before earnings announcements21 . Many of the control variables were used in the multivariate analysis of the share price in response to guidance. They include: indicator of whether the guidance occurred after Regulation Fair Disclosure (RFD), quarterly return of S&P500 prior to earnings announcement day (qrSP500), proportion of firm ownership by managers (Man); analyst coverage measured as log (1 + number of analysts that follow the firm) (Analyst); proportion of firm ownership by institutional investors (Insthold); change of institutional ownership in the firm in quarter t (Insthold); log of the market capitalization of the firm (Size); trading volume of shares of the firm measured as log of average per day trading volume of shares in quarter t divided by number of shares outstanding (Vol); systematic risk of the firm measured as beta from the market model over the estimation period of (−255, −46) days prior to guidance announcement (Beta); unsystematic risk of the firm measured as a standard deviation of the error term from the market model over the estimation period prior to guidance announcement (ResStd); dummy variable set equal to 1 when the firm is classified within the technology industry and zero otherwise (Tech); and dispersion in industry price-tobook ratio measured as standard deviation (Dispersion). We also include a variable to control for the firm’s exposure to litigation. We follow the method of Francis, Philbrick, and Schipper (1994) and use an indicator variable called Litigation that is set equal to 1 if the firm is a member of one of high-litigation-risk industries: biotechnology (SIC codes 2833-2836, SIC codes 8731-8734), computer (SIC codes 3570-3577, SIC codes 7370-7374), electronics (SIC codes 3600-3674), and retail 9SIC codes 5200-5961) industries.

Guide

6.2. Relation between market uncertainty and decision to issue guidance

No guide

industries exhibit more dispersed industry price to book ratios in response to negative guidance. Overall, the association between the share price response to the guidance announcement and the control variables is conditioned on the type of guidance issued.

Table 6 Characteristics of guidance decision sample. This table presents descriptive statistics of the following variables by guiders and non-guiders: average VIX value over 60 days prior to earnings release (VIX60), percentage of earnings announcements after Regulation Fair Disclosure (RFD), quarterly return of S&P500 prior to earnings announcement day (qrSP500), proportion of firm ownership by managers (Man), analyst coverage measured as log(1 + number of analysts following the firm (Analyst), proportion of firm ownership by institutional investors (Insthold), change in proportion of institutional ownership in the report quarter (Insthold), log of the market capitalization of the firm (Size), log of average trading volume of shares in the report quarter divided by number of shares outstanding (Vol), firm systematic risk (Beta), firm unsystematic risk (ResStd), percentage of firms that are in the tech industry (Tech), dispersion in industry price-to-book ratio (Dispersion), and percentage of firms in one of high-litigation-risk industries (Litigation). The statistics is provided separately for periods of low and high VIX, measured whether average VIX level 60 days prior to earnings release was below or above average daily VIX over 1996–2011 period, respectively. High–Low columns report difference in means and statistical significance of the difference. The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively.

A. Agapova, J. Madura / The Quarterly Review of Economics and Finance xxx (2015) xxx–xxx

Please cite this article in press as: Agapova, A., & Madura, J. Market uncertainty and earnings guidance. The Quarterly Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.qref.2015.12.001

183,599 35,768 147,831 9.11% 14.52%

2995.1 54.6 808.8 14 25.2 4183.2 14.1 49.2 312.7 664.4 6.4 329.8 1462.2 39.2 5

<0.0001 <0.0001 <0.0001 0.0002 <0.0001 <0.0001 0.0002 <0.0001 <0.0001 <0.0001 0.0116 <0.0001 <0.0001 <0.0001 0.0256

17,528.7

<0.0001

Coefficient −7.844 −0.015*** 1.076*** 0.016*** 0.877*** 0.521*** −0.091** −0.023 −0.037*** 0.439*** −0.103*** −11.84*** 0.567*** 0.005** 0.104 ***

152,969 5138 147,831 2.94% 11.53%

2

Pr > 2

2206.8 38.6 568.7 28.6 26.8 470.3 3.8 0.1 8.8 473.1 13.7 87.9 277.2 4.4 1.8

<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0498 0.763 0.0031 <0.0001 0.0002 <0.0001 <0.0001 0.0349 0.176

4561.9

<0.0001

Neutral 2

Coefficient −3.964 −0.004*** 0.302*** −0.017*** 0.126 0.778*** −0.084*** −0.334*** −0.247*** 0.248*** 0.048*** −14.521*** 0.542*** 0.001 −0.086 ***

161,269 13,438 147,831 4.51% 10.34%

Pr > ␹2

1528.9 7.5 159.6 84.1 0.8 2253.3 7.3 40.3 877.2 384.5 7 349.3 614 0.7 2.6

<0.0001 0.0062 <0.0001 <0.0001 0.3788 <0.0001 0.007 <0.0001 <0.0001 <0.0001 0.0081 <0.0001 <0.0001 0.4041 0.1081

7448

<0.0001

2

Coefficient −4.438 −0.013*** 0.721*** 0.003* 0.561*** 0.757*** −0.072** −0.159*** −0.037*** 0.126*** −0.034* −14.012*** 0.738*** 0.009*** 0.198*** ***

162,363 14,532 147,831 7.07% 15.62%

Pr > 2

1855.2 70.5 800.4 2.9 23.9 2195.4 5.9 10.3 22 97.6 3.3 284 1173.5 63.2 17.6

<0.0001 <0.0001 <0.0001 0.0901 <0.0001 <0.0001 0.0149 0.0014 <0.0001 <0.0001 0.0686 <0.0001 <0.0001 <0.0001 <0.0001

11,911.2

<0.0001

ARTICLE IN PRESS

LR 2 N obs. Guide No guide R2 Max-rescaled R2

−3.693 −0.007*** 0.457*** −0.004*** 0.432*** 0.672*** −0.077*** −0.254*** −0.093*** 0.215*** −0.031** −9.104*** 0.567*** 0.005*** 0.076** ***

Pr > 2

G Model

Intercept VIX60 RFD qrSP500 Man Analyst Insthold Insthold Size Vol Beta ResStd Tech Dispersion Litigation

Negative

Positive 2

Coefficient

A. Agapova, J. Madura / The Quarterly Review of Economics and Finance xxx (2015) xxx–xxx

All

QUAECO-897; No. of Pages 15

12

Please cite this article in press as: Agapova, A., & Madura, J. Market uncertainty and earnings guidance. The Quarterly Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.qref.2015.12.001

Table 7 Relation between VIX and guidance decision (Logistic Regression). This table reports results of logistic regression of decision to issue guidance on right-hand-side variables of the eq. (2) for period 1996-2011based on whole sample and by type of guidance (positive, negative, neutral). Right-hand-side variables: average VIX value over 60 days prior to earnings release (VIX60), VIX60Big, VIX60Mid, VIX60Small are the interactions of VIX60 with dummies identifying whether the firms belongs, respectively, to the portfolio of big, mid-size or small firms, indicator (dummy) of a period after Regulation Fair Disclosure (RFD), quarterly return of S&P500 prior to earnings announcement day (qrSP500), proportion of firm ownership by managers (Man), analyst coverage measured as log(1+ number of analysts following the firm (Analyst), proportion of firm ownership by institutional investors (Insthold), change in proportion of institutional ownership in the report quarter (Insthold), log of the market capitalization of the firm (Size), log of average trading volume of shares in the report quarter divided by number of shares outstanding (Vol), firm systematic risk (Beta), firm unsystematic risk (ResStd), dummy variable that classifies whether the firm is in a tech industry (Tech), dispersion in industry price-to-book ratio (Dispersion), and indicator (dummy) if the firm is a member of one of high-litigation-risk industries (Litigation). The symbols * , ** and *** indicate statistical significance at less than the 10%, 5%, and 1% levels, respectively.

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We apply the following multivariate logit model to determine whether the probability of issuing guidance is associated with VIX60, while accounting for the control variables identified above: Prob(Guide = 1)i,t

13

Columns 5 through 16 of Table 7 disclose results of logit analysis segmented by type of guidance news. We find that for all sub-

= ˛ + ˇ1 VIX60i,t + ˇ2 RFDi,t + ˇ3 qrSP500i,t + ˇ4 Mani,t + ˇ5 Analysti,t + ˇ6 Instholdi,t + ˇ7 Instholdi,t + ˇ8 Sizei,t + ˇ9 Voli,t + ˇ10 Betai,t +

(2)

ˇ11 ResStdi,t + ˇ12 Techi,t + ˇ13 Dispersioni,t + ˇ14 Litigationi,t + εi,t where the dependent variable Guide is 1 if firm i issues guidance in quarter t and 0 otherwise. Table 6 discloses descriptive statistics of the variables included in the multivariate analysis designed to assess the likelihood of issuing guidance. We conduct univariate tests for each variable to determine if its mean when firms guide differs significantly from its mean when firms do not guide. The comparison is conducted separately within periods of low market uncertainty (low VIX) and high market uncertainty (high VIX) periods22 . The Analyst variable is significantly higher for firms that guide in the low VIX period and in the high VIX period. The Insthold variable is significantly higher for firms that guide in the low VIX and high VIX period. The change in institutional holdings is significantly lower for firms that guide in the low VIX period, but is not significant when market uncertainty is high. Firm size and liquidity (as measured by trading volume) are significantly higher for firms that guide when tested in the low VIX and high VIX period. Beta is significantly higher while the ResStd variable is lower for firms that guide in the low VIX and high VIX period. The ratio of tech firms as a proportion of all firms that guide is higher than firms that do not guide. The Dispersion variable is higher for firms that guide in the low VIX period, but the difference in means of Dispersion between the firms that guide versus do not guide is insignificant in the high VIX period. The difference in the means of Litigation is not significant in the low VIX period, but the mean is higher for firms that guide in the high VIX period. Table 7 presents results from applying logistic regression analysis to assess how a firm’s propensity to issue guidance is conditioned on market uncertainty. Panel A shows that for the entire sample of firms, the coefficient of the VIX60 variable is negative and significant, which suggests that when average level of VIX 60 days prior to earning announcements increases, managers are less likely to issue guidance. Regarding the control variables, the propensity to guide is positively related to the Man, Analyst, Vol, Tech, Dispersion, and Litigation variables, consistent with the univariate results. It is inversely related to Insthold, Insthold, Size and ResStd, consistent with univariate results23 . Following Kasznik and Lev (1995) methodology, we further examine the effect of market uncertainty on a company’s decision to guide by type of guidance news (positive, negative, or neutral). We apply a logit model to each subsample of guidance news, where the dependent variable takes a value of 1 if firm i issues guidance in quarter t, and zero otherwise. The explanatory and control variables are the same as in Eq. (2).

22 Periods of low and high VIX are measured whether average VIX level 60 days prior to earnings release was below or above average daily VIX over 1996-2011 period, respectively. 23 As a robustness test, we follow Gomes, Gorton, and Madureira (2007) methodology and break-up the VIX60 variable according to the size group that the guiding firm belongs to, and create interaction terms. We define firm size in each quarter by placing top 25% largest firms into big firms group, bottom 25% smallest firms into small group, and the remaining middle 50% into mid-size group. The results (not reported) suggest that the relation between implied volatility and the propensity to issue guidance is conditioned on firm size. Our analysis shows that large and small firms have lower propensity to issue guidance than mid-size firms have when VIX60 is higher.

samples of guidance news, the coefficient of VIX60 is negative. To the extent that firms are less confident that they can accurately forecast earnings in periods of high market uncertainty, they may wish to avoid providing guidance when VIX60 is high. Furthermore, they may want to defer the release of information until conditions improve. The magnitude of the coefficient is relatively large for the positive and neutral types of guidance. The results here support the hypothesis that firms are less willing to offer guidance when the prevailing level of market uncertainty is high. Regarding the control variables, results in Table 7 for the subsamples segmented by type of guidance show that Analyst, Insthold, Size, Vol, ResStd, Tech, Dispersion, and Litigation are typically significant in the same manner as shown in Table 7 for the entire sample24 . 7. Conclusions We argue that the increased transparency resulting from earnings guidance may depend on the prevailing level of market uncertainty. While the increasing influence of market uncertainty on investor behavior is well documented, it is not been given adequate attention in studies on earnings guidance. We apply existing pricing theories based on ambiguity and uncertainty to suggest how investor perception of guidance and the managerial decision to issue guidance should be associated with the prevailing level of market uncertainty. According to Hansen and Sargent (2010), uncertainty is priced. Their model incorporates uncertainty about a state realization, and about valuation model uncertainty, and concludes that the consumer deals with uncertainty by skewing probabilities pessimistically. Epstein and Schneider (2008) show that when ambiguity-averse investors process news of uncertain quality, they presume a worst-case assessment of quality. Epstein and Schneider (2008) conclude that investors require compensation for low future information quality, and that investors react more strongly to bad news than to good news. In the framework of these theories, we assess the share price response to earnings guidance under disparate conditions of market uncertainty, as measured by levels and changes in VIX. We find a more pronounced negative share price response to negative guidance releases under environments representing higher market uncertainty, even after controlling for firm-specific characteristics that affect the uncertainty surrounding the firm.

24 As a robustness check, we perform similar analysis as in columns 5 through 16 but replacing the VIX60 with 3 variables that interact VIX60 with a size category of the firm. The coefficients of the interaction terms vary among types of guidance, and vary by firm size for a particular type of guidance (results are not tabulated). For the biggest firms, the coefficient is negative and significant for all types of guidance. For the mid-size firms, the coefficient is negative and significant for negative and neutral types of guidance. For the small firms, the coefficient is negative and significant for all types of guidance and has the largest coefficient among all size interaction terms, suggesting that small firms appear to be more reluctant to issue guidance in higher uncertainty market conditions than firms in other size categories. The decision to issue guidance in response to the market uncertainty level appears to be less sensitive for mid-size firms than for small or large firms.

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Furthermore, we find that the share price response to positive news guidance releases is not conditioned on market uncertainty. Overall, the results are consistent with Hansen and Sargent (2010) and Epstein and Schneider (2008) models’ implications about asymmetry of investor’s response to negative versus positive news. These results could also be partially explained by how market uncertainty could alter the firm’s decision to issue guidance. To the extent that firms use a more restrictive guidance selection process when the prevailing market uncertainty is high, the information content of their negative guidance may be more potent. We also test whether the propensity of management to issue guidance is related to the level of market uncertainty. Results show that the likelihood of issuing positive and negative guidance relative to no guidance (while controlling for other factors) is significantly lower during periods of increased market uncertainty. To the extent that high market uncertainty may exacerbate the signal relayed by negative information, firms may prefer to defer the announcement until the formal earnings announcement. Furthermore, to the extent that firms are less willing to issue guidance when their forecasts are less accurate (Libby and Rennekamp, 2012), increased market uncertainty might discourage firms from issuing guidance because it could hamper their ability to forecast earnings accurately. We also find that the relationship between some characteristics and the likelihood of issuing positive guidance differs in the high market uncertainty environment versus the low market uncertainty environment. Furthermore, we find that the relationship between some characteristics and the likelihood of issuing negative guidance differs in the high market uncertainty environment versus the low market uncertainty environment. In particular, the general inverse relationship between market uncertainty and the likelihood of issuing negative guidance is driven by the high market uncertainty environment, but this relationship is absent within the low market uncertainty environment. Overall, the share price response to guidance and the firm’s decision to issue guidance are conditioned on market uncertainty, but the specific association is dependent on the type of guidance of concern, and the measure of market uncertainty employed.

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Please cite this article in press as: Agapova, A., & Madura, J. Market uncertainty and earnings guidance. The Quarterly Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.qref.2015.12.001