This is a team project in course Financial Accounting Thoery.

1. Binghamton University
Event Study: Stock Market Reactions to New CEO Announcement
ACCT 540 Financial Accounting Theory
Team # 105
Qin Li
Zhuting Meng
Xue Shao
Jie Yin
Yang Yang
2014/3/27

2. 1
1. Introduction and Literature Review
1.1 Introduction
CEO, whose duty is to maximize shareholders’ wealth by making sensible decisions, plays the most important role when it comes to the outlook and growth of a firm. His/her abilities, preferences and decisions profoundly affect the firm by the projects the firm selects, its financial policies, and the corporate culture. Regarding to empirical evidences, under ideal conditions, capital markets should be informationally efficient, suggesting that market prices will fully and unbiasedly reflect every publicly held information. Hence, a change in CEO is a significantly- vital event of a firm, and the market should react to new CEO announcement.
In our study, we investigate market reactions toward new CEO announcement using standard event study methodology. Firstly, based on the “Market Model”, we conduct our analysis using 50 randomly-chosen US listed firms which have an announcement of CEO succession during recent five years. The outcome shows a rough average Cumulative Abnormal Return (CAR) of 1.5% on each day during the event window with a p-value of 0.0626, which means that new CEO announcement induces a market movement with a 93.74% certainty. Secondly, we examine six primary variables to explain the differential market reactions: the company’s past performance, company size, the new CEO’s facial attractiveness, types of CEO departure, new CEO’s gender, and the origin of successor. In addition, we conduct a subgroup analysis filtered by the company’s past performance and types of departure. The result suggests that the market reacts differently depending on whether an internal or external candidate is nominated as CEO.
1.2 Literature Review
Top management change has always caught huge attention, and researches from various fields have been conducted. Many scholars have performed event studies of management turnover. Although the findings of those studies are sometimes in conflict with one another, they can provide us with a deeper understanding of this situation. Firstly, a firm’s past performance does influence the likelihood of a management change according to Furtado and Rozeff (1987). Secondly, the finding of Jensen and Warner (1988) indicates that management turnover is inversely related to share price performances. Thirdly, Bonier and Bruner (1989) find that in

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distressed firms, a top management change will come with an abnormal return of 2.48% on the previous day and the event date.
In order to explain the differential market reactions, scholars have also examined a variety of explanatory variables. According to the company performance hypothesis proposed by Warner, Watts and Wruck (1988), management turnover frequently happens to companies experiencing continuous poor performances. Besides, the firm size hypothesis suggests that new CEO announcement can be more powerful in small-size companies. Moreover, a Forbes article in January 2014 points out that attractive CEOs can boost companies’ stock prices after the hiring announcements. Other studies also suggest that market reactions to a new CEO announcement may depend on the types of CEO departures, forced or voluntary. Furthermore, new CEO’s gender hypothesis proposed by Lee and James (2007) highlights that the announcements of female CEO appointments may evoke negative stock price reactions.
In addition, the majority of empirical studies believe that the market may react differently depending on whether an internal or external candidate is nominated as CEO, so we conduct a subgroup analysis based on two scenarios identified in the research done by Dherment-Ferere and Renneboog. On one hand, in poor past performing firms, the nomination of an external CEO following the performance-related forced resignation may trigger a stronger positive market reaction, whereas internal promotion following poor performance and forced resignation may not be regarded favorably by the market. On the other hand, in well-performing companies with voluntary resignation, the nomination of an internal successor may create a less negative market reaction because the loss of company-specific human capital at the departure of the CEO is less.
1.3 Hypotheses
We conduct our study to test the following hypotheses:
H1: New CEO announcement is a market-moving event.
H2: The company’s past performance has an influence on cumulative abnormal returns.
H3: CEO succession announcements in small-size companies may trigger a stronger market reaction.
H4: Better-looking new CEO may have a positive effect on stock prices.

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H5: Market may react more positively to a forced resignation.
H6: The nomination of a new female CEO may evoke negative stock price response.
H7: Origin of CEO succession is correlated to abnormal returns.
2. Data and Methodology
The 50 firms are randomly chosen from firms publicly traded in NYSE and NASDAQ, which have announcements of CEO succession during recent five years from 2009 to 2013.
2.1 Data and Methodology of CAR
2.1.1 Model Introduction
We conduct our event study analysis based on the “Market Model”:
Rj = αj + βj × Rmt + εj
In terms of market model, abnormal return is the difference between actual return and predicted return. The event day is the day when firm initially issues an announcement of naming new CEO on official websites. We define this day as Day0, the one trading day before and after Day0 as Day-1 and Day+1 respectively. These consist of event window. Estimation window is the period one year prior to Day-2 till Day-2.
2.1.2 Data Source
Daily Holding Period Return (RET) and Value Weighted Average Market Return (VWRETD) are two parameters representing Actual Return of each firm and Average Market Return respectively, and they are obtained from Wharton Research Data Services (WRDS), CRSP daily stock files. The date range of data includes both estimation window and event window.
2.1.3 Procedures of Data Analysis
(1) A regression analysis is performed, with VWRETD as the independent variable daily market return, and RET as the dependent variable daily actual return of firm, to calculate α and β of each firm. Estimation window is used as our date range. In the regression result, the value of intercept corresponds to the value of α, and value of x variable refers to value of β.

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(2) Predicted Returns (PR) of the three days event window are calculated respectively based on the Market Model,
PR_Day-1 = αj + βj × VWRETD_Day-1
PR_Day0 = αj + βj × VWRETD_Day0
PR_Day+1 = αj + βj × VWRETD_Day+1
(3) Abnormal Returns (AR) during event window are obtained:
AR_Day-1 = Actual Return_Day-1 – PR_Day-1
AR_Day0 = Actual Return_Day-1 – PR_Day0
AR_Day+1 = Actual Return_Day-1 – PR_Day+1
In which, Actual Return is represented by RET.
(4) CAR during event window is the sum of Abnormal Return during event window (Day-1 to Day+1):
CAR(-1,0) = AR(-1) +AR(0)
CAR(0,1) = AR(0) +AR(1)
CAR(-1,1) = AR(-1) +AR(0) +AR(1)
(5) T-test
A descriptive statistical analysis of CAR(-1,1) of all 50 firms is conducted. T-statistic is calculated based on the results of descriptive statistical analysis:
In the formula, x bar refers to sample mean, μ refers to population mean, which is 0 in this case, s refers to standard deviation, and n refers to sample count.
(6) P-value is calculated based on the value of t-statistic and use of TDIST function:
P-value = TDIST(t-statistic, n-1, 2)
2.2 Data and Methodology of Variable Analysis

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2.2.1. Data Collection of Primary Variables
According to the statistics results, the stock returns change abnormally when companies announce the new CEO succession through their official websites. In this event study, the company’s past performance, firm size, the new CEO’s facial attractiveness, types of management departure, new CEO’s gender, and the origin of successor are examined as the primary variables.
Our sample data is mainly subtracted from the WRDS and the 50 firms’ official websites. We get the data of quarterly net income and total assets from Compustat (North America Fundamentals/Quarterly file) to calculate the ratio of ROA as the measurement of company’s past performance; we also retrieve the data of daily stock price and number of shares outstanding from CRSP to compute market cap as the measurement of firm size. When evaluating new CEOs’ facial attractiveness, we primarily rely on Google.com image searches and then use the Anaface.com, a facial beauty analysis website, to compute the Facial Attractiveness Index for 50 new CEOs. The information of CEO’s gender, origin of successor, and the types of departure are all captured from the news release on companies’ official websites. Table 3 provides the details about the definitions of explanatory variables.
2.2.2 Data Filtering
In this section, we focus on three variables, including the company’s past performance, forced or voluntary resignation, and internal or external succession. Based on the research conducted by Dherment-Ferere and Renneboog, we determine to analyze differential market reactions to new CEO announcement under two scenarios. The first scenario is that in company with poor past performance which has led to CEO resignation, the nomination of an external CEO may trigger a stronger positive market reaction. The second scenario is that in company with sound performance and voluntary resignation prior to retirement age, the nomination of an internal successor may be held more favorably by the market.
Therefore, we choose internal or external succession as the explanatory variable. As our sample includes 50 firms whose situations may vary, we choose past performance and forced or voluntary resignation as our filters and develop two subgroups of data. Under the first scenario, the subgroup includes companies with poor past performance and forced resignation. While

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under the second scenario, the subgroup includes companies with good past performance and voluntary resignation. Then, we run the regression on CAR over internal or external succession.
3. Empirical Results
3.1 Interpretation of Analysis of CAR
Following the procedure explained in previous section, we get a result of t-statistic and p- value of all 50 firms in our sample (See Table 1). However, the result of both t-statistic and p- value are not good enough to show the correlation to abnormal returns on and after announcement date. Besides, there is even an error to get the p-value of CAR(0,1), due to a negative mean value. A probable reason for the result is that a firm in our sample has a very strangely different abnormal return from the other 49 firms. ELECTRONIC ARTS INC, firm #50, has a quite large negative abnormal return during the 3-day event window.
We draw a trend line chart and find that all CARs are in a range from -0.2 to 0.2, except the CAR (-0.470561307) of ELECTRONIC ARTS INC, which has been circled in Figure 2. Due to the huge difference of CAR value, we consider it as an outlier and thus delete the firm from our sample.
With the rest 49 firms, we re-conduct the procedures again, and get the new t-statistics and p-value shown in Table 2.
In the new 49-firm sample, the average CAR shows a roughly 1.5% abnormal return on each day during the event window. The new p-value is 6.26%, which means that new CEO announcement induces a market movement with a 93.74% certainty. The result falls within the range of 0.05 to 0.1, which is a certainty level not very excellent but reasonable to show the influence of new CEO announcement on the market reaction. Hence, we consider new CEO announcement as a market-moving event.
3.2 Interpretation of Explanatory Variables
When analyzing the underlying factors driving differential market reactions, first of all, we examine the result of regression on CAR over the primary variables. Then, as the result is not statistically significant, we determine to filter our sample based on two variables forced or voluntary departure and company’s past performance, and examine the relationship between

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CAR and the origin of successor under two specific scenarios. Therefore, the first part of the analysis focuses on examining the three variables: new CEO appearance, firm size, and gender, while the second part of the analysis emphasizes on the rest three variables: origin of successor, the types of departures, and company’s past performance.
3.2.1 Analysis of Primary Variables
As we can see in Table 4, the p-values of six primary variables are larger than 10%, so the result is not statistically significant. To be more specific, we get a p-value of 0.292427 for the variable appearance which is larger than 10%, so we find no significant impact of the new CEO’s appearance on the share price changes. We get similar FAI scores with the researches from Halford and Hsu in 2013, but the final regression result is different. The potential factors causing different result could be the selection of event date, sample size and observation windows. To be more specific, their sample includes 677 chief executives and they measure the companies’ share performance three days before and five days after the date when the CEOs’ images are revealed. According to their findings, there is a positive relationship between CEO attractiveness and stock returns around new CEO’s announcements.
Moreover, the statistical result shows that there is little correlation between the share price changes and the size of firms’ with the new CEO announcement. Our sample size is rather small to develop a convincing statistical conclusion in terms of company’s size. As for the variable gender, in contrast to some statistics findings, there is no substantial share price movements in response to the announcements of new female CEO. In fact, a research conducted by Xerox Corporation in 2011 finds that CARs during the three event days of female CEO announcements are not significantly different from the male CEO announcements. This research investigates a relatively large sample of 114 firms with female CEOs in S&P 500, whereas findings of Lee and James (2007) are based on only 17 female CEOs in their sample.
3.2.2 Analysis of Origin of Successor
In firms which have poor past performances and forced resignation, an external CEO may be hailed more favorably by the market in contrast to an internal successor (scenario one). As we can see in Table 5, we get a p-value of 0.085123, which is less than the 10% threshold, indicating that our result is statistically significant at the 10% confidence level. Therefore, internal/external

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succession is correlated to abnormal returns. Furthermore, the coefficient of x variable (0.069089) is positive, indicating that there is a stronger positive market reaction if the company nominates an external candidate (external=1, Internal=0) (Figure 3). This is because an internal successor is held partially responsible for past poor performance. Moreover, since the company’s existing strategy is not working well, an external candidate is preferred as he may bring change and revive creativity.
In well-performing companies with voluntary resignation, the nomination of an internal successor may create a less negative market reaction (scenario two). The reason why the market may react more favorably to internal successor is that an internal candidate understands the company’s culture and is aware of the specific internal needs of the company. In addition, hiring an outside CEO is relatively more costly than promoting an internal manager due to large pay packages for outside recruits. As we can see in Table 6, the p-value is 0.838054 which is significantly higher than 10%, so our result is not statistically significant. Nevertheless, the coefficient of x variable (-0.005817) is negative, indicating that the market reaction is smaller if the company nominates an internal successor (internal=1, external=0), which is in consistent with our hypothesis.
4. Conclusion and Critiques
This study analyzes share price reactions to CEO succession announcement. A 93.74% certainty of market movement is triggered by the new CEO announcement. Therefore, the announcement of CEO succession is a market-moving event.
This paper also analyzes how different variables may affect market reactions, represented by cumulative abnormal returns. Five of six variables in the analysis show no significant correlation to abnormal returns. Under specific firm scenarios, the origin of new CEO (internal versus external candidate) may cause differential market reactions. Our result shows that in company with poor past performance and forced resignation, the nomination of an external candidate indeed causes a stronger positive market reaction.
There are mainly two limitations in our analysis. Firstly, the sample size in our study is too small when comparing with sample size in other academic papers, which contain a normal sample size of 600 to 800 firms. In particular, when we are analyzing the two subgroups of data,

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our sample becomes even smaller as only a few companies fit into the scenarios. Secondly, our analysis is based on a multi-regression model, while many scholars conduct a more complex model in their studies. We can get better results if we use a more complex model to analyze the situation.
As future accounting professionals, we can learn real skills to provide an independent evaluation on company’s CEO turnover and get a good understanding of company’s structure.

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References
1. Furtado, Eugene P.h., and Michael S. Rozeff. "The Wealth Effects of Company Initiated Management Changes." Journal of Financial Economics 18.1 (1987): 147-60. Print.
2. Jensen, Michael C., and Jerold B. Warner. "The Distribution of Power among Corporate Managers, Shareholders, and Directors." Journal of Financial Economics 20 (1988): 3-24. Print.
3.Bonnier, Karl-Adam, and Robert F. Bruner. "An Analysis of Stock Price Reaction to Management Change in Distressed Firms." Journal of Accounting and Economics11.1 (1989): 95-106. Print.
4. Dherment-Ferere, Isabelle, and Luc Renneboog. “Share Price Reactions to CEO Resignations and Large Shareholder Monitoring in Listed French Companies.” Center for Economic Research (2000): No. 2000-70. Print.
5. Lee, Peggy M., and Erika Hayes James. “She’-E-Os: Gender Effects and Stock Price Reactions to the Announcements of Top Executive Appointments.” Darden Business School Working Paper (2003): No. 02-11. Print.
6. Adams, Susan. "Do Attractive CEOs Really Boost Their Companies' Stock Prices?" Forbes. Forbes Magazine, 07 Jan. 2014. Web. 20 Mar. 2014.
7. Halford, Joseph Taylor, and Scott H. C. "Beauty Is Wealth: CEO Appearance and Shareholder Value." SSRN, 21 Nov. 2013. Web. 20 Mar. 2014.

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Appendix of Table
Table 1. Cumulative Abnormal Returns (CAR) of 50-firm sample
No.
Firm Name
Event Date
Car(-1,0)
Car(0,1)
Car(-1,1)
1
Apple Inc
8/24/2011
0.012066398
0.001832566
0.018551926
2
Bank of America
11/9/2009
0.064282
0.058479
0.06228
3
Best Buy
8/20/2012
0.000272
-0.00427
-0.00265
4
Barclays Plc
8/30/2012
-0.010314524
-0.00452234
-0.017550414
5
Bank of New York Mellon Corp
12/10/2013
0.017394186
0.001662657
0.003498453
6
Citigroup Inc
10/16/2012
0.035424654
0.016753908
0.056772426
7
Chevron Corp New
9/30/2009
0.013265293
-0.004307427
0.005479553
8
Deutsche Bank A G
11/1/2012
0.029349214
-0.00679599
0.031796029
9
First Niagara Finl Group Inc Ne
12/19/2013
-0.056682776
-0.040434605
-0.04484122
10
General Motors Co
12/10/2013
0.005973457
0.001291842
0.016216695
11
Groupon
8/7/2012
0.050403776
0.041969425
-0.015951073
12
Harley Davidson Inc.
4/8/2009
-0.004616661
0.103089279
0.070072909
13
Hewlett Packard Co
9/22/2011
0.083859645
-0.038253659
0.059489984
14
International Business Machs Co
10/25/2011
-0.006713221
0.00259554
-0.007073004
15
Intel Corporation
5/2/2013
0.010226954
-0.012205869
0.00266892
16
Lockheed Martin Corp
11/9/2012
-0.006952681
-0.00274402
-0.009224981
17
Massmutual Corporate Invs Inc
12/30/2009
0.008617534
-0.008888881
0.013064146
18
Morgan Stanley
9/10/2009
0.034446569
0.034257067
0.01892876
19
Netapp Inc
8/19/2009
-0.007285583
-0.078135041
-0.078529241
20
Pepsi Co
3/12/2012
0.1476641
0.117379786
0.085187289
21
Rite Aid Corp
1/21/2010
0.057918876
0.045733048
0.057768166
22
Sandridge Energy Inc
6/19/2013
-0.001366809
-0.020034229
-0.028949426
23
Silicon Graphics, Inc.
2/23/2012
0.002942
0.010586
0.004759
24
Siemes
7/31/2013
0.005009933
0.006687638
0.003476758
25
Stryker Corp
10/1/2012
-0.014322275
-0.021327752
-0.019463626

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26
Symantec Corp
7/25/2012
0.130168494
0.146096245
0.140366923
27
Union Bank of Switzerland
11/16/2011
-0.010627493
-0.019943914
-0.036580232
28
Verizon Communications Inc
7/22/2011
-0.026006307
-0.035332993
-0.037360536
29
Xerox Corp
5/21/2009
0.031609677
0.003028322
0.026208245
30
American International Group Inc
8/3/2009
0.001101676
-0.005151408
-0.005116175
31
Advanced Micro Devices Inc
8/25/2011
-0.013810401
0.022936904
-0.017485692
32
Aol Inc.
12/4/2009
0.002817143
0.01279735
0.004046039
33
Avon Products Inc
4/9/2012
0.010033353
-0.024823921
0.005805162
34
Boston Scientific Corp
9/13/2011
-0.009154341
-0.001752094
0.007057925
35
E-Trade Financial Corporation
1/17/2013
0.001322761
0.016096449
0.027589942
36
Green Mountain Coffee Roasters I
11/20/2012
0.107430487
0.014284706
0.10133127
37
Hologic Inc
12/9/2013
-0.024515198
-0.002834979
-0.01828989
38
Penney J C Co Inc
6/14/2011
0.164259164
0.144035714
0.151662708
39
Lululemon Athletica Inc
12/9/2013
-0.015548689
-0.00756471
-0.028912288
40
Nokia Corp
9/10/2010
0.019695603
0.023412294
0.027498265
41
Rogers Communications Inc
9/12/2013
-0.011134324
-0.005771876
-0.006654644
42
Radioshack Corp
2/7/2013
-0.006382078
0.080206225
0.091288749
43
Sears Holdings Corp
1/7/2013
0.007424773
-0.039902344
-0.053661201
44
Ulta Salon Cosmetics & Frag Inc
6/24/2013
0.05189607
0.042641855
0.04990449
45
Weyerhaeuser
6/16/2013
-0.009210255
-0.076729614
-0.036373191
46
Yahoo Inc
7/16/2012
-0.014849663
-0.013384985
-0.024003492
47
Zynga Inc
7/1/2013
0.07881905
0.167045524
0.141505397
48
Qualcomm Inc
12/13/2013
-0.004409806
-0.005713438
0.168616527
49
Blackberry Ltd
8/20/2012
-0.190692781
-0.138620124
-0.159848033
50
Electronic Arts Inc
3/18/2013
-0.438044037
-0.501164553
-0.470561307
Average
0.006061099
-0.000114228
0.00667626
T-Statistics
0.51340638
-0.00889
0.518088
P-Value
0.60997436
Error
0.606728

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Table 2. T-test and P-value of CARs of 49-firm sample
CAR(-1,0)
CAR(0,1)
CAR(-1,1)
Average
0.015124469
0.010111288
0.016415802
t-Statistics
1.9588824
1.27489
1.906165
p-Value
0.0559498
0.208485
0.062626
Table 3. List of Explanatory Variables
Measurement
Variable
Source of Data
Past Performance
Return on Assets
NIQ/ATQ (Net Income/Total Assets)
Good = Positive Sign
Bad = Negative Sign
Compustat
Facial Attractiveness Index
Anaface Evaluation
Rating out of 10
Anaface.com
Size
Market Capitalization
ABS (Price*Shares outstanding)
CRSP
New CEO's Gender
Female or Male
Female=1,Male=0
Firm's Official Websites
Origin of Successor
Internal or External Succession
External=1, Internal=0 (scenario 1); Internal=1, External=0 (scenario 2)
Firm's Official Websites
Type of Departure
Forced or Voluntary Resignation
Forced=1, Voluntary=0
Firm's Official Websites
Table 4. Regressions of CAR(-1,1) over Explanatory Variables
Coefficients
t-Statistics
p-Value
Size
-0.00712
-0.52495
0.602668
Past Performance
0.012956
0.678364
0.501652

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FAI
-0.01106
-1.06762
0.292427
Types of departure
0.028801
1.65238
0.106698
Gender
0.000309
0.014427
0.988565
Origin of Successor
-0.00895
-0.4905
0.6266
Adjusted R Square
-0.02535
N
45
Table 5. Regression of CAR over Internal/External Succession
Scenario One
Coefficients
t-Statistics
p-Value
Internal/External Succession
0.069089
2.003938
0.085123
Adjusted R Square
0.273768
N
9
Filter: Poor Prior Performance & Forced Resignation
The market favors external succession.
Table 6. Regression of CAR over Internal/External Succession
Scenario Two
Coefficients
t-Statistics
p-Value
Internal/External Succession
-0.005817
0.208869
0.838054
Adjusted R Square
-0.079409
N
14
Filter: Good Prior Performance & Voluntary Resignation
The market favors internal succession.

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Figure 1. This figure presents a screen shot of anaface.com. The photograph is CEO of Yahoo, Marissa Mayer, by Google.com.
Figure 2. Trend line of CARs of 50-firm sample
-0.6
-0.4
-0.2
0
0.2
0.4
1
5
9
13
17
21
25
29
33
37
41
45
49
Value of CAR
Number of Firms
Trend Line of CAR(-1,1)
Trend Line

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Figure 3. Correlation between CAR and Internal/External Succession
Figure 4. Correlation between CAR and Internal/External Succession