1. Analysis of Repeated Firm Behaviors and Trend Analysis
Project 3
Nicole Maillette
PhD Candidate
Professor John Teall
International School of Management (Paris)
December, 2015

2. 1.0 INTRODUCTION
Neuro-finance is a science that studies risk taking habits. This field of research includes
investigations on patterns of recognition that are associated to risk-taking habits. Therefore the study of
trader's personality can help researchers correlate professional behaviors to risk taking or risk aversion.
Since risk taking is often correlated with a person's confidence in their own ability to deal with
financial issues; Glaser, Langer and Weber (2007) have studied investors' capacity to recognize
temporary trends that are correlated with risk aversion. During a within-subject design experiment
which tested probability estimation and quantile intervals; they find both types of trading behaviors.
Traders either displayed over and/or under-confident traits. They also stated that under-confidence in
trend recognition became more pronounced when using longer price history. Nevertheless most traders
had various degrees of overconfidence when trading in shorter time periods. Another important point
that was made is the fact that when they looked at the level of trading experience each subject
possessed; they found that professional traders displayed a higher number of overconfidence traits than
students. These results reenforced an earlier study conducted by Badescu and Du (2007).
Nevertheless the major finding in Glaser, Langer and Weber's (2007) research is the fact that
over or under-confident behaviors did not increase or decrease a person's capacity to see financial
trends.
Further research conducted by Bhandari and Deaves (2006) graphed demographics of
overconfidence. They stated that people fail to learn from past mistakes because they are overconfident
about their ability to recognize situations and patterns. In particular they found that gender and
education are consistently associated to overconfidence (x>=5%). According to this study, men do not
generally have more knowledge than women over short term investments. Furthermore educated
people do not know more about investment trends than experienced self-investors. The major
difference between the latter group is the fact that investing knowledge is what differentiate financial
successes. Therefore if educated and experienced investors acquire ongoing information regarding
future securities at a price time; their ability to foresee a “good deal” should be seen in their investing
actions.
The following analysis is based on the fact that the financial market should therefore reflect
investor's over or under-confidence in their capacity to recognize trends by generating price patterns
prior to certain announcements. The industry chosen for this study is the Banking industry because
money affects every person in the world and successful Banks are positively correlated with higher
price returns.

3. 2.0 METHODOLOGY
Chart #1 shows that the following analysis inputted fifty-three (53) acquisition events related to
fourteen (14) American Banks in order to answer the following questions:
1. The market appropriately anticipated the failure announcement and adjusted share prices accordingly
prior to the announcement.
2. The market quickly adapted to any additional information learned from the announcement.
3. The failure announcement was detrimental to acquirers' shareholders.
4. Are recurring events in regard to new acquisitions affect price changes. In particular does the
market react faster to the announcement that a Bank is again merging or acquiring another failed Bank.
Chart #1 Bank names and event number
Source: FDICWebsite as of Oct 02nd
2015 http://www.fdic.gov/bank/individual/failed/banklist.html

4. A list of failed Banks was obtained from the Federal Deposit Insurance Corporation (FDIC) in which
fifteen acquiring Banks were chosen. Each Bank is associated to one or two of the four factors having
the following properties:
a. One of the Banks had to have had more than 10 events listed (X = 10; Heritage Bank Group)
b. Some of the Banks had to have had only one event listed (X = 2,5,6,9,12,13,14)
c. Some of the Banks had to have had acquired other Banks and had to have been acquired by
another larger Bank (X = 3,10).
d. Some Banks had to have more than one event and less 10 events (X = 1,3,4,7,8,11,15)
The present study did not take into consideration the acquired or acquiring Bank size. Instead it looks at
the amount of acquisitions associated to an event that each Bank has made.
The purpose behind this principle is to find out if a pattern of acquisitions by one Bank affect a
trader's behavior by either increasing or decreasing the same Bank stock price. Trader's behaviors
would be recognized through the forming of similar trends prior to any new acquisitions.
Questions #1 and #4 would then be answered by testing the following hypothesis:
H1 states that trader's behavior is associated to price changes while H0 states that price changes
which affects shareholders' returns is not significant enough to be associated to trader's prior knowledge
of a specific event.
H1=traders' behavior is seen in market price change trends
H0=trader's behavior does not affect market prices
Bordino et al (2012) graphed trading behaviors by inputting volume trades and adjusted
close price prior to a specific event in time. They state in their paper that past studies have
demonstrated that volume shifts can be correlated with price movements. Furthermore they have found
out that volume queries is correlated with volume of transactions (Bordino et al, 2012, page 1).
According to this finding the above study takes the stand that an unusually large change in volume
prior to a merger should be an indication that traders may have had insiders information or have had
enough knowledge to find trends and are acting accordingly (Bordino et al, 2012). Therefore a Bank
that is continually acquiring other Banks should have a noticeable change in sales volume within three
days of the merger.
Dickerson, Gibson, and Tsakalotos (1998) paper on Takeover Risk and Dividend Strategy: A
study of UK Firms confirms that the effect of dividend payments can be employed to reduce takeovers.
Dividends payments has therefore a significant impact on keeping the loyalty of a firm shareholders.

5. The experimental group is formed by the Banks that have more than one acquisition (Group A =
1,3,4,7,8,10,11,15) while the control group is formed by the Banks which only has one known event
(Group B = 2,5,6,9,12,13,14) at the time of the study. Two independent variables were chosen to
determine if Group A is responding to external influences. It is assumed that volume of sales and
dividend payments have some impact on price changes. Moreover it is therefore believed that the more
acquisitions a Bank makes; the more patterns are formed which leads to significant price changes prior
to a specific event.
A two-way ANOVA analysis between group A and B and within group will demonstrate if a co-
dependence exists when Banks continuously acquire other Banks. A within group assessment in
particular in Group A should demonstrate that traders are more confident in their assessment when a
Bank mergers or acquires other institutions on a regular basis.
3.0 ANALYSIS
A first look at six (6) variables shows some correlation between the number of time a Bank
acquires or merges with another Bank. Overtime a higher number of occurrences is noted within
Group analysis.
Graph # 1
Source: Excell Calculations using recorded data from FDIC (2015)
Heritage Bank Groups (x=12 acquiring, x=1 acquired), Ameris Bank (x=8), Bank of Ozarks (x=7) and
Bear Stearn (x=8) are the four banks which have the most mergers and acquisitions from 2006 until
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
Group A: Multiple Mergers and Acquisitions/Bank affects
Event Analysis
3 days prior Volume change
3 days after volume change
DAY OF ANNOUNCEMENT
3 days prior Dividend paid
3days prior Price change more
than 50%

6. 2012). Graph #1 shows a change in share volumes three (3) days prior to the announcement; but there
is no noticeable price change for neither. Therefore Bordino et al. (2012) volume shift prior to an
announcement could indicate that a repeated financial behavior is correlated with a higher degree of
confidence in trader's decision to purchase or sell.
Graph #2
Source: Excell Calculations using recorded data from FDIC (2015)
When Graph #1 is compared to Graph #2 which shows no correlation between price and
volume changes prior to any event; the between Group analysis indicates that Group A possesses a
higher degree of correlation between its variables than what is demonstrated in Group B.
An ANOVA two-factor analysis was conducted between Group A and B since three conditions
were included in the test. Condition 1 included a change in volume three (3) days prior to the event,
Condition 2 included a price change three (3) days prior to the event while the last Condition 3
included the distribution of dividends three (3) days prior to the event. Nevertheless a further look at
Graph #1 shows that Firstmerit Bank did not have enough Mergers or Acquisitions to affect traders'
behaviors. Therefore Firstmerit Bank was eliminated from Group A.
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
Group B: 1st Know Merger or Acquisition /Bank affects
Event Analysis
3 days prior Volume change
3 days after volume change
DAY OF ANNOUNCEMENT
3 days prior Dividend paid
3days prior Price change more
than 50%

7. Chart #2 Between and Within Group A and B Volume changes
Source: Excell ANOVA analysis
Chart #2 indicates no significant difference (p=0.998) between Group A and B. Regardless of
dividend payments prior to an event, Group A and B do not differ in price and volume changes. This
result indicates that the market was not affected prior to any acquisition or merger announcement.
However there exists some effect between variables within a group F(2,3)=0.46, p=0.68.
Therefore a covariance study was conducted within Group A and Group B.
Chart #3 Correlation analysis between 3 variables in Group A
Source: Excell Correlation analysis
Chart #3 shows some correlation between a volume change and a price change three days prior
to an event for Group A (Cor = 0.44). Since Group A includes Banks with repeating behaviors, this
result would indicate that some trend is being noted by traders and they would act accordingly.
Alpha 0.05
Groups Count Sum Mean Variance
Group A 3 0.8583 0.2861 0.06139884
Group B 3 0.8571 0.2857 0.02042041
3 days prior vol 2 0.8308 0.4154 0.03364418
3 days div 2 0.4799 0.23995 0.071177645
3 days price change 2 0.4047 0.20235 0.007092405
Source of Variation SS df MS F P-value F critical
Within Group 0.05172451 2 0.025862255 0.4621809123 0.683909899 19
Between Groups 0.00000024 1 0.00000024 0.000004289 0.9985355891 18.512820513
Error 0.11191399 2 0.055956995
Total 0.16363874 5
ANOVA - Two Factor
Correlations 3 days vol 3 days div 3 days price
3 days vol 1
3 days div 0.2900323714 1
3 days price 0.4447507217 0.0518978328 1

8. Chart #4 Correlation analysis between 3 variables in Group B
Source: Excell Correlation analysis
A further look at Group B also indicate that a first time acquirer would not show any patterns
of purchase of sale. Chart #4 indicate no significant correlation between all three variables.
4.0 CONCLUSION
Two hypothesis were proposed in order to answer four (4) questions:
H1=traders' behavior is seen in market price change trends
H0=trader's behavior does not affect market prices
A Two-factor ANOVA study demonstrated that H0 the null hypothesis is correct and that trader's
behaviors do not affect market prices; but as long as Banks are not repeated acquirers or mergers.
Has the market therefore appropriately anticipated the failure announcement and adjusted share
prices accordingly prior to the announcement?
Graph #1 showed a marked increase in volume during and three (3) days after the event for
Group A (multiple acquisitions/mergers). Added to the correlation analysis of Group A, price changes
did occur but was not significant enough to state if the market appropriately anticipated a failure
announcement.
This paper did not further study if there was an increase or decrease in price prior or after the event. It
only looked at price and volume changes prior and after an acquisition or a merger.
On the other hand, the market did quickly adapt to any additional information learned from
prior behaviors. Even though the two-factor ANOVA analysis was not significant, the results in Chart
#3 and Chart #4 indicated that some variables could be correlated and could affect the behaviors of
traders.
Further study using linear regression in price changes should be conducted in a separate study
in order to show that an acquisition or merger event was detrimental to acquirers' shareholders. The
present study did not find any evidence of a negative effect on either Group A or Group B.
Nevertheless this study only looked at three days prior and after the event. Which means that any
linear regression would have been inadequate to show trend formation.
However, this study demonstrated that recurring events in regard to new acquisitions affect
Correlations 3 days vol 3 days div 3 days price
3 days vol 1
3 days div 0.0912870929 1
3 days price -0.25819889 -0.353553391 1

9. price changes. It appears that trend formation may be associated to repeating behaviors. Volume and
price changes are somewhat correlated. Group A which includes Banks which have acquired other
Banks eigth (8) times or more may have some impact on trend forming in the market.
A further look at Group A should be conducted in order to demonstrate that the Market may or
may not be efficient. As per previous paper long-term study may show trend formation, but this paper
only looked at a three (3) day short-term period.
This paper has therefore showed that the Market is efficient as long as a behavior is not repeated
over a long period of time.
REFERENCE:
Bhandari, G., & Deaves, R. (2006). The Demographics of Overconfidence.Journal Of Behavioral
Finance, 7(1), 5-11. doi:10.1207/s15427579jpfm0701_2
Biais, B., & Weber, M. (2009). Hindsight bias, risk perception, and investment performance.
Management Science, 55(6), 1018-1029. doi:10.1287/mnsc.1090.1000
Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A., & Weber, I. (2012). Web Search
Queries Can Predict Stock Market Volumes. Plos ONE, 7(7), 1-17. doi:10.1371/journal.pone.0040014
Dickerson, A. P., Gibson, H. D., & Tsakalotos, E. (1998). TAKEOVER RISK AND DIVIDEND
STRATEGY: A STUDY OF UK FIRMS. Journal Of Industrial Economics, 46(3), 281-300.
FDIC (2015) Federal Deposit Insurance Corporation. Failed Banks.
Retrieved from http://www.fdic.gov/bank/individual/failed/banklist.html on October 02 2015.
Filbeck, G., Hatfield, P., & Horvath, P. (2005). Risk aversion and personality type. Journal Of
Behavioral Finance, 6(4), 170-180. doi:10.1207/s15427579jpfm0604_1
Glaser, M., Langer, T., & Weber, M. (2007). On the trend recognition and forecasting ability of
professional traders. Decision Analysis, 4(4), 176-193. doi:10.1287/deca.1070.0099
Lai, M., Low, K. T., & Lai, M. (2001). Are Malaysian investors rational?. Journal Of Psychology &
Financial Markets, 2(4), 210-215. doi:10.1207/S15327760JPFM0204_5
Morante, F. (2010). Omnipotence, retreat from reality and finance: Psychoanalytic reflections on the
2008 financial crisis. International Journal Of Applied Psychoanalytic Studies, 7(1), 4-21.
doi:10.1002/aps.232