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HOT & COLD VALUATION BIASES
Bachelor thesis
Name
Stefano Haro Alfaro
Student nr.
354679
Supervisor
Prof. J.T.J Smit
1
CONTENTS
1.
Introduction ........................................................................................................................ 2
2.
Theoretical framework ....................................................................................................... 3
2.1
Experiment................................................................................................................... 3
2.2 Projects ............................................................................................................................. 3
2.3 (Standard) Option ............................................................................................................. 4
2.4 Real Option ....................................................................................................................... 4
2.5 Behavioral bias: Over optimism........................................................................................ 5
2.6 Behavioral bias: Anchoring ............................................................................................... 5
2.7 Hot & Cold deal markets................................................................................................... 6
3.
Experiment .......................................................................................................................... 6
3.1 Managerial mindset .......................................................................................................... 7
3.2 Different treatments......................................................................................................... 8
3.2.1 Random economic shocks.......................................................................................... 9
3.2.2 Competitive bidding ................................................................................................... 9
3.2.3 Deal outcomes ......................................................................................................... 10
3.2.4 Reservation price ..................................................................................................... 11
3.3 The bidding process ........................................................................................................ 11
3.3.1 Structure .................................................................................................................. 11
3.3.2 Rationality, expectations and mitigation ................................................................. 13
4.
Participants ....................................................................................................................... 14
4.1 Selection ......................................................................................................................... 14
4.2 Monetary incentive ........................................................................................................ 15
5.
Analysis ............................................................................................................................. 16
5.1 Main results .................................................................................................................... 16
5.2 Further specification ....................................................................................................... 17
6.
Conclusion ......................................................................................................................... 17
7.
Actual Experiment ............................................................................................................. 18
8.
Limitations......................................................................................................................... 18
9.
Appendix ........................................................................................................................... 19
9.1 Example experiment ....................................................................................................... 19
Bibliography.............................................................................................................................. 23
1. INTRODUCTION
Valuation biases are extensively researched through a behavioral finance lens in the past
couple of decades. Findings include popular terms like ‘mental accounting’, ‘prospect theory’
and ‘anchoring’.
A somewhat less researched topic is the valuation bias caused by the market itself. In the
world of mergers and acquisitions, there is a constant cycle which shows both intensive deal
making periods as the not-so-intensive deal making periods. The former are called hot deal
markets or M&A booms and are accompanied by positive market sentiment en aggressive
competitive bidding. The latter are called cold deal markets and are characterized by
pessimism and cautiousness.
This study aims to research the effect of the market on bidding behavior, in a competitive
auction for deals. Furthermore, real options are added to the auction to see how these are
valued in different turns of the cycle.
The research will be based on a controlled experiment, conducted to analyze how people
make decisions in an uncertain environment where both the hot deal market as the cold
deal market are implemented in the experiment.
To conduct such an experiment, a series of pitfalls must be accounted for. How does one
measure optimism? How does one simulate a hot/cold deal market? Whom is suited to
participate in this experiment? What are the expectations with regards to results and how
will this compare to the actual results? How do human cognitive errors interact in a bidding
environment and how can these be controlled?
These and much more of this kind of questions are necessary to ask, if one conducts an
experiment which relies on the subjective valuation of participants.
This thesis tries to analyze how such an experiment should look like, in order to measure
what should be measured.
How does one accurately test for hot & cold valuation biases?
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2. THEORETICAL FRAMEWORK
2.1 Experiment
In order to test for overoptimism and the change of behaviour under different
circumstances, an experiment will be conducted. In this experiment, the manner in which
the questions will be asked is of great importance. Because this experiment will have to
point out how participants act in different settings (see Hot & Cold Deal Markets for
explanation what kind of settings) it is mandatory to have a control group to which the
different ‘treatments’ can be compared to. Further specifications about how this experiment
will look is discussed in the following paragraphs. Participants have a monetary incentive to
seriously consider their answers instead of randomly guessing. This will be discussed in
“Monetary incentives”.
2.2 Projects
The projects for which the participants will have to bid for are defined as the text book
definition of projects, which is defined as a series of certain cash flows with parameters t,
CFt and r:
t
length of the project
CFt
cash in- or outflow on time t
r
discount rate
In the experiment, participants will have to bid for a project, based on both their intuition
and calculative skills just like in the business environment. The intuition part comes in after
the explicit cash flows. Participants will have to guess what the outcomes of a certain project
will be in order to calculate what the project is actually worth. The acquisition of a project
will be called a deal from now on.
When making deals, often a too static NPV method is used with no regard for future
uncertainty. Such a way of valuing projects works fine whenever cash flows are certain and
everything can be predicted. However, in real life such a situation isn’t the case most of the
time. Often, a horizon value is used to value the continuation value of the project after the
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explicitly modeled cash flows. Such a horizon value can be very subjective and is highly
suggestible by manager biases such as confirmation bias or over optimism.
2.3 (Standard) Option
A financial option gives the holder the right but not the obligation to buy or sell a tradable
asset at a predetermined price (X) at a certain date in the future (t). A distinction is made
between call options and put options. A call option gives the holder the right to purchase, a
put option entitles the holder to sell. The value of an option is in the fact that under
uncertainty, the prices of the underlying assets may fluctuate. An option holder can make
use of the positive market shocks, while in a negative scenario the option need not be
exercised.
2.4 Real Option
A real option is related to the financial option, only here the option relates to an investment
decision (which often is not publicly traded) as opposed to the tradable asset in the financial
option. The value of these options is the fact that the commercial prospects are often
uncertain and the market can develop both in a positive and negative way. Of the real
options this study covers the three basic options: Defer, Abandon, Expand. Besides these
three real options there are a multitude other real options that are not discussed in
connection with brevity. Furthermore, these other options are variations and combinations
of the three basic options. In the experiment, the participants will only have to consider
these three options. These will now be briefly explained.
The option to defer is the option to run a project in the future instead of now. By
postponing, the holder can see what the market is doing and when the market is sufficiently
developed in a positive way, make the investment. At the same time the holder has the
option not to perform when the market does not develop well. In fact, the option to defer is
a call option on the underlying project with the exercise price (X) of the investment required.
The option to abandon a project is the option to cancel a project which already has been set
in motion and the holder may or may not receive a certain amount for this abandonment
(Salvage value). This allows the holder of the option to keep the losses at a minimum instead
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of keeping a loss-generating project too long. The option to abandon a project is a put
option on the underlying project with the exercise price of the salvage value.
The option to expand is the option to increase the scale of a project which has been already
set in motion in order to increase revenues. Often, an additional investment is required. This
option is, as all call-related options, especially valuable when the market develops in a
positive way. In this case, the required investment is the exercise price of the option.
(Damodaran, 2005)
2.5 Behavioral bias: Over optimism
Optimism makes people overestimate the value of projects systematically. This follows
according to Kahneman & Tversky from an underestimation of the costs, time and difficulties
of completing the project, and an overestimation of the cash flows from the project.
(Kahneman & Tversky, 1979). In the experiment the focus will mainly be on the second part,
as the investment will be determined through an auction and the timing of the investment is
certain and given. Then the valuation of projects, which will be measured through
competitive bids, will be compared with valuations in a different setting. In this way, one can
observe the difference in valuation caused by the change in setting.
2.6 Behavioral bias: Anchoring
A mechanism that biases valuations and estimations in general is anchoring. Tversky &
Kahneman wrote a paper which explained how this bias arises:
“In many situations, people make estimates by starting from an initial value that is adjusted
to yield the final answer. The initial value, or starting point, may be suggested by the
formulation of the problem, or it may be the result of a partial computation. In either case,
adjustments are typically insufficient (4). That is, different starting points yield different
stimates, which are biased toward the initial values. We call this phenomenon anchoring.”
(Tversky & Kahneman, 1974)
According to this explanation, any information provided during the experiment can bias the
participants in a certain manner. Examples of potential ‘anchors’ in valuation are bids of
competitors, reservation prices and expected values of projects.
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2.7 Hot & Cold deal markets
Hot deal markets are described as markets in which exuberance of investors in financial
markets along with positive sentiment of boards and aggressive acquisition behavior of rivals
leads to overestimation of projects (Smit & Lovallo, 2014). In such a market, too much focus
is on the long term growth estimation, which is unrealistically high. This causes a great
valuation bias which in turn affects the prices paid.
The other side of the spectrum are the so called cold deal markets. Here, pessimism and
inactive acquisition behavior attribute to a framing of deals with too much focus on the risk
involved, ignoring the long term growth. One could argue that a cold deal market is exactly
the opposite of a hot deal market in terms of how the deals are analyzed. These hot and cold
deal markets correspond
M&A Deals 1995 - 2013
with the phenomenon of
M&A waves. In the figure
on the right a depiction of
12000
11000
10000
this wave is shown
9000
(Thomson Reuters, 2014).
8000
Here, the peaks of the cycle
7000
would be a hot deal market,
6000
the bottom of the cycle vice
5000
4000
versa.
Figure 1
3. EXPERIMENT
In order to conduct a solid experiment, a series of questions should be asked. These
questions will have to be chosen carefully, as the way in which they are asked also
determines the outcome.
First off, to be able to make a bridge between the experiment and the real life counterpart,
it is important that the participants act like they are the real life counterpart. The bridge
between the experiment and the real world is dependent on who the participants are, which
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will be elaborated on in ‘Participants: selection’. In the experiment, participants are ought to
represent managers in a business environment.
Next up, it is important that the participants can be compared with one another. This is done
by designing and implementing different treatments, which will be administered randomly
to the participants. There are within the experiment a few ways in which it is possible to
treat the participants in a different manner. These ways of implementing the treatment will
be discussed below.
When the participants have been assigned to the different treatments, the real experiment
begins. The main results will be observed through a controlled auction, in which the
different treatments should yield different results. Here the output variable will be B, the bid
of the participant in question.
Lastly, there will be looked for a way to mitigate the supposed valuation biases, caused by
the different treatments. Valuation literature brings the use of a more dynamic approach
instead of the static NPV method. This dynamic approach usually includes the use of real
options, which allow for an objective tool to bring either more caution (in case of hot deal
markets) or more venture (in case of cold deal markets) to the analysis of a deal.
Now, all the different components of the experiment will be discussed in more detail.
3.1 Managerial mindset
In the experiment, participants will be asked questions as if they would be responsible for
the projects in question. A way to warm the participants up for the real questions is the use
of some preliminary questions. By asking these questions, a basic overview of the participant
is obtained, as well as the degree of over optimism, which can be used later when comparing
the results. Also, these questions are used to put the participant in a competitive,
managerial mindset by asking questions where they have to rank themselves compared with
other participants. Lastly, a question about loss aversion is asked to get an insight in how
loss averse the participant is.
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3.2 Different treatments
In the experiment, certain variables need to be measured. In order to test for a change in
degree of managerial optimism, the different situations (being ‘hot’ and ‘cold’) have to be
compared with each other. The main idea behind this experiment rests on the fact that there
are basically three different treatments.
The first treatment is called ‘neutral’ and should encourage the participant to act in a normal
manner. No specific interventions are made to influence the state in which the participant
will be. This group will be the control group, which both other treatments will be compared
with.
The second treatment is called ‘hot’, which should correspond with a hot deal market.
Participants with the hot treatment are expected to act less cautiously and more
aggressively. This should be observable through the bids these participants make, which
should be higher than those of the other two groups.
The third treatment is called ‘cold’ and corresponds to a cold deal market. Here, the
participants are expected to act somewhat reluctant and more cautious compared with the
other two groups. On the same grounds as above should this be observable by looking at the
bids of this group.
How will this treatment be implemented in the experiment?
Because of the fact that the main cornerstone of the experiment are the fact that
participants undergo different treatments, it is necessary to put the participants in such a
position that they actually really experience the treatment in a manner which they are
supposed to. In order to frame the participants in such a way that they act according to the
treatment they’re under, it is extremely important that they have an incentive to do so. This
is why a monetary incentive, which will be explained later, is obligatory to this experiment.
With this monetary incentive, a lot of possible tools are suddenly useable to manipulate the
mindset of the participant. A number of applications of the hot & cold treatment will now be
discussed.
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3.2.1 RANDOM ECONOMIC SHOCKS
A cold deal market often coincides with economic downturn.1 Due to all the effects which
come along with this economic stagnation, managers of firms are usually somewhat
restrained to make deals and do projects. By administering the participants a monetary
shock, they can be framed in a similar mindset. Because the economic shock here directly
influences the monetary payoffs of the participant, they will probably be embittered and
more cautious in the future. This should induce the participants to act in a ‘cold’ manner, i.e.
less active and aggressive bidding behavior.
In a manner analogous to what is described above, hot markets often coincide with
economic upturns. Better liquidity, good economic prospects and positive market sentiment
causes boards and managers to be optimistic about deals and projects. By informing
participants about the favorable market conditions and providing them with a monetary
boost, they will most likely be more in a hot market state-of-mind that their cold treatment
counterparts. This mindset should entail more aggressive bidding behavior and thus higher
bids.
3.2.2 COMPETITIVE BIDDING
Because participants will have to bid for a project and only receive the payoffs of such a
project if they win the auction, the “opponents’ bids” can be used as an instrument to
influence the bidding behavior of the participant. These bids can be constructed fictional in
order to put a participant with a hot treatment in a hot market bidding environment and a
cold market participant vice versa. These fictional bids are not the actual bids of the other
participants. However, they will be told that these bids are the in fact the bids of other
participants, so that they act in a natural way as observed in real life markets.
The key is setting these fictional bids at a certain level to simulate hot and cold market
bidding behavior. If all of the fictional bids are already known, participants can simply bid a
fraction more to win the auction, which will yield unrealistic results.
1
According to Bureau of Economic Analysis, M&A activity and GDP growth are correlated
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Instead, consider a situation where 1/3 of all bids is known and the rest of the bids are still
uncertain. In such a situation, participants are given a taste of how the market bidding
sentiment is and use this information to construct their own bids.
According to economic theory, a project is worth exactly what its cash flows are, discounted
to the appropriate rate. In other words, the bids of the competitors should not influence the
bid of the participant, as overpaying for a project isn’t in their best interests. Despite of this
economic ‘law’, participants are expected to anchor their bids when observing the fictional
bids of competitors. This is also due to the fact that the actual value of the project is
uncertain, as the horizon value/future prospects are not given so it is impossible for
participants to calculate the fair value of the project.
Another method to simulate a hot/cold deal environment is by communicating a different
bidding scenario. Here, the number of unknown bids is used as a tool to influence the
bidding behavior. The expected effect will be that managers get a ‘now-or-never state of
mind’, corresponding with one of the hot market characteristics also discussed by Smit &
Lovallo. (Smit & Lovallo, 2014)
3.2.3 DEAL OUTCOMES
Another cause for overoptimistic behavior is the so called ‘hot hand fallacy’. Such a situation
consists of a series of positive outcomes, which makes the person in question believe that
they are ‘on a streak’ i.e. that these positive outcomes will keep coming. Not much research
has been done on the hot hand fallacy in a competitive bidding environment but it is not
unlikely that such a phenomenon would occur. Consider the following example.
A manager has to make a bid for a project. After reviewing the currently known competitors’
bids and observing the explicitly modelled cash flows combined with market sentiment, the
manager decides to bid X for the project. However, the real value of the project will only be
revealed ex post to the bidder. In other words, whether or not the bid for the project is
profitable, will be a surprise at the time of the bid. This surprise is comparable with the real
life situation where managers do not know beforehand if a project will be a success or not.
When the outcome of the project is revealed to the winning bidder and this turns out to be
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positive2, it is evident that the bidder is happy with this ‘victory’. Suppose such a situation
happens three times in a row. Now, the bidder has only experienced wins in every situation
where he/she is responsible for. So called hubris comes into play and the manager will
imagine him/herself on a winning streak. This mindset stimulates the manager to keep on
winning bids, inducing higher bids.
An opposite situation arises when the manager is on a so called losing streak. Consecutive
bad results will make the manager more cautious and eventually reluctant of pursuing risky
investments.
By manipulating the outcomes of the project which participants bid for, one can create a
winning streak environment, making the participant believe that he/she cannot lose. In an
analogous manner, a losing streak can be ‘administered’.
3.2.4 RESERVATION PRICE
The reservation price is the minimum bid required for the auction. Due to anchoring, a
different level of this disclosed reservation price should influence the height of the bid. Even
though this reservation price has nothing to do with the actual value of the deal, as this is
determined by the future cash flow.
3.3 The bidding process
After the preliminary questions, the auctions will take place. These will be different in
multiple aspects.
3.3.1 STRUCTURE
First off, the projects for which the participants will bid for are different across the auctions.
The first project will be a simple project with 4 explicit cash flows and a distribution of cash
flows after the explicit period. A reservation price will be set in order to inform the
participants the minimum amount they are required to pay for this project. This can also be
used as a tool to influence the perception of the value of the project in question. It is
expected that this will function through the mechanism of anchoring, as participants will be
using this reservation price as a reference for the actual value of the project.
2
With a positive NPV after deducting the bid for the project
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After this first auction the participants are informed of the outcome of their bid i.e. the NPV
after subtracting their bid. These outcomes may or may not be manipulated to influence the
state of mind of the participant, as illustrated in the previous section.
The second auction will be similar to the first one, in order to test the effect of a positive
outcome versus the effect of a negative outcome. The results of this question should point
out if making a successful/unsuccessful deal influences the next bid.
In the following auctions the effect of options will be tested.
First, an option will be included in the project. This option gives the holder the right but not
the obligation to do a second project with similar characteristics after three years. According
to recent research, it would be logical for hot deal market managers to be more venturing
than a cold deal market manager (Smit & Lovallo, 2014). Analogously, a participant which
has been administered a hot treatment is expected to attach more value to this growth
option than a cold participant. The expand option is formulated in the following way:
“an option to do a follow-up investment to do the project again. This option can be exercised
after 3 years. ”
Such an option would only be valuable in the case of positive market movements. Therefore,
an option like this will not be worth much if you think the market will perform poorly. In the
experiment setting, this should be observable through higher bids among the hot
participants than their cold counterparts.
Another option that will be included is the option to defer. Before bidding for this project,
participants will be told that they have the option to initially buy a 50% stake in the project,
limiting both the up- and downward movements of the project. Then, after one year, they
can either choose to stick with the 50% they own or increase their share to 100%.
Such an option would be valuable to managers which are cautious about future prospects. A
participant which did undergo a cold treatment is expected to be more cautious than
someone with a hot treatment. Therefore, it is likely that the former group will value this
project higher than that the latter group does.
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3.3.2 RATIONALITY, EXPECTATIONS AND MITIGATION
The paragraph above describes the process of bidding in the experiment. At the final part,
(real) options are introduced in the auctions, which causes a somewhat more complex
valuation process.
What participants should do according to their mindset, dependent on their treatment, is
already described above. The ones undergoing a hot treatment are more likely to value the
growth option higher, as the ones undergoing a cold treatment should value the defer
option higher, according to the value scheme of those options.
However, in recent literature, both options put forward as a tool to mitigate the valuation
bias which is entailed by both hot and cold markets. This is illustrated by the following
example.
Suppose as a manager, you are aware of the fact that you’re currently in a hot deal market.
This environment causes high prices in deals and aggressive bidding by competitors. By
doing a deal which has in fact a too high price, the bidders are relying on the market to
thrive even further. Let’s say, for the sake of argument, that after doing this deal, the market
doesn’t perform well. Even more, the market falls in stagnation and cash flows turn out to
be much worse than expected. As winner of the auction, you have now overpaid a
substantial amount when comparing the price to the realized cash flows.
If the manager was more cautious at the time of the auction, he would not be in such a
tedious situation as he is now. A way to allow for more caution when making deals is
through a minority stake. Here, the managers doesn’t acquire the total amount which he
desires, but only a fraction of it, along with the option (but not the obligation) to acquire the
remaining stake of the project. By doing this, the manager has in fact a defer option on the
project, allowing him to wait and see how the market performs and after that, decide
whether he does or does not want to buy the remaining stake.
Even though it may be beneficial to managers to acquire such an option, it isn’t expected to
happen that often. In a hot market, most managers are optimistic about future prospects,
which causes that defer options aren’t really valuable from their point of view (at least less
valuable than growth options). This mismatch between what managers are expected to do,
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given their mindset and what could be beneficial to them, to mitigate potential losses,
causes a paradox.
This paradox also arises when managers are in the exact opposite situation, a cold deal
market. Here, managers are maybe too cautious to bid for projects, resulting in inactive
acquisition behavior. This caution is a result of underestimating growth potential. A way to
introduce a tool to mitigate this underestimation is by using real options.
By looking for both growth and exit options, an initially unprofitable project could turn in
something with great potential. Where expand and growth options are in the money in case
of a positive market ‘swing’, exit options are abandonment options which provide salvage
value in case of negative market conditions.
The above explained paradox especially arises when pessimistic managers are demanding
defer options (due to their expectation of the market), when they really should look for
expand options in order to put more ‘venture’ in their deal valuation.
4. PARTICIPANTS
4.1 Selection
Because of the fact that the questions of this experiment are calibrated on a managerial
environment, the best possible participants would be of course, financial managers. If one
were to research the effects of hot & cold markets, a well-diversified group of managers
should be questioned.
Whenever financial managers are not available to question, a substitute can be students.
Finance students are more available than managers and easier to incentivize by using a
monetary reward. Also, they are a somewhat less occupied group which are expected to
have almost the same theoretical knowledge about finance. Finance students are the closest
one gets to approach the desired target group of financial managers without actually
interviewing financial managers. The difference will be mainly due to practical knowledge, as
real life managers have much more experience in the field of finance than master graduates.
A downside of using students is that the results will no longer be applicable to managerial
decision behavior, as students simply aren’t the same as managers. The up side of using
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students is that the monetary incentive is more of an incentive to students than it is to
managers, as students simply have probably less wealth.
The number of participants questioned should be around 30. This number is based on a
study which examined 119 behavioral studies, along with their number of observations
(Taborsky, 2010). These participants should be chosen accordingly to reflect a realistic image
of a real life managerial environment. A recent US study shows that approximately 50% of all
management positions in the US are occupied by women. Therefore, approximately half of
the participants should be female.
4.2 Monetary incentive
A way to incentivize the participants in really doing their best and acting like the
experimental setup is a real life situation, is through a monetary reward.
This reward will be constructed in way representative of the way managers are rewarded in
a business environment: by using bonuses.
In real life, whenever managers make decisions which turn out profitable for the company
they work for, they obtain a bonus, which compromises a big part of their income3. In other
words, bonuses are important for managers and they have an incentive to do what is best
for their companies.
In the experimental setup, participants will thus be rewarded if and only if they land
profitable deals. This means that bidding for a project too high entails the risk of overpaying
and not receiving any bonus. At the same time, bidding too low for a project can result in not
getting the deal at all, making no profit.
Initially, participants will get a certain amount of points, which is equivalent to a certain
amount of money. Then, when progressing through the experiment, participants are
rewarded (or deducted) points dependent on their performance. As participants will want to
make quick cash, it is logical for them to do their utmost in order to maximize their cash
reward.
3
15-20% for upper management and 30-50% for executives, according to
http://smallbusiness.chron.com/paying-bonuses-instead-salary-increases-34786.html
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By designing the experiment in this way, the participants are now more or less forced to act
like any other manager would, given the fact that they want to maximize their reward.
5. ANALYSIS
5.1 Main results
After the experiment has been conducted, the results can now be analyzed. The main
variable which will be analyzed is the variable [Bx,p], corresponding with the bid on question
x by participant p. Analysis of these bids will be conducted through statistical software4, to
see whether there is variation in the data, and if so, where this variation occurs. The
population will be splitted in 3 categories: hot market treatment (Th), cold market treatment
(Tc) and neutral market treatment (Tn).
First, a quick summary of the outcomes by participant p:
B1,p
is the first bid without any interference. This will serve as benchmark
B2,p
is the second bid, after the first round of bidding has been completed. Here, the
outcomes of the previous auction are expected to influence the mindset of the bidder. This
bid will be compared with bids of other participants, where the outcome of the previous
auction will be used to define the different treatments. Also, the bids of B2,p can be
compared to the benchmark B1,p if and only if the project in B2,p is similar to the project in
B1,p.
B3,p
is the third bid, a situation analog to the second auction, only now with the addition
of the real option ‘expand’. A bidder with a favorable outcome in B1,p and B2,p is expected
to value B3,p higher when compared to the valuations of bidders with unfavorable outcomes
of the previous auctions.
B4,p
is the fourth bid, a situation analog to the second auction, only now with the addition
of the real option ‘defer’. A bidder with unfavorable outcomes in B1,p and B2,p is expected
to value B4,p higher when compared to the valuations of bidders with favorable outcomes of
the previous auctions.
4
Eviews
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After all the values of Bx,p are known, these results can be compared with one another. The
causality looked for is the effect of a certain treatment [Tx] on a certain bid [Bx,p]. The
expectation is that a ‘hotter’ treatment entails higher overall bids in B2,p and B3,p, whereas
a ‘colder’ treatment is expected to entail a higher bid in B4,p.
Mathematically:
[B{2,3},p | Th] >
[B{2,3},p | Tn] >
[B{2,3},p | Tc]
[B{4},p | Th] <
[B{4},p | Tn] <
[B{4},p | Tc]
5.2 Further specification
After the main variables have been analyzed, the option to analyze the participants on a
personal level is available. Because of the preliminary questions, there is now a set of
information available about each individual, which can be used to explain variation in the
bids which isn’t covered by the variation in treatments.
Examples of individual differentiation are demographics like gender and age, but also
degrees of optimism5 and the opinion about what managerial skills are most important. Also,
the degree of loss aversion is measured by a simple question about a gamble, involving both
a potential loss and potential gain.
6. CONCLUSION
In this study, possible ways to research valuation biases has been discussed. First off, it is
really important to understand which effect you’re investigating. As shown in the ‘Analysis’
section, the key relation here is between the treatment and the valuation, with treatments
being experimental settings which are based on hot/cold/neutral deal markets.
The way to measure the valuation bias, caused by the treatment, one should divide a
population in three segments, using the treatments, and observe the difference in valuation.
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Here, over optimism occurs when a participant rank him/herself consequently high on most ‘managerial
qualities’
17
Three ways to ‘administer’ a treatment to a participant are discussed in this study, along
with their relation to the real hot and cold deal markets.
The bidding process is then established in such a way that it allows for the analysis of the
different bids, in order to observe the variation in the valuations of participants.
Also, the expected outcomes along with their rationale are discussed, which seem to be
contradictory with the ways to mitigate the valuation biases. These expectations are
mathematically expressed in the ‘Analysis section’.
The selection of participants is of major importance, because of the fact that this will have
great consequences to the external validity of the results found in the experiment.
7. ACTUAL EXPERIMENT
An example of an experiment, drafted according to the suggestions done in this study, can
be found in the appendix.
8. LIMITATIONS
Two limitations of the experiment designed are related to the participants. Firstly, whenever
managers are not available and one is dependent on finance master students, the results are
far less significant as it isn’t possible to draw conclusions about managers using students.
Secondly, the proposed sample size might prove insufficient to use in statistical analysis.
According to literature, sample sizes should be bigger. The law of large numbers indicates
that more observations leads to more accurate values of the actual population, being
graduates or managers (dependent on type of participants) (Moore et al., 2009).
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9. APPENDIX
9.1 Example experiment
Note: everything between [brackets] will not be disclosed to participants.
Description
Your (wealth) starts at 500 points to begin with and changes in your points total as results of
the gains and losses from the projects. At the end, the points will be translated into a
monetary reward. You have to make a decision regarding investments under uncertainty.
After the auction of each project uncertainty resolves and the real outcome will be disclosed
to the bidders. In case of winning the bid, the NPV is added/subtracted from the point
amount of the bidder.
Preliminary Questions
In this part of the experiment, you will have to answer some personal questions.
In the following there will be references to ‘the other participants’. The other participants are economic
students from Bachelor-3 or an economic Master.
What is your gender?
Male
Female
What is your age?
Head or tails question: 250 points for heads. -100 points for tails. How much money do you require in
order to not do this gamble?
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Question
Well below
Below
average
average
Average
Above
Well above
Average
average
Relative to the other participants, how would you
rate your IQ?
Relative to the other participants, how would you
rate your perseverance?
Relative to the other participants, how would you
rate your ability for analytical thinking?
Relative to the other participants, how would you
rate your social skills?
Relative
to
the
other
participants,
how
independent do you think you are?
Relative
to
the
other
participants,
how
performance-oriented do you think you are?
Relative to the other participants, how emphatic
do you think you are?
Relative to the other participants, how creative do
you think you are?
Relative to the other participants, how confident
do you think you are?
Relative to the other participants, how do you rate
your willingness to accept risk?
Which of the following qualities do you think a good manager should have? (More answers possible!)
Check
Intelligence
Perseverance
Social skills
Independency
Creativity
Confidence
Analytical thinking
Empathy
Orientation on good performance
Willingness to take risk
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Question 1:
What would you bid for a project with the following cash flows and uncertain horizon value:
T=
1
2
3
4
10
15
13
19
horizon value
Where future horizon value (after t=4) are distributed with an interval of (-50, 300). The
exact distribution is not disclosed.
The minimum bid is 20 [for neutral, 15 for cold and 25 for hot] which is the reservation price.
Discount rate is 0%.
Question 2:
The last project you’ve invested in turned out to be a failure/success. Due to the outcome of
the last project, your financial position has worsened/improved by 200 points. Now it is your
turn to make a decision regarding the following projects.
What would you bid for a project with the following cash flows:
T=
1
2
3
10
15
13
horizon value
Where future cash flows (after t=3) are distributed with an interval of (-50, 300).
The minimum bid is 20 [for neutral, 15 for cold and 25 for hot] which is the reservation price.
Discount rate is 0%.
You are bidding for this project along with 5 [for neutral, 8 for hot, 3 for cold] other
managers. Two of the bids are respectively 160 and 180 [for the neutral treatment, 200 /
220 for hot and 100 / 120 for cold]. The highest bidder receives the present value of the
project. When the investment (bid) is subtracted from the present value, the net present
value is calculated. In case of losing the bid, nothing happens.
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Question 3:
Consider an analog situation as described above, now with an option to do a follow-up
investment to do the project again. This option can be exercised after 3 years.
Similar as above, the winner of the auction receives the present value of the project and the
loser will receive nothing. Additionally, the winner can decide after 3 years to do the second
project if they exercise the option. The cash flows of this project are distributed in the same
way as the initial project after t=3, so with an interval of [-50, 300], which will be known by
then.
Question 4:
Consider a project with similar prospects as above. You can buy a 50% stake in the project,
with the option to wait and either buy the other 50% of the project or just stick to the 50%
you already own. This option can be exercised one year from now, when more information is
available about the cash flows after t=3.
Again, the winner of the auction receives the present value.
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