33
sing volatility in the markets (
Over/Under Re-
action Theory
).
Herding Theory (Group Behaviour)
describes
investors´ behaviour to give up individual decis-
ions in favour of group opinions. It really asses-
ses the correlation in trading patterns for a par-
ticular group of market participants and their
tendencies to follow leadership recommenda-
tions. Group Behaviour is characterized by in-
ternal discussions and final voting procedures.
Implicitly however, the group opinion is syste-
matically influenced by in-official group leaders
leading the herd.
Behavioural Controlling and
Accounting
Internal Behavioural Accounting mainly focuses
on instruments of incentives and control. The
theoretical bases is given by the principal agent
theory, game theory and motivation theory and
therein represent an asymmetrically biased
preference and utility function model under
uncertainty as described with the Prospect
Theory of Kahneman and Tversky. Fields of ap-
plication of internal behavioural accounting are
bonus related compensation plans
for the
management as well as
participation budge-
ting processes
. Applied instruments of incen-
tives and control are mainly target costing,
hurdle rates, zero based budgeting. Therefore,
the application of full cost versus variable cost
calculation systems lead to different key corpo-
rate earning figures like Economic Value Added
(EVA) or Weighted Average Cost of Capital
(WACC). The bonus related compensation
scheme for management and key personal in-
fluences the level of risk exposure the manage-
ment is prepared to take into account and thus
determines the volatility and sustainability of
earnings and profit margins. A conservative and
sound compliance regime should limit bonus
payments and stock option plans in order to
avoid basic insolvency risks.
A key benchmark of performance measure-
ment is the Economic Value Added (EVA) that
contains the shareholder´s target of the equity
capital based surplus yield for taking entrepre-
neurial risks and as compensation for entrepre-
The
Regret Theory
deals with emotional re-
actions of investors after realizing that they
have made an error in their evaluation and de-
cision. They tend to stick onto their positions
and/or prefer to take higher risks in order to
correct their decision. This behaviour of regret
avoidance is called inertia. An instrument to
overcome inertia is to apply an autopilot sys-
tem that is “automatically” correcting and ad-
justing an investment strategy. In the past,
high commission rates fostered inertia and
prevented investors from re-balancing their
decisions and portfolios. Nowadays, internet
online banking – amongst others – has lead to
marginal low commission rates. Private inves-
tors have no longer reasonable transaction
cost disadvantages in comparison with institu-
tional investors.
People basically rate themselves as being bet-
ter than the average and therefore overestima-
te their expertise and knowledge leading to un-
derestimate future risks (
Theory of Overconfi-
dence
). This is, because market developments
are affected by multi causal and complex fac-
tors and parameters and therefore require de-
tailed analytical skills that non professional in-
vestors do not have. This often leads to funda-
mental wrong decision and effects of over-tra-
ding activities.
Loss Aversion
theory assumes that investors
seek the highest return for the level of risk they
are willing and able to bear. Hence, they are
more sensitive to losses than to returns and
basic risk. This leads to an asymmetric risk re-
turn function (bias). Furthermore, investors
tend to a so called “disposition effect”, be-
cause they tend to sell winners and stick on lo-
sers in order to avoid realizing losses. This of-
ten leads to a systematic underperformance in
relationship to key market indices like stock
market indices (e.g. DAX 30, S&P, Dow Jones,
Nasdaq Composite).
Investors get optimistic when markets recover.
On the contrary, they become extremely pessi-
mistic in crisis situations. As a consequence of
anchoring, placing too much importance on re-
cent events while ignoring historical and funda-
mental data. The result is an under/over reac-
tion on market developments leading to increa-
Decisions can be anchored by the way informa-
tion is presented to investors (
Anchoring
).
Stock market indices provide chart technique
based peaks, inflexion points and other techni-
cal markets signs. Investors refer to these figu-
res and make their buying and selling strategy
dependent to such market data. Herein, re-
cently observed or experienced data or events
dominate investment decisions. This is as well
referred as
Availability Bias
.
The
Coherent (Efficient) Market Hypothe-
sis
(CMH) by Eugene Fama is a non linear dy-
namic economic model for non-perfect, non-
arbitrary capital market experience, estima-
ting probability density functions for future
market price movements. In this situation the
CMH tries to prognosticate future equity yields
by the parameters of market fundamentals
and by patterns of investor group behaviour. It
states that market movements may be predic-
ted by certain broad limits, depending on a
combination of investor sentiment and funda-
mental bias. The model assumes that all fun-
damental capital market and asset class rela-
ted information and data is available to all
groups of investors and market participants
without restrictions. It herewith assumes ef-
ficient market conditions differing between
low efficiency, medium efficiency and strong
efficiency:
➡
➡
Low efficiency: Historical data are not a va-
lid input to prognosticate future market pri-
ces. Technical analysis therefore does not
provide an information advantage.
➡
➡
Medium efficiency: It is assumed that in ad-
dition to low efficiency all publicly known,
relevant information is already priced in by
the market.
➡
➡
Strong efficiency: Insider information is as
well priced in by the market. This assumpti-
on is mostly unrealistic.
Practical experience however disproved the Co-
herent (Efficient) Market Hypothesis. The theo-
ry assumes that markets pass the four phases
random walk, unstable transition, chaos and
coherence. The model attempts to curb the
perceived overstatements of random walk and
the efficient market theory.
CM März / April 2019
