Emotions and decision making

discussion on the interdependency between affect and cognition).⁹ Oatley and Jenkins (1996) divide emotions into basic categories, underlining the fact that they can be both conscious and unconscious.¹⁰ Finally, Loewenstein and Lerner (2003) rely on the moment when emotions are experienced in order to distinguish between expected and immediate emotions.¹¹

However, psychologists and neurobiologists are the first to recognize the fact that, desirable or not, emotions always impact on human decisions. Thus, emotions are de-scribed as “the very center of human mental life” (Oatley and Jenkins (1996), p. 122) and regarded as our link to the outside world.

In this framework, emotions are proved to show both disruptive (i.e. negative) and functional (i.e. positive) effects on decision making. According to Damasio (1996) and Frijda, Manstead, and Bem (2000b), thenegative effectsoccur for example when emotions have no object and can be misattributed to false causes, entailing biases against objective facts or interfering with working memory. Loewenstein and Lerner (2003) mention several main reasons for such negative effects: First, emotions that have evolved to solve certain decision problems may be incompatible with the current environment; Second, the emo-tions experienced at the time of decision making (the immediate emoemo-tions) are extremely sensitive to non-normative guiding factors of behavior and also distort evaluations of the probability and value of choice alternatives. In the same spirit, Simon (1967) observes that emotions may become disruptive when the triggering stimuli are intense and persistent, and repeatedly interrupt and hence prevent an organized behavioral response.¹⁶

The more recent perspective over emotions has however changed. (See Elster (1999).) Damasio (1996) suggests that emotions turn intosuitable decision toolswhen the quality of decisions is measured by the survival in a given environment. The main reason is that, as underlined in Oatley and Jenkins (1996), emotions serve to focus on certain events and to discard irrelevant decisions alternatives. Since deciding well means very often – especially under time pressure, uncertainty, and limited resources – deciding fast and well enough, emotions represent survival-oriented (i.e. adaptive) instruments developed in the course of our biological evolution. As emphasized in Elster (2003), emotions improve decision making in twofold respect: first by avoiding the delay of (vital) decisions. In other words, emotions help us to make some decision; And second by improving the decision quality that could be achieved exclusively by rational deliberation.

Numerous recent studies detail the motivation and implications of emotions as bene-ficial decision making tools. We commence by supporting evidence from psychology and neurobiology. This evidence serves the purpose of better understanding the psychophys-iological mechanisms of emotions, and hence the origins and the manifestations of their

16He also notes that emotional behavior can be learned. This can both enhance and reduce the

“emotionality” of responses, the former when occuring emotions stop the process of fulfilling real-time needs and the latter by adaptive improvement of the reaction programs.

positive features. Also, it helps to better define the relation between emotions and ratio-nality.

In this context, the somatic markers hypothesisof Damasio (1996) is one of the main theories meant to explain how emotions occur, to which extent they imply the body and/or the brain, and which is the valence of their impact on decision making. Somatic markers are defined as instances of feelings connected – by learning and experience accumulated during education and socialization – to secondary emotions. Their function is to “label”

decision alternatives as favorable or dangerous.¹⁷ A first general consequence of this la-belling is underlined in Slovic, Finucane, Peters, and MacGregor (2002): Since they mark the mental representations of reality (as positive or negative), somatic markers – hence emotions – direct the decision making. Second, Damasio (1996) argues that the choice alternatives marked as dangerous are automatically eliminated. Thus, somatic markers provide for reducing the number of choice options and hence forfastening decisions. This is a crucial feature in particular in dynamic environments and/or when decisions need to be made under time pressure, as it is the case on financial markets. Slovic, Finucane, Peters, and MacGregor (2002) stress as well that, in spite of the importance of the delib-eration in certain decision making situations, affect and emotions provide a faster, easier, and more efficient way to cope with the environmental complexity and uncertainty.¹⁸ The somatic markers hypothesis explains in detail a fact apparent from the definition but with important implications for decision making: Emotions can be rooted in both the body andthe brain. The usual inducers of emotions are representations of objects or situations that can come either from theoutside world and elicit bodily reactions or from inside of the organism, being entirely triggered in the brain. Consequently, emotional reactions do not necessarily respond to real stimuli, in which case they are even faster and may be more difficult to control.¹⁹ We can thus conclude that emotions play an adaptive – hence necessary and positive – role in decision making.

The beneficial aspects of emotions for decision making can be further motivated in

17In other words, somatic markers provide criteria for ranking the choice alternatives.

18They even speak about an “affective rationality”, as the optimal behavior may be achieved by means of the affect.

19Damasio (1996) offers more details on the functioning of somatic markers. They are mainly experi-enced as bodily responses to external stimuli and many feelings stem indeed from changes of the bodily state. This mechanism is denoted as thebody loop. However, our brains appear to have evolved in order to minimize the reaction time and the energy consumption during the response to certain stimuli. Certain neural devices, that help us to feel “as if” bodily changes would occur, have been developed. The trigger signals are now entirely processed by the brain and do not necessitate the intervention of the body. This corresponds to the so-calledas-if loop. Of course, the core condition for such “bypass devices” to start functioning is that the process implying actual bodily reactions had run at least once.

view of the relation between rationality and emotions. It is not possible to draw a clear separation line between these phenomena, either with respect to their development at physiological level or to their impact on decision making. In effect, the mechanism of behavior is based on the interaction of rational and emotional processes. Yet, as all cognitive processes not only rely on emotions but are also framed by them, “emotions may be an indispensable foundation for rationality” (Damasio (1996), p. 164). In particular, since emotions are indissolubly related to the body (see the definition in Section 2.1.1), they guide all posterior mental processes, hence all cognitive processes which are slower and arise subsequently. Moreover, emotions themselves require the intermediation of both the brain core (viewed as the center of affect) and the cortex (viewed as the center of cognition).²⁰ Furthermore, Frijda, Manstead, and Bem (2000b) consider that beliefs – hence cognition – are not sufficient to initiate action, they need the support of emotional impulses. Accordingly, “emotions can awaken, intrude into, and shape beliefs [...]” (p. 5).

This occurs in that emotions can either create new beliefs or change the strength of existent ones (i.e. amplify or alter them, and/or increase their resistance to change).²¹ In essence, emotions appear to guide cognition.²² Damasio (1996) explains that somatic markers boost the other two supporting mechanisms of reasoning, i.e. the attention and the working memory, throughout the cognitive system.²³ This idea is reinforced by Oatley and Jenkins (1996), who argue that emotions have two main cognitive properties. The first is the management of action and is intermediated by the so-called informational signals carried by emotions. These signals carry information about events that caused the emotion and commands to specific destinations. Thus, emotions change the readiness to act. The second cognitive function of emotions is to set the cognitive system into distinct modes of organization. This is achieved through specific signals that control brain organization but have no informational content. The effects of this brain structuring are to modify perception, to direct attention, to give preferential access to certain memories, and to bias thinking. Thus, emotions guide the cognitive search for possible plans. Note that

20On the one hand, emotions can be characterized as concrete, cognitive and neural. On the other hand, although rational processes occur in the newest part of the human brain, i.e. the neocortex, rationality actually implies the collaboration of neocortical and subcortical regions. It is intrinsically related to the biological regulation that occurs in the older brain areas, such as the brain stem and the limbic system that is the center of emotions.

21In addition, Frijda and Mesquita (2000) argue that emotions include the formation of beliefs and stimulate their elaboration.

22Or, as stressed in Loewenstein and Lerner (2003), emotions serve an essential function in coordinating cognition and behavior.

23This claim is equivalent to the assertion in Frijda, Manstead, and Bem (2000b) that emotions provide information and guide attention.

control signals may be accompanied by informational ones (which gives rise to feelings), but although this is often the case, it is not absolutely necessary.²⁴

In the same context of the necessary and positive contribution of emotions to deci-sion making, researchers have also focused on economical aspects, such as the decideci-sion optimality measured in terms of opportunity costs. They show that pure rationality is merely a theoretical abstraction and emotions can foster decision optimality in practical situations. As already emphasized in Simon (1967), the human knowledge and informa-tion processing capacities are limited. These limitainforma-tions turn into constraints for real decision problems and make a fully rational search through all possible alternatives – as self-evident according to the traditional economic theory of rational agents – virtually impossible. In practice, the search for the best decision alternative stops either when the goal has been achieved, or when a certain amount of time has elapsed, or, in the majority of cases, at a partial solution that is found to be satisfactory. The latter is denoted in Simon (1967) assatisficing.²⁵

Search and stopping rules are assessed in real life by means of “shortcut rules” called heuristics.²⁶ As already mentioned, the heuristics-and-biases program of Kahneman and Tversky develops this idea focussing on cognitive heuristics and on their negative impact on decision making. In contrast, Gigerenzer, Todd, and the ABC research group (eds.) (1999) introduce the concept offast and frugal heuristics. As models of bounded rational-ity, they are meant to replace the theoretical idealization of decision making referred to as unbounded rationality. Accordingly, fast and frugal heuristics guide search in twofold man-ner: First, they define easily computable stopping rules and hence constitute one possible form of satisficing. Second, they provide facile decision rules, that represent a trade-off between generality and specificity. The fast and frugal heuristics are consequently rules of thumb that can lead to accurate and useful decisions. They are considered to be a part of the set of specialized cognitive mechanisms developed in the course of the human evo-lution that are shaped to cope with the environmental challenges.²⁷ Moreover, fast and frugal heuristics perform well when their structure is adapted to the environment.²⁸ As

24This occurs for instance in case of free-floating emotions.

25For a more detailed description of satisficing, see Simon (1982).

26According to the Merriam-Webster dictionary at www.merriam-webster.com, the term “heuristic”

comes from the Greek “heuriskein” and means “to discover”.

27This set is denoted by Gigerenzer and Todd (1999) as the “adaptive toolbox”. For more details hereon and on the fast-and-frugal heuristics program see Gigerenzer and Selten (1999).

28Gigerenzer and Todd (1999) denote such a situation as “ecological rationality”. Fast and frugal heuristics are ecologically rational in environments with noncompensatory information, scarce informa-tion, T-shaped distributions, or decreasing populations. Moreover, fast and frugal heuristics are

consid-they consist of a small set of simple rules, fast and frugal heuristics are mostly robust to environmental changes.²⁹ Beside cognitive heuristics, emotions are considered to belong to this type of heuristic principles. As Slovic, Finucane, Peters, and MacGregor (2002) mention, rationality of decisions should rather be understood in terms of “deciding in the best interests”. Since interests depend on individual and environmental constraints, heuristics – in particular, emotions – ensure adaption and can provide the best solution to the constrained decision problems addressed above.

Moreover, Oatley and Jenkins (1996) recall two further reasons that can additionally impede full rationality: First, the same individual usually envisages multiple and often contradictory goals. Second, the achievement of these goals mostly involves other people and hence the coordination of their own and others’ actions. Since emotions provide guid-ance in such ambiguous and complex situations, they become necessary forcomplementing reasoning.³⁰ In essence, emotions serve asjudgment and decision making heuristics, espe-cially when the analyzed situation is complex and the mental resources limited (see Slovic, Finucane, Peters, and MacGregor (2002)). They provide for the ability of deciding when the corresponding rational decision faculty cannot act (at full power) given the internal and external constraints. Thus, they supplement and enhance rationality, as argued in Elster (2003).

The two different views of heuristics as biases (Kahneman and Tversky) and as adap-tive tools (Gigerenzer and colleagues) are reconciliated in Gilovich, Griffin, and Kahneman (2002). The simultaneous occurrence of positive and negative effects of emotions on deci-sion making can be accordingly explained in terms ofdual processes. These processes also shed a new light on the controversy regarding rationality and emotions and complete the explanations given above. According to Kahneman and Frederick (2002), two systems for judgment and choice operate in parallel and interact in generating final human behav-iors.³¹ They can be described following Sloman (2002), Stanovich and West (2002), and Slovic, Finucane, Peters, and MacGregor (2002). Thus, System 1(also called the associa-tive or theexperiential system) relies on temporal and similarity relations, in one word on perception (or intuition). It maps the reality into images with affective load. Moreover,

ered as “socially rational”, i.e. they guide behavior in fast changing environments, where decisions have to be coordinated with other individuals.

29The main classes of fast and frugal heuristics studied in Gigerenzer and Todd (1999) are ignorance-based heuristics, one-reason decision making, elimination heuristics, and satisficing heuristics.

30Oatley and Jenkins (1996), argue that this guidance especially concerns our social relations. It is the result of making available a set of action alternatives already stored in the brain.

31See also Kahneman (2003) for an overview over the two-system model.

it mostly involves automatic (thus fast), heuristic-based, spontaneous, intuitive, and ef-fortless processes and entails highly contextualized, personalized, and socialized inferences and predictions. In contrast,System 2(also therule-basedor therational system) is based on a set of abstract variables and rules of logic and evidence. It is deliberative, effortful, slow, analytical, and strategic. Put in a different way, it acts in accordance withreason(or knowledge). It mainly involves controlled (thus slow) processes and yields more general mental representations. The interaction of these two systems complies with the principle ofcollaboration, yet their responses may strongly diverge from each other. In such cases, System 1 features primacy, since its automatic response is faster and effortless, while System 2controls– and can overrule – the associative reaction. Also, the two systems are intrinsically related and support each other. For instance, rule-based reasoning is needed to develop associative structures, whereas associative reasoning becomes necessary when rules are inaccessible – such as in new situations or environments – and is helpful when knowledge has been already integrated in our mental landscape.

Lo (2004) develops these ideas even further in his adaptive markets hypothesis. This hypothesis attempts to reconciliate market efficiency with behavioral evidence that has been originally interpreted as a counterexample of rationality and thus of efficiency. The adaptive markets hypothesis builds on evolutionary principles, stressing that individuals act in self-interest, make mistakes, learn and adapt. Thus, their behavior is not necessarily intrinsic and exogenous, but evolves by natural selection and depends on the particular environment in which the selection occurs. In this context, individuals are organisms that attempt to maximize the survival of their genetic material (in other words, of their species). In financial markets, survival of the fittest becomes survival of the richest. The sole objective and the organizing principle of markets is survival, while the maximization of profits, utility, etc. remains just an aspect of market ecology. Survival is reached through satisficing, and stopping rules are determined through trial and error. This implies that choices rely on past experience and best guesses of the optimum, and learning occurs by receiving positive/negative reinforcement from the choice outcomes. Moreover, decision rules (e.g. trading or investment strategies) consist of heuristics that provide the best adaptation to the environment. Naturally, as the environment changes, the heuristics employed might not be suitable anymore, so they entail “irrational” behavior. Therefore, strategies follow cycles of profitability and loss in response to the variation of the market

conditions.³²