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Erschienen in:

2013 | OriginalPaper | Buchkapitel

3. The Mind Process

verfasst von : Yasmine Hayek Kobeissi

Erschienen in: Multifractal Financial Markets

Verlag: Springer New York

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Abstract

The sense of time and financial players’ behavior is the central theme of this chapter. The notion of “intrinsic time”, a dimensionless time scale that counts the number of trading opportunities that occur regardless of the calendar time that passes between them, is explained to highlight the difference in investors’ perceptions and how to use this fact as a tool in understanding the processes at play and the biases to identify and avoid. As new information is constantly entering the market financial participants need to revise their expectations according to their own utility perception. As such the study of utility is important to understand the financial marketplace. The key element in any information content is the surprise element. Surprise is experienced only if an unexpected outcome occurs from which a new or different utility per individual is derived. Bearing in mind that information is a decreasing function of probability, we introduce an innovative subjective utility theory as per the findings of Viole and Nawrocki: the “Multiple Heterogeneous Benchmark Utility Functions”. Bayes’ theorem and fuzzy logic that has found application in many contexts are presented as a device to effectively account for “probabilities” in the decision-making process under conditions of uncertainty.

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Vorheriges Kapitel The “Noisy Chaos” Hypothesis

Nächstes Kapitel Macrostates Indicators

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…your amygdala acts as an emergency control center that gets all the other parts of the brain to quit mucking around with their daily tasks and concentrate all the resources on the one, main thing that is happening. It is like being an athlete or performer “in the zone”. When something threatens your life, this area seems to kick into overdrive, recording every last detail of the experience Eagleman (p. 31).

It is not the intuition as defined by Behaviorist like Kahneman interested in the biases of quick guesses.

Researchers are only beginning to investigate these topics and it is unclear which, if any, of these factors will prove to be important. The relationship between the amygdala and the hippocampus might be bi-directional during the encoding of emotional events. Researchers are just starting to explore more complex interactions between emotion and memory that could be unique to human function (Phelps 2004, pp. 198–202).

The amygdala plays a crucial part in facilitating the link between attention and emotion thus enhancing our memory. For instance, marketing professionals bring into use strategies to trigger attention and curiosity about the uncertainty of what will be said. As a result, the audience's senses will focus on the broadcast commercial/or billboard, and what will be said will not be forgotten easily.

According to Libet (2004), “We are not conscious of the actual moment of the present. We are always a little late”.

According to Damasio (2002), this lag is actually 120 ms.

James Bernoulli (1713) developed the law of large numbers: the difference between the probability of an event and the frequency of an event become arbitrarily close to zero as the number of attempts approaches infinity. This means that the ratio of heads to tails will become closer to one after a vast number of flips, not that tails will become more likely after a series of heads. A tail is not more likely on the next flip just because you have just thrown 15 straight heads; the probability of getting another tail is still 50 %.

except during the month of December in the U.S., for tax reasons.

For the decision maker, each additional monetary unit gained or lost is worth less than the previously gained or lost monetary unit (Kahneman and Tversky 1992).

High volume stocks are generally glamour stocks and low volume stocks are generally value or neglected stocks, (Lee and Swaminathan 2000).

In 1952 Shackle (GLS 1952) advanced that an occurrence with low probability contains more surprise than an occurrence with a high probability with the amount of surprise measuring the risk of the investment. As such information is a decreasing function of the probability. So, if there are different weights of outcomes (potential surprise), then there will be a potential surprise function. The potential surprise function of Shackle is analogous to the weighted entropy measure derived by Guiasu (Guiasu 1977). Bill Harding and N proposed a state-value weighted entropy value 25 years ago because entropy as a statistical measure does not take into account the values of the microstates (Nawrocki and Harding 1986). Weighted entropy in comparison is more adequate the economic and financial context as a measure of portfolio risk, because the structure of the dispersion contained in the frequency classes is not ignored.

\( \ {\text{Hw}} = - \sum\nolimits_{{i = 1}}^{n} {{\text{Xi}}\,{\text{pi}}\:{\text{loge}}\:{\text{pi}}} \)
Where Hw is the weighted entropy,
Xi is the monetary payoff or return,
n is the number of outcomes, and
pi is the a priori probability of the outcome I.

According to the Expected Utility Theory (EUT) the decision maker chooses between risky or uncertain prospects by comparing their expected utility values, i.e., the weighted sums obtained by adding the utility values of outcomes multiplied by their respective probabilities. The cumulative prospect theory of Kahneman and Tversky’s (Kahneman and Tversky 1992) is a descriptive theory of decision behavior where weights are applied to the cumulative probability distribution function and relative value is assigned to each outcome. In this theory, the concept of “utility” is replaced with the concept of “value”. The reference points become the net gains and losses instead of net wealth. The prospect theory is characterized by a value function that is concave for gains, convex for losses, and steeper for losses than gains.

…The less wealthy is typically guided by the concavity of the total wealth function for local choices, as they are furthest from their PCS level (Viole and Nawrocki 2012).

…When wealth increases and the PCS level is eclipsed the Wealthy enjoy a convex utility or economies of scale for additional resources. The migration of positioning explains the non-stationarity of loss-aversion as the marginal dollar gained is larger than the marginal dollar lost for the Wealthy. Again, the total subjective wealth influences the change in wealth of the decision; neither is exclusive per EUT and PT (Viole and Nawrocki 2012).

The house money effect introduced by Thaler and Johnson (1990) predicts investors will be more likely to purchase risky stocks after closing out a profitable trade. It is an example of mental accounting, whereby agents consider large or unexpected wealth gains to be distinct from the rest of their wealth, thus they are more willing to gamble with such gains than they ordinarily would be.

Keynes described the positive feedback loop between professionals and the general public in his well-known metaphor about a beauty contest in which he compared the stock market with the competition between American newspapers where each competitor tries to select the photo they think would appeal to the average America: “The question is not to choose, according to your own opinion, the photos that are actually the prettiest, nor to select the one that the average American would consider the prettiest. We have reached here the third degree where we consecrate our intelligence to anticipating what the general public thinks to be the opinion of the general public” (Keynes 1936, p. 156).

An example is Goldman Sachs chief market strategist Abby Cohen’s cautionary warnings on 28 March 2000.

Titel: The Mind Process
verfasst von: Yasmine Hayek Kobeissi
Verlag: Springer New York
Buch: Multifractal Financial Markets
Print ISBN: 978-1-4614-4489-3

Electronic ISBN: 978-1-4614-4490-9

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-1-4614-4490-9_3