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The Mind Process

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Multifractal Financial Markets

Part of the book series: SpringerBriefs in Finance ((BRIEFSFINANCE))

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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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Notes

  1. 1.

    …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).

  2. 2.

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

  3. 3.

    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).

  4. 4.

    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.

  5. 5.

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

  6. 6.

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

  7. 7.

    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 %.

  8. 8.

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

  9. 9.

    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).

  10. 10.

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

  11. 11.

    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.

  12. 12.

    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.

  13. 13.

    …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).

  14. 14.

    …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).

  15. 15.

    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.

  16. 16.

    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).

  17. 17.

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

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Correspondence to Yasmine Hayek Kobeissi .

Appendix A: NASDAQ100 (2000–2001)

Appendix A: NASDAQ100 (2000–2001)

In this section, we analyze the behavior of investors from 19 October 1999–12 January 2001, to demonstrate the biases in the markets, using the Nasdaq 100 (NDX100) and the S&P500 volatility index (VIX). Figure 3.3 illustrates the movement of these two indices during the period of our analysis in three phases: euphoria, transition, and bear market.

Fig. 3.3
figure 4

The NASDAQ 100 Index from 19 October, 1999–12, January, 2001. (Data Source Bloomberg)

Euphoria

The collective myopia observed during this phase was a logical consequence of individual investors’ irrational behavior where more importance is given to information that satisfies their desire for maximum profits.

During the accumulation phase (19 October, 1999–3 January, 2000), prices started to increase progressively, influencing the perception of market players, leading to widespread optimism. The NDX100 rocketed from 2,362 points to 3,790 points, an increase of 60.45 % in only 53 working days. Everything in the environment was functioning in favor of sustainable growth as evidenced by high liquidity, favorable forecasts for companies, and prospects for economic growth combined with limited t inflationary pressures. The increase observed during this phase was accentuated by investors ready to repurchase the shares they had sold at lower prices as soon as there was a market correction. No one wanted to or could afford to miss the market rise. Trading in the market became a social trend, a fashion, allowing individuals to show off their wealth, and prove their skills. Thereby they were easily induced into the leverage buildup cycle.

The period between 4 January 2000 and 10 March, 2000, was marked by technical corrections and lots of speculation but overconfident behavior reinforced the bullish trend. Throughout January 2000, the NDX100 oscillated between 3,790 and 3,446 points, a fairly reasonable difference of 344 points or 9 %, owing to investors’ profit-taking. Investors created mental accounts, closing profitable positions and leaving open losing ones. Their unrealized losses were only considered an accounting loss or “paper loss” as long as they were not forced to realize them, such as in the case of a margin call.

On February 2 2000, the Federal authorities increased the rates by 25 basis points (bps) instead of the expected 50 bps, thus reinforcing the positive bias. Markets soared and on March 10, the NDX100 reached 4,587 points, an increase of 33 % in only 28 days. Investors became even more overconfident and increased their investments through leveraging. In fact, decisions were biased by the information selected to fit their thoughts and justify their behavior, otherwise known as anchoring behavior. Investors ignored cautionary calls by analysts who foresaw possibilities of market deterioration because of their desire for rapid gains and fear of missing a market upturn. They continued to leverage their positions, consequently amplifying the difference between market prices and fundamental values.

During periods of euphoria, the sensitivity of market players to media is incredibly high; an example of this phenomenon is illustrated by the so-called “Media effect”. Trading rooms are often tuned into financial media channels, where traders listen to the opinions of analysts. While TV channels may not be the best source of information, it is the most accessible to the trading public. Price fluctuations accompanied by the recommendations of financial journalists, increase (or decrease) the number of stock market transactions exponentially. It is thus useful for professionals to study how media influences the general public in their decision making.Footnote 16 The Media effect takes place when investors follow market tidbits or snippets of information. This effect is especially pronounced in periods of market excitement during which the categories of investors are quite diverse, ranging from large fund managers and professional investors, to nonprofessional investors and retired individuals. The following is a non-exhaustive list of psychological mechanisms by which journalists, intentionally or unintentionally influence their audience:

  • Financial journalists identify with certain social groups and as such, they are more likely to influence those groups. For instance, by writing an optimistic article during a bullish phase, journalists influence their readers to increase their investments. Tvede (2002, pp. 191–192) explains this effect using a medical example test.

    Imagine you are presented with the following medical outcomes:

    • Outcome One: 200 people out of 600 will be saved whatever option is selected.

    • Outcome Two: 400 people out of 600 will die whatever option is selected.

    The result of the test is that when people are presented with the first outcome, they choose an option; but, when presented with the second outcome, they fail to make a choice.

  • Journalists often ignore criticism that calls into question their previous analyses. They tend to wrongly interpret new information in order to confirm their opinions.

Between 13 March, 2000 and 7 April, 2000, economic indicators confirmed the build-up of an economic heating and the future deterioration of the financial environment. Investors began to fear the possibility of a 50 bps increase in the interest rates during an upcoming federal meeting on 21 March. As a wave of anxiety started to sweep investors, the NDX100 fell by an average of 3 % per day between 13 and 15 March. On 21 March, the federal authorities increased the interest rates by only 0.25 point, which somewhat calmed the market. As the outlook turned positive, the market recovered. Here, we can discern the hesitation of the investors prior to the market reversal. They have a selective perception, unconsciously interpreting information incorrectly to rationalize their strategies and a selective exposure, where they are open only to information which validates their outlook. Unconsciously, investors adopt the same attitudes of others they identify with. However, they overestimate the number of people sharing their opinion. Meanwhile, large fund managers began to pull out of the market.Footnote 17 The deterioration of the financial market originally forecast becomes a reality. Between 28 and 30 March, the NDX100 fell by 10 %. Both investors and the media attributed this decrease to a simple market correction owing to profit-taking. On 31 March, the market rocketed to 4,397 points.

On 3 April, the market tumbled again, this time by 7.6 %. On 4 April, it fell by 13 % and closed at 4,034 points. The market bounced back on 7 April, closing at 4,291, an increase of 4.9 %; investors breathed a sigh of relief as the volatile week ended positively. It was still unclear, however, whether the market correction was simply a technical correction. Nonetheless, large investors had already started liquidating their positions.

Transition phase—the crash

The process of financial disengagement started as signs of a reversal grew stronger, monetary conditions tightened and anxiety took over. This period can be compared to trying to listening to an opera. We are so carried away by the music that we are able to block out any disturbing noise. As time passes, however, when the ambient noise intensifies, we can no longer ignore it and continue to enjoy the opera. This increasing noise represents the financial disengagement of market professional. Investors realized that the correction observed in the stock market prices was not the same as the previous one. This correction was more serious and did not seem selective and brief as it affected all market sectors. On 10 April, the NDX100 fell 300 points and prices continued to decline drastically in the following 4 days prompting authorities to suspend quotes on several shares. The successive suspension of quotes, however, aggravated the situation even more, owing to the temporary illiquidity it created and the following behaviors were observed:

Crowd behavior: the panic sent a clear signal of the critical situation to other market players, influencing the rest of the investors who ended up changing their attitudes. In short, the panic was generalized with optimal dissemination of information and investor’s horizons align. Many investors habitually adopt strategies that take into account long-term equilibrium. From time to time, however, investors forgo these strategies when they lose confidence in the market and in its future. The lack of comprehension of external events provokes a panic more accurately described as an “avalanche effect”.

Sensory-tonic theory: The pressure created metabolic reactions which reinforced the escalation of panic. Subjected to stress, investors started to liquidate their positions. Liquidation made market prices fall even more and increased the margins call even more.

The market continued to drop every minute without showing any signs of stopping; on 14 April, the NDX100 closed at 3,205 points, a decline of 1,086 points (23 %) in 5 days. The Bearish trend (17 April–31 May, 2000) that followed the crash was marked by erratic fluctuations. No consensus could be reached and market players were lost. The mood fluctuated between positive and negative depending on market news. As such, investors were unable to think clearly and stick to their decisions without first having to review and analyze their decisions several times, ruminating over and over again. Now, the only pertinent information was the negative yields of the prices. In addition, margin calls amplified daily volumes on the sell side and aggravated the bearish trend.

On 16 May, indicators continued to show signs of economic heating, prompting federal authorities to increase interest rates by 50 bps. As a result, the market tumbled by 600 points. Owing to this substantial fall, investors hesitated for several days before buying in the market again. On 30 May, the NDX100 climbed by 9.6 % to 3,414 points. During this period, market fear was reflected in the high implied volatility where the VIX Index fluctuated between 27 and 35 %. Investors questioned whether this volatility spike indicated a short-term correction or if it was the beginning of a more severe correction. In reality, investors were hoping for a technical rebound following news that inflation has not reached an alarming level and that the economy was going to witness a soft landing. That was followed by a consolidation phase between June and September 2000 where the NDX100 fluctuated between 3,477 and 4,099 points.

Uncertain investors remained on their guard and the market remained nervous until the process of elimination started at the end of September 2000. Any negative information, regardless of its importance and whether it concerned only one company, affected the whole sector. The progressive elimination of categories of investors continued with the margin calls. During this period, it was crucial to ensure that the decrease in the price per barrel of oil was definitive and to evaluate the consequences of the fall of the Euro, which created an uncertainty relative to the period of profit reporting. The period of pre-announcement of earnings or warnings was an excuse for everyone to liquidate their positions. The NDX100 lost 13 % in 20 days. Investors were obsessed with the slightest details and were questioning themselves whether they had run proper analyses and whether they had overlooked any important information. They ended up by developing symptoms of depression in the sense that they were often unsatisfied and preoccupied. On October 2, 2000, during the Federal Reserve board meeting, Chairman Alan Greenspan’s commentary was pessimistic, owing to the resurgence of inflation fed by the increase in the oil price. Simultaneously, the weakness of the Euro against the U.S. dollar affected multinational’s margins which led to a series of “profit warnings” on behalf of these multinationals.

Following these events, an inverse schema was rapidly established wherein the decrease in share prices, deterioration of the underlying mechanism and bias reinforced one another. The NDX100 was in a bearish pattern (2 October, 2000–12 January, 2001) and the consensus was mostly negative. Market participants waited for a republican candidate to be elected, hoping for a new flow of liquidity owing to substantial tax reduction. By November 8, the elections were still in progress and the market was overwhelmed by enormous uncertainty pushing the NDX100 down by 7 %. At the end, G.W. Bush was elected as U.S. President on December 13. By then, however, pessimism had already overtaken the market. Market players felt that only a decrease in interest rates by the Federal Reserve could save these companies and uplift market, but nothing happened. Therefore, the NDX100 declined by 5.8 % the next day, to 2,340, a decrease of 34 % in 63 days.

On 3 January, following another 50 bps drop in interest rates, investors were very pessimistic and overestimated the deterioration of the economy and the markets. They were influenced by information, including that which was irrelevant, a phenomenon also known as the “touchy-feely syndrome.” The NDX100 declined by 48 % and each market rally became a “bear trap”. Throughout the bear market, an increase was deemed convincing only if the advance was based on economic and financial fundamentals news which can only modify the underlying mechanism.

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Hayek Kobeissi, Y. (2013). The Mind Process. In: Multifractal Financial Markets. SpringerBriefs in Finance. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4490-9_3

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