Term Paper: Herding in Bank Panics

Pages: 10 (3113 words)  ·  Bibliography Sources: 15  ·  Level: Doctorate  ·  Topic: Economics  ·  Buy This Paper

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[. . .] The researchers noted that "decisions under uncertainty . . . draw upon different neural processes." (Prechter and Parker, nd, p.14) Conclusions stated are reported as follows: "Depending on the circumstances, moods and emotions can play useful as well as disruptive roles in decision-making" (p. 428)." (Prechter and Parker, nd, p.14)

Prechter and Parker additionally report that over the past 3 1/2 decades "social psychologists have found that unconscious dynamics affect memory, perceptual skills, self-concept and self-evaluation, and biases and stereotypes related to race, gender and political partisanship. Socioeconomics adds financial decision-making to this list." (nd, p.14) Herding is reported to account for "human behavior in the financial realm that is anomalous to the neoclassical economic theory. The motivation of both types of behavior (financial and economic) is surely the same as that for all evolved behaviors: to survive and thrive. In finance, however, the mind is operating differently. Buyers in a rising market appear unconsciously to think, "The herd must know where the food is. Run with the herd and you will prosper." Sellers in a falling market appear to think, "The herd must know that there is a lion racing toward us. Run with the herd or you will die." (Prechter and Parker, nd, p.15)

The work of Avgouleas (2008) entitled "Reforming Investor Protection Regulation: The Impact of Cognitive Biases" states that Behavioral Decision Theory describes the "interdisciplinary intellectual movement that incorporates theories of decision-making that have their roots in: (1) the branch of cognitive psychology that is called psychology of judgment and choice, pioneered by two leading psychologists Daniel Kahneman and Amos Tversky and (2) experimental economics, a term that is mostly used to describe the laboratory tests of economic theory doctrines and the findings of those tests." (p.2) It is reported that studies that are empirical in nature and which have been "undertaken by psychology of judgment and choice scholars have documented the strong impact of cognitive processes (heuristics) and cognitive biases on individuals' decision-making." (Avgouleas, 2008, p.1) It is reported in the work of Kahneman and Tversky (1974) which provided a description of the heuristics of (1) representativeness, (2) availability; and (3) anchoring that people:

"…rely on a limited number of heuristic principles, which reduce the complex tasks of assessing probabilities and predicting values to simpler judgmental operations. In general, these heuristics are quite useful, but sometimes they lead to severe and systematic errors. Cognitive biases are the results of the use of heuristics, when they lead to: (a) 'systematic errors in estimates of known quantities and statistical facts' and (b) systematic departures of intuitive judgments from the principles of probability theory." (Avgouleas, 2008, p. 2)

Avgouleas (2008) states that some of the cognitive biases which are most important are those as follows: (1) mental accounting; (2) overconfidence; (3) loss-aversion; (4) anchoring; and (5) the framing effect. (p.3) Behavioral finance theory holds that markets "move only on the basis of rational expectations. Namely, asset prices are set by rational investors." (p.4-5)

EMH is stated to be "the brainchild of rational choice theory" and to make the assumption that "…market reflect-equal fundamental value and change because of new information. Thus, in an efficient market no investment strategy can yield average returns higher than the risk assumed ('there is no free lunch') and no trader can consistently outperform the market or accurately predict future price levels, as new information is instantly absorbed by market prices." (Avgouleas, 2008, p. 5)

EMH further makes the assumption that "…markets are efficient and transaction costs relatively low giving 'professionally-informed traders' the opportunity to quickly observe and exploit through arbitrage trading any price deviations from fundamental value, as this would create an opportunity to profit from such discrepancy. The result of arbitrage trading is that prices reach a new equilibrium, which reflects more accurately the traded asset's value and corrects any mis-pricings."(Avgouleas, 2008, p. 5-6)

The primary assumptions of EMH are challenges by behavioral finance which has as its primary tenets that: (1) certain market phenomenon called anomalies or puzzles may not be explained by the EMH, whereas the use of psychology can provide convincing explanations and (2) the corrective influence of arbitrage trading is limited due to a number of restrictions." (Avgouleas, 2008, p.6)

Jonah Lehrer reports an experiment conducted by Montague stating as follows:

"Each subject was given $100 and some basic information about the "current" state of the stock market. After choosing how much money to invest, the players watched nervously as their investments either rose or fell in value. The game continued for 20 rounds, and the subjects got to keep their earnings. One interesting twist was that instead of using random simulations of the stock market, Montague relied on distillations of data from famous historical markets. Montague had people "play" the Dow of 1929, the Nasdaq of 1998, and the S&P 500 of 1987, so the neural responses of investors reflected real-life bubbles and crashes. The scientists immediately discovered a strong neural signal that drove many of the investment decisions. The signal was fictive learning. Take, for example, this situation. A player has decided to wager 10% of her total portfolio in the market, which is a rather small bet. Then she watches as the market rises dramatically in value. At this point, the regret signal in the brain -- a swell of activity in the ventral caudate, a reward area rich in dopamine neurons -- lights up. While people enjoy their earnings, their brain is fixated on the profits they missed, figuring out the difference between the actual return and the best return "that could have been." The more we regret a decision, the more likely we are to do something different the next time around. As a result, investors in the experiment naturally adapted their investments to the ebb and flow of the market. When markets were booming, as in the Nasdaq bubble of the late 1990s, people perpetually increased their investments. But fictive learning isn't always adaptive. Montague argues that these computational signals are also a main cause of financial bubbles. When the market keeps going up, people are naturally inclined to make larger and larger investments in the boom. And then, just when investors are most convinced that the bubble isn't a bubble -- many of Montague's subjects eventually put all of their money into the booming market -- the bubble bursts. The Dow sinks, the Nasdaq collapses. At this point investors race to dump any assets that are declining in value, as their brain realizes that it made some very expensive prediction errors. That's when you get a financial panic." (Lehrer, 2008, p.1)

VII. Summary of Literature Review

The literature reviewed in this proposal for research has indicated that there is most certainly a neurological reason for financial mania, herding or financial panic. There are many questions remaining in this area of study however and various theories posited to attempt to explain this phenomenon.

VIII. Recommendations

The brief and introductory literature review contained in this proposal for research has resulted in a recommendation for further, additional and in-depth research in the area of neuroeconomics and its relation to financial herding and financial mania or panic. Therefore, this work in writing recommends that a year-long study be commenced for the purpose of better understanding the impact of psychoneurological effects on financial mania and bank herding during financial and economic crises.

References

Avgouleas, E. (20008) Reforming Investor Protection Regulation: The Impact of Cognitive Biases. Retrieved from: http://www.law.man.ac.uk/aboutus/staff/emilios_avgouleas/documents/AvgouleasCognitiveBiasesOgusfinal.pdf .

Bulow, Jeremy and Paul Klemperer, 1994, Rational frenzies and crashes, Journal of Political Economy 102, no. 1, 1-23. Chari, V.V. And Ravi Jagannathan, 1988, Banking panics, information, and rational expectations equilibrium, Journal of Finance 43, no. 3, 749-761.

Chen, Yehning, 1995a, Bank runs: Panic of efficient monitoring, Working paper (UCLA, Los Angeles, CA).

Chen, Yehning, 1995b, Banking panics: The role of the first-come, first-served rule and informational externalities, Working paper (UCLA, Los Angeles, CA). Donaldson, R. Glen, 1992, Sources of panics: Evidence from the weekly data, Journal of Monetary Economics 30, 277-305.

Devenow, A. And Welch, I. (1996) Rational Herding in Financial Economics. European Economic Review 40 (1996). Retrieved from: http://research.ivo-welch.info/journalcopy/1996-eer.pdf

Donaldson, R.G. (1989) Sources of Panics: Evidence from the Weekly Data. Journal of Monetary Economic 30 (1992) North-Holland. University of British Columbia, Canada. October 1989.

Glimchard et al. (2009) Neuroeconomics, Decision Making and the Brain, Elsevier, Amsterdam.

Grinblatt, Mark, Sheridan Titman and Russ Wermers, 1995, Momentum investment strategies, portfolio performance and herding: A study of mutual fund behavior, American Economic Review, forthcoming.

Grossman, Sanford J. And Joseph E. Stiglitz, 1976, Information and competitive price systems, American Economic Review 66, no. 2, 246-253

Jacklin, Charles J., Allan W. Kleidon and Paul Pfleiderer, 1992, Underestimation of portfolio insurance and the crash of October 1987, Review of Financial Studies 5, no. 1, 35-63.

Jacklin, Charles, J. And Sudipto Bhattacharya, 1988, Distinguishing panics and information -based bank runs: Welfare and policy implications, Journal of Political Economy 96, no.… [END OF PREVIEW]

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