TheRumpledOne

<--------------------------------------------------------------------> "Look, for example, at this elegant little experiment. A rat was put in a T-shaped maze with a few morsels of food placed on either the far right or left side of the enclosure. The placement of the food is randomly determined, but the dice is rigged: over the long run, the food was placed on the left side sixty per cent of the time. How did the rat respond? It quickly realized that the left side was more rewarding. As a result, it always went to the left, which resulted in a sixty percent success rate. The rat didn't strive for perfection. It didn't search for a Unified Theory of the T-shaped maze, or try to decipher the disorder. Instead, it accepted the inherent uncertainty of the reward and learned to settle for the best possible alternative. The experiment was then repeated with Yale undergraduates. Unlike the rat, their swollen brains stubbornly searched for the elusive pattern that determined the placement of the reward. They made predictions and then tried to learn from their prediction errors. The problem was that there was nothing to predict: the randomness was real. Because the students refused to settle for a 60 percent success rate, they ended up with a 52 percent success rate. Although most of the students were convinced they were making progress towards identifying the underlying algorithm, they were actually being outsmarted by a rat." P64 HOW WE DECIDE <--------------------------------------------------------------------> Remember what H. Rearden said: Now, 2 patterns of market behaviour happen on a regular basis: 1) the price breaks to new high's (or low's) 2) the price reverses from new high's (or low's) <--------------------------------------------------------------------> If price is NOT making a new high then it must be reversing from the high. If price is NOT making a new low then it must be reversing from the low. GREEN RAT REVERSAL TRADE 1) price within 20 pips of the daily low - that is OPPORTUNITY 2) red/black candle closes 3) green/white candle closes - note the high price of the green/white candle 4) enter long at the green/white candle's high price 5) STOP LOSS IS 10 PIPS 6) Take whatever profit you can. <--------------------------------------------------------------------> RED RAT REVERSAL TRADE 1) price within 20 pips of the daily high - that is OPPORTUNITY 2) green/white candle closes 3) red/black candle closes - note the low price of the red/black candle 4) enter short at the red/black candle's low price 5) STOP LOSS IS 10 PIPS 6) Take whatever profit you can. <--------------------------------------------------------------------> You are either a RED RAT, a GREEN RAT or a YALE STUDENT. If you do not understand the reason you can not be both a red rat and a green rat then you are YALE MATERIAL:

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LOOKING FOR LOWS IN ALL THE RIGHT PLACES...LOL!!

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Ignoring Big Chances, Bumblebees Just Seek Small, Reliable Gains By NATALIE ANGIER Published: Tuesday, September 3, 1991 TO anybody who has been attacked by an enraged bumblebee, the insect seems impulsive to the point of kamikaze madness, willing to risk life and stinger to protect its nest. But in its everyday behavior while out rummaging for nectar and pollen, it seems, the bumblebee is a model of conservatism. In the most detailed study yet of how an animal estimates the costs and benefits of various foraging strategies, Dr. Leslie A. Real of the University of North Carolina in Chapel Hill has discovered that bumblebees make decisions about the marketplace of flowers with a degree of caution that would please an Amish elder. Avoiding the Big Gamble Reporting in the current issue of the journal Science, Dr. Real said that bumblebees preferred small rewards in measured doses over the possibility of winning big but with a high chance of failure. When presented in the laboratory with two types of artificial flowers, one that holds a modest but predictable amount of nectar, and the other that sometimes offers huge quantities of food but at other times contains little or nothing of the bee's beloved liqueur, the bees quickly learn to avoid the chancy flower and home in on the known quantity. The results indicate that the bees make decisions in a manner quite unlike the strategies used by many humans, he said, who often rely on a subjective sense of luck, fate and intuition before choosing a course of action. Dr. Real suggests that the conservative approach is of great benefit to the bee, and that a more daredevil approach would probably doom the little creature to extinction. "A bee will go after a predictable resource rather than a risky one," Dr. Real said. "Bees are processing information in a very particular way, and following certain computational rules that end up being good for the bee in its particular environment." The new findings, which involve elaborate calculations of bee flight dynamics, bee energy needs, bee brainpower capacity and bee ingestion mechanics, give fresh insight into why animals make the choices they do about local resources and how best to harvest them. "The questions he's asking are incredibly important, and it's great that he has an ecological perspective," said Dr. Thomas Eisner, an evolutionary biologist at Cornell University in Ithaca, N.Y. Surprisingly Sophisticated Choices Other scientists were impressed by the report's emphasis on bee intelligence. Rather than dismissing the bee as a stupid creature whose every action is a reflexive, hardwired response, as many researchers have in the past, Dr. Real says that the bee uses its limited neurological capacity to good advantage, and that it reaches surprisingly sophisticated conclusions about life from a restricted sampling of the environment. "This is a question of animal problem solving," said Dr. Gene E. Robinson, an entomologist at the University of Illinois in Urbana-Champaign, who works on honeybees. "Real isn't writing a neurobiological paper, but he's trying to ask, How does an animal make a decision and what do the results say about the underlying neural processes that may be taking place in the brain of a bumblebee?" Dr. Real chose to study bumblebees because, unlike honeybees, they do not dance or in any other way seem to communicate with one another about potential food sources. Instead, each bumblebee makes its foraging decisions independently. The researchers built artificial gardens of 100 blue cardboard flowers and 100 yellow cardboard flowers, interspersed randomly, with little dishes placed on top of them. The blue-flower dishes were supplied with fixed amounts of honey and water -- representing the nectar -- while in the yellow-flower dishes the quantity of food was varied. Some trays were left empty, while others were filled far beyond what was apportioned to the fixed blue flowers. Marking individual bees with daubs of paint, the researchers set them free to forage. The bees began by randomly visiting flowers. With their keen color vision able to discriminate between blue and yellow, they needed only a sample of five or six flowers before they started focusing all their efforts on the predictable blue flowers. They did so even though the average amount of nectar under each flower type was the same. The only difference was that in one case it was divvied up evenly, and in the other it was distributed with more in some dishes and none in the others. For another foraging session, the flower colors were changed, with blue representing varying rewards, and yellow the sure bet. The color made no difference. After visitations to only half a dozen flowers, the bees this time overwhelmingly preferred the steady yellows over the fickle blues. Dr. Real then began playing around with the ratio of risk to benefit in the varying flower dishes, offering tiny bits of honey in some dishes and bigger amounts in the remaining; but still the bees opted for the flowers that had the constant, moderate amounts of food. Only when the ratio of payoff to risk became considerable did the bees begin preferring the flowers with the varied amounts. But at that point, the average amount of nectar to be had from all the variable flowers was several times greater than could be extracted from the sum of the predictable flowers, a set of odds that could hardly qualify as a Dostoyevskian gamble. After many additional experiments and complex engineering and economics calculations, Dr. Real has concluded that the bee's fundamental computational rule is to obey what it has deduced about flowers after the most seemingly cursory of samplings. "They seem to be influenced by short-term calculations of benefit rather than by long-term calculations," he said. "If the bee were just concerned about the total nectar it could extract over an entire patch of flowers, then it might take the longterm average of those flowers. But it seems to be more concerned about the rewards it will get from a particular flower, so it computes the average value very differently." While that may seem like a short-sighted and small-minded approach to seeking food, said Dr. Real, it actually works to the bee's advantage. "There are lots of other bees and other pollinators in the same patch that are exploiting the same types of flowers," Dr. Real said. "So what the bee needs to worry about more than anything else is the quality of this flower it's on, rather than thinking about those flowers that may be spread out around it." In general, he said, any given crop of flowers in nature is likely to have been picked through to some degree by other nectar-seekers. Only seldom is a floral stand so virginal that a visiting forager could expect the patch to be bursting with food. Because bees need to keep eating, they cannot afford to hunt around for such a rare blessing. Thus, it behooves a bee to accept the realities of competition and to make the best of a modest situation, finding a small group of flowers within the larger patch that offers a reasonable if unremarkable quantity of nectar. Dr. Real believes the bees are so geared toward this sort of pragmatism that they end up pooh-poohing the occasional juicy reward as a probable irrelevance. "Bees ignore rare events and pay attention to common events," he said. Indeed, his calculations showed that the bees somewhat underestimate the chances of a rare event occurring, which is why he had to bump up the ratios in his variable flowers relatively high before the bees would change their natural predilection for the predictable. "A bumblebee perceives the rare event as being even rarer than it is," he said. Such an attitude stands in decided contrast to that of humans. "Psychologists have long suggested that humans underestimate the likelihood of common events, and overestimate the likelihood of rare events," he said. "They homogenize probabilities and treat them almost like they're 50-50. "Humans are optimists, and they believe rare events will happen more frequently than they actually do." Dr. Real suggests that it is just this sort of faith that keeps Las Vegas and state lotteries in business. Diagrams: "The Mind of a Bumblebee" How do bumblebees weigh benefit and risk in deciding which plants to visit? In an experiment designed to probe the insects' thinking processes, a researcher set out an artificial meadow of reliable blue flowers, each containing a small amount of nectar, and chancy yellow flowers, some containing nothing, some a jackpot of nectar. Bumblebees turn out to choose a safe thing over a lottery. They prefer blue flowers with reliable though meager nectar to yellow flowers with a greater but inconsistent reward. This is a sensible strategy when nectar-rich flowers are rare. When yellow flowers are made the reliable source of nectar and blue flowers the unpredictable source, the bees switch from blue to yellow after sampling only three flowers. The quick switch conserves energy. (Source: Science) Ignoring Big Chances, Bumblebees Just Seek Small, Reliable Gains - The New York Times

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YOUR MONEY AND YOUR BRAIN: How The New Science Of Neuroeconomics Can Help Make You Rich By Jason Zweig

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YOUR MONEY AND YOUR BRAIN: How The New Science Of Neuroeconomics Can Help Make You Rich By Jason Zweig

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THIS IS WAY TOO FUNNY!! RATTRADERS (rattraders)

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