TAILIEUCHUNG - Stock Market Behavior Predicted by Rat Neurons

The SEC sued a number of individuals who used mailing lists to target seniors for investments in "guaranteed" and fully-collateralized promissory notes. The individuals distributed literature stating that the lengthy, complicated, and expensive Texas probate process could be overcome by employing their company’s planning services. Investors were urged to liquidate their legitimate, safe investments; to withdraw funds from their IRAs; and to invest in high-risk investments. Investors were told their investments would be used to fund business ventures, none of which existed. Instead, investor funds were misappropriated to inappropriate uses as the construction of a lake home. | Stock Market Behavior Predicted by Rat Neurons by Timothy C. Marzullo Neuroscience Program University of Michigan Ann Arbor Edward G. Rantze Red Antze Inc. Cumming Georgia Gregory J. Gage Biomedical Engineering University of Michigan Ann Arbor We here report for the first time to the best of our knowledge rat motor cortex neurons predicting the behavior of the American stock market. We implanted the motor cortex of the brains of rats with silicon electrodes. Using the correlation technique we monitored the activity of neurons in our rats while simultaneously tracking the activity of stocks in the . stock market. Background Hedge Funds Hedge funds burgeoned in the early 1990 s as a popular alternative to the conventional and more regulated mutual funds. Hedge funds have often used alternative methods such as various human social factors to predict future performance of the stock market. However we here propose an alternative alternative method. Methods Correlation Analysis For nine days neural activity in the form of firing rates which are the number of electrical discharges per second from recorded neurons n 94 of three rats were averaged each day as Figure 1 top Behavioral apparatus rat trained on a brain-machine interface task while stocks simultaneously tracked. 22 Annals of Improbable Research July-August 2006 the rats learned to use a brain-machine interface1 to obtain food pellets. Mean firing rate data per day were stored using custom software MATLAB Mathworks Inc. Natick MA along with the closing stock prices for the same day for all corporations listed on NASDAQ the New York Stock Exchange and the American Stock Exchange n 4195 . Correlation coefficients were obtained using the corrcoef function of MATLAB and only stocks that had significant coefficients . t-test were labeled responding and further analyzed. See Figure 1 for a depiction of the behavioral apparatus. Methods Stock Market Prediction Generalization prediction is .

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