Ten inexperienced remote viewers attempted to predict the outcome of the Dow Jones Industrial Average (DJIA) using a protocol known as associative remote viewing (ARV). ARV was developed in 1984 by Russell Targ and Harold Puthoff, making use of trained viewers to predict future events. Since that time, there has been limited experimentation resulting in few publications, despite indications that suggest that the ARV protocol works and can be easily repeated. The current experiment used ARV with untrained viewers. The participants were drawn from a University of Colorado class and had no formal training in ESP or remote viewing prior to the start of this project.
For each trial the tasker chose two images, one that he linked to a DJIA rise and the other to a fall. He did not reveal either image to anyone until the end of the market day, which was a day or two after the ARV session. For the first five minutes of seven successive class sessions, the students were tasked to describe an image that was to be shown to them after the close of the market on the designated day. The tasker and other judges compared the viewers’ drawings to the two images and judged which image each drawing was closer to. The image that the majority of viewers’ sessions was judged to most closely resemble was used to predict the outcome of the market and guide the investment. The results are shown in the table, where D and U indicates down or up predictions, respectively, and M indicates mixed predictions which could not be linked clearly to either image. The number following the letter indicates the judged quality of correspondence of the drawing to the image.
Using this ARV protocol, the participants successfully predicted the outcome of the DJIA in seven out of the seven trials (binomial probability test, p less than .01). Investments in stocks were made based on the outcomes of the amateur remote viewers’ sessions resulting in a significant financial gain over a short period of time. From this experiment it appears that ARV can be used by untrained and inexperienced subjects with success, at least for limited runs.
Stock Market Prediction Using Associative Remote Viewing with Untrained Viewers
This experiment is one of the student experiments carried out as part of Edges of Science, an Honors course offered at the University of Colorado in Boulder.
Christopher Carson Smith, Darrell Laham, and Garret Moddel
Recorded at the 29th annual SSE Conference in 2010 in Boulder, Colorado, USA.
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Published on May 5, 2011