Predicting financial markets using associative remote viewing


Earlier this year, the Journal of Parapsychology, published  the results from a 13-year experiment conducted by Greg Kolodziejzyk, using a unique approach to the associative remote viewing (ARV) protocol which allows a single operator to conduct the full ARV process beginning to end. ARV is, essentially, a form of clairvoyant precognition (or extrasensory perception, ESP) designed specifically for use in the area of financial forecasting. It has a history going back to the 1970s. Many important research studies that preceded this one are cited in the article. Also here is a link to an audio interview with Greg Kolodziejzyk about his work.

A total of 5,677 ARV trials were conducted from May 11, 1998, to September 26, 2011. Of these, 52.65 % were correct in predicting the outcome of their respective future events (where only 50% would be expected by chance), yielding a statistically significant score of z = 4.0. These 5,677 trials addressed a total of 285 project questions. Most of these project questions were intended to predict the outcome of a given futures market. Of these project questions, 60.3% were answered correctly, resulting in a statistically significant z = 3.49. By increasing the number of trials in a project question, and giving more weight to higher subjective confidence scores reflecting the quality of the match between the remote viewing and one of the two target images, the success rate increased to above 70%. One hundred eighty-one project questions resulted in actual futures trades where capital was risked. Of these, 60% of the trades were profitable, amounting to approximately $146,587.30.

In the academic community, particularly in the field of psychology, there is a tendency to scoff as results such as this. The study of extrasensory perception is still considered by many to be a fringe science. However, it should be noted that the Parapsychological Association, the organization of serious researchers in this field, has had a formal association with the American Association for the Advancement of Science since 1969. I myself, received a doctoral degree in parapsychology back in 1980 from the University of California, Berkeley. And, in spite of the controversies that stigmatize this field, I can attest from decades of experience that, generally speaking, parapsychology researchers are far more sophisticated and knowledgeable than their noisy critics.

Progress in this field is very slow. But, eventually, I imagine that Kolodziejzyk’s pioneering work (and that of others in the field) will become incorporated into the realm of mainstream financial forecasting. My timetable for this is about fifty years; although, if I had my way, it would be sooner.


Posted in scientific understanding of financial markets Tagged with: , , , , , , , , , , , , , , , , , , , , , , , , , , ,
4 comments on “Predicting financial markets using associative remote viewing
  1. says:

    Jason, I have asked Greg to respond to your questions. Here is the response he sent to me —


    The trade selection process is outlined in the paper.

    Statistical significance (Z score) of the result was calculated using a control group (monte carlo simulation). Details are in the paper.

    There is no equity curve, and since this was a parapsychology experiment, not a trading experiment, we felt the discussion of drawdown, and an equity curve didn’t fit the context of the paper. Although, I did discuss the fact that the drawdown was high and I don’t feel that this is a viable trading methodology on it’s own in my summary – again, it is in the paper.

    Greg Kolodziejzyk

  2. Jason says:

    Thanks for the reply. Please try to reconcile these statements from his paper:

    “The 5,677 ARV trials I conducted between 1998 and 2011 were
    divided among a total of 285 project questions aimed at deciding what, if any, action to take regarding that same number of future events. Most of these events were market trades, and most of the trades were actual trades where capital was risked. ”


    “Of the 285 project questions, 181 led to actual trades where
    capital was risked on the prediction. These 181 projects were comprised of 4,007 trials; 60% of the trades were profitable, and net profits amounted to $146,587.30.”

    Mow, since you posted the paper and you defend the works maybe you know which was the selection process from the 285 project questions that led to 181 actual trades.

    In addition, it would be easy to calculate the statistical significance of the results based on a control group that basically tossed a coin to make a decision if the markets and dates were known.

    Finally, I am surprised there is no equity curve presented. What was the drawdown? What was that caused an increase of capital from 50k to 100k late in the game?

    “The starting capital required in the futures account was $50,000, and was increased to $100,000 in 2011”

    Why the trials stopped shortly after the capital was increased?

    Since you posted the paper I suspect you know the answers/


  3. says:

    Jason, I differ with you on all points.

    AAPL has been a wonderful stock. In fact, my AAPL profits have more than paid for all the many Apple products I have purchased over the last 30 years. But, the phenomenal growth of that stock is irrelevant to this particular study. Your pointing to the 5,600% growth is a post hoc analysis. I’ll bet you wish you could have predicted what would have happened 13 years ago.

    As far as non-repeatability is concerned, many scientific studies focus on a single individual. In social science, this is known as an “ideographic” approach, as opposed to a “nomethetic” study. Such studies have made a great contribution to our knowledge — so there is no loss of credibility in citing such a study. Furthermore, there have been a number of conceptual replications of the same concept (associative remote view or ARV) that are cited within Kolodziejzk’s paper.

    The argument that the study is statistically flawed in the absence of a control group is also specious. The general lore among traders is that only about 10% are consistently successful over time. One can use that as a control, if you like. Or, one can use the basic assumption that, for short-term trading, the a priori probability of either an upward or downward movement is approximately 50%.

    Of course, one can nitpick any single scientific study, in any discipline. And, if you are uncomfortable with the purported finding, that is precisely what you will do. But, given the weight of 150 years of parapsychological research, sustained over ever-increasing degrees of methodological rigor, I find the Kolodziejzk study to be reasonable and consistent.

  4. Jason says:

    The AAPL return in the same period is close to 5,600%. Your blog is loosing credibility when reference to non-repeatable experiments is presented like that. Besides the study is statistically seriously flawed as there is no control group.

1 Pings/Trackbacks for "Predicting financial markets using associative remote viewing"
  1. […] Predicting financial markets using associative remote viewing | The Alpha Interface. […]

Leave a Reply

Your email address will not be published. Required fields are marked *


Book Three: Trading With The News

Learn about a news-based trading system that yielded a back-tested, average annualized, compounded return from 2000 to 2011 of 58.6%.

“Only once you’ve done your homework will you be able to understand how the stock market works and learn to distinguish between news and noise.” Maria Bartiromo, Use The News

Book Two: Technical Analysis

Learn about the "trend recalling" algorithm that yielded researchers a simulated annual return of greater than 400% in multiple tests.

“The scientific method is the only rational way to extract useful knowledge from market data and the only rational approach for determining which technical analysis methods have predictive power.”
David Aronson, Evidence Based Technical Analysis

Book One: Analysts’ Forecasts

Learn the strategy, based on analysts' revised forecasts, that yielded researchers an average of 1.13% - 2.19% profit per trade, for trades lasting one to two days?

Learn how certain analysts' recommendations, following brokerage hosted investment conferences, yielded profits of over 3% during a two-day holding period?

Learn how researchers found an average profitability of 1.78% for two-hour trades following an earnings announcement?

"This set of tools can help both ordinary and professional investors alike to re-think and re-vitalize their stock picking, timing and methods. A young, aspiring Warren Buffet could put this book to good use."
James P. Driscoll, PhD, investor

Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments by David Aronson (software included)

Evidence-Based Technical Analysis by David Aronson

Archive of Earlier Posts