The Quest for the Holy Grail

The Quest for The Holy Grail 
Jeffrey Mishlove, PhD
Is there a Holy Grail in the world of investing?  Conventional wisdom has it that there is not, i.e., that there is no system of financial forecasting that can consistently and reliably produce significant, profitable results.  Yet, simultaneously, investors spend millions of dollars annually on computer programs for the purpose of beating the market.

Skeptics argue that, if such systems really performed, then the large financial houses — who have millions of dollars to invest in such systems — would be more profitable than they are.

Proponents point out that many, individual traders and investors use computer systems year after year to earn significant income — i.e., in the neighborhood of 200% return on their investment capital.

Skeptics counter that chance alone, combined with the general expansion of the economy, will result in percentage of people achieving such investment success — without the need for or benefit of a viable forecasting system.  Skeptics note that, eventually, these highly touted systems stop working.

Proponents acknowledge that forecasting systems require modification and refinement as market conditions change.  Proponents also point out that effective, forecasting systems are not widely known for proprietary reasons.  They also point out that, in certain thinly traded markets, effective forecasting systems will only remain viable when their use is sufficiently limited so as not to be confounded by additional flow of capital.

Skeptics counter that the very randomness of the markets acts — in a manner analogous to Heisenberg’s uncertainty principle in physics — as an impenetrable barrier to the effective, long-term use of mechanical forecasting systems.

Proponents respond that there have been published, academic studies pointing to the viability of certain technical indicators — such as the 200 day moving average — as reliable forecasting tools.

Skeptics respond by noting that, once such scientific information is made public, it is then absorbed by the investing public to the extent that its usefulness is diminished.

Proponents counter that newer, more sophisticated forecasting systems are being developed each year.  Many, involving neural networks and other forms of artificial intelligence, have the ability to learn and adjust themselves as conditions change.

For the latest information on this quest, visit my new website The Alpha Interface