Forecasting markets has always been a nightmare to say the least. Just when you think that you have everything figured out, the trend suddenly emerges in the opposite direction. The science of forecasting itself has encountered a rather shabby reputation largely due to the number of people in the field who think they have everything figured out when in fact the market proves them to be wrong most of the time.
Personal interpretation is everything in technical analysis, fundamental analysis, Elliot Wave or even cyclical analysis. The only means of increasing the degree of accuracy lies in trying to eliminate personal interpretations and bias as much as possible. Today, the global economy has been making a fool out of just about every economic theory devised by man. Purely domestic economic/capital market models give way to the growing tide of international capital forces. If we look at the 1980-1985 period in the United States, we find that money supply rose by 400% and the national debt doubled. While the monetary theory would have us believe that an increase in money supply should produce higher inflation, the 1980-1985 period was proclaimed as the age of deflation.
The confusion that is emerging in the field of economics and capital market forecasting is a direct result of the drastic changes in our global economy since 1971. Where the theory of the monetarist was based upon a 100 year study of prices and money supply, there was one basic assumption that was ignored – the exchange rate. Prior to 1971 the world monetary system remained on the gold standard. Inflation and changes in money supply were directly linked since the value of currency was fixed. However, in the floating exchange rate era that began in 1971, inflation and money supply were no longer tied together. As 1980- 1985 proved, a rise in money supply did not necessarily result in inflation. A third variable was introduced, the floating dollar. Deflation emerged during the 1980-1985 period because the pressure within the system was relieved through the 405 rise in the value of the dollar.
Both economics and capital market forecasting are being seriously impaired by the shifting tides and evolution process within the global economy as a whole. for this reason, the models and understanding of our economic environment must also be able to change with the times or suffer from becoming obsolete.
Artificial Intelligence is one of the newest buzz words in computer technology. Unfortunately, there are a number of imitations that some people are calling AI. An Expert System is one such product where a computer can appear to be accomplishing artificial intelligence when in fact it is a rather simple object oriented program. Expert Systems take a knowledge-base on any topic from medicine to lending money in a bank. One needs only establish a knowledge-base of the facts. This is accomplished by a series of questions to query that knowledge among humans. In the end, a doctor can easily diagnose even a rare and unusual disease if he has never encountered the symptoms before. Banks can automate lending decisions on individual loans by establishing its criteria based upon past performance.
Some Expert Systems can employ what is called INDUCTION. This is a method of taking a huge sample of loans that a bank has made over a number of years. Which loans proved to be good and which loans proved to be bad can be sorted out by the computer itself. A set of rules would then be generated and the computer will follow those rules for making loan decisions in the future.
But this type of “intelligence” is still not true AI. It is a rather high level object oriented programming system designed to match A with B following a predetermined set of rules. At times this type of system can appear to be very intelligent making even complicated decisions in a few minutes or even seconds. Nonetheless, Expert Systems cannot adapt to changing market conditions as the economy moves through a natural evolution process. In order to keep an expert system up to date, requires “experts” to constantly rewrite the rules by which the computer would function.
For example, if interest rates tripled from their current levels, many loans, which may have been good at lower levels, could suddenly become bad loans. That was the case in many situations involving oil for example. An Expert System would be unable to cope with this type of loan decision if all the aspects of risk are not discernable at the time of making the loan decision. Even in the field of medicine, should a new disease emerge, someone would need to update the knowledge-base to inform the computer of its symptoms.
True Artificial Intelligence is therefore defined as a computer’s ability to adapt to changing conditions on its own without human intervention. For example, creating a robot who’s goal would be to explore Mars on its own requires a computer program to make a judgement decision. It may come upon a ravine and it must determine whether or not that ravine can be crossed and at what point. No expert system is capable of writing a rule for every possibility that would encompass situations that no human has ever encountered. When we are dealing with the global economy, the same problems exist since an evolution process is constantly underway.
Artificial Intelligence must be capable of adapting its program to the changing conditions in which it finds itself. If it were diagnosing a disease, it must be able to recognize the fact that it is dealing with something new. It must be able to create its own knowledge based upon what it encounters and store that experience in a collection of knowledge in a cognitive manner as a human does as he moves through life.
This is the main difference between Artificial Intelligence and all other forms of so called AI computer programming. It is the ability of the program to learn from its experiences in a cognitive manner exactly in the same methodology as a human being. It must be able to logically arrive at a conclusion based upon its collective and recorded experience, not strictly within the limitations prescribed by its programmer.
At Princeton Economics, we have poured countless hours of research and development into Artificial Intelligence with the exclusive goal of creating a financially intelligent computer that is capable of assessment and forecasting. Our Artificial Intelligence Unit is the only such working system in the financial industry. It is capable of assessing the market conditions providing specific buy and sell signals, asset allocation and strategic multinational planning.
Our AI computer model is capable of pattern recognition on a global scale monitoring world capital flows. Our models have been successful in not merely picking direction, but also in determining the timing and the players who will do what and when.
Armed with a database of incomparable size, our AI programs take searches it knowledge base to determine the next likely course of action. It knows what is likely to happen when capital flows shift from one nation to another and the impact of that change on the domestic economies and capital market in each nation.
In addition, our AI computer models take each domestic market globally and separates it into daily, weekly, monthly, quarterly and yearly activity. In this manner, it establishes the ability to differentiate between short-, intermediate-, and long-term changes in economic and capital market trends around the world. It was this model that enabled our forecast at the day of the low in 1987 that the stock market would rally back to new highs in 1989 and that there was NO risk of a 1929 style depression.
This multilevel infrastructure was the key to our global model’s success in not merely forecasting the change in trend in the U.S. stock market 1987, but it also provided the precise forecasts for the peak in real estate worldwide in 1990, the Japanese economy and much more.
Since the problem with most economic theories stems from their closed-door domestic approach “assuming all things remain equal,” it is not difficult to see why most forecasts of the economy and market behaviour prove to be incorrect. It is simply impossible for any individual to comprehend everything that is going on collectively around the world and take that knowledge to forecast a domestic outcome. Typically, most economic forecasts are still conducted today in total isolation removing any potential major variables by “assuming all things remain equal.” Our AI computer models work in the opposite manner by monitoring every possible economic and capital market change within the entire global community. Only in this manner can we ever hope to increase the odds of understanding the dynamic global changes in the world economy as a whole.
The PEI AI computer models have proven to be an important tool that expands our knowledge of the field of economics. It has the ability to seek new methods and explore new timing models on its own. It has the ability to adapt to changing conditions by creating its own database when it sees fit storing vital information for future comparison. In reality, the PEI AI computer models are a major breakthrough in technology that has been as vital to advancing true science as the invention of the microscope.
Star Trek? Perhaps! But the main thing is that true knowledge comes from experience. It is a collection of experiences that enables us to cope with day to day events. The PEI Artificial Intelligence designed into our computer models is a sophisticated method of storing economic, financial and political experiences that serve as a knowledge base upon which to assess the past and extrapolate the possibilities for the future. We are embarking on a new era of knowledge that will hopefully bring mankind to a much greater level of understanding his political-social- economic environment for the 21st century.