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The 1997 Nobel Prize in Economics was awarded to Robert C. Merton and Myron S. Scholes for their Options Pricing Model, along with Fischer Black.
This is a good example to reveal the general importance of pricing models, although this model was only designed to determine the time value of
derivatives but not the value of the underlying contract itself. Furthermore, this mathematical model contains blind-spots due to the use of static
parameters which fail to perform price forecasts under the rule of Random Walk. As a matter of fact, this model can only find the derivatives' fair
value at a certain time-spot. Consequently, the risk component and the long-term question — are prices following a Random Walk or are they predictable?
— remain. The failure of LTCM proved that this model is not applicable in kinetic markets.
The Weaknesses of Fundamental/Technical Analysis and the Application of Artificial Intelligence
When economists try to use economic figures to analyze markets, they are facing various difficulties. Either the data available is insufficient or
numbers are ambiguous and even worse, markets roll over consistently and money is changing hands rapidly. With such background, it may not be impossible
but difficult to come up with useful and reliable price forecasts.
On the other hand, Technical Analysis nowadays is dominated by Candlestick-, Bar- and Line-Charts in combination with various indicators merely derived
by statistical or mathematical calculation. Furthermore, the accuracy of Technical Analysis is blocked by the theory of Random Walk.
In the late 20th century, computer technology has gained its popularity; as a result, Wall Street financial communities have had biannual conventions
on the application of Artificial Intelligence in financial trading since 1991. During those conferences there were lots of discussions about utilizing
Neural Networks, Genetic Algorithms, Fuzzy Logic or Chaos Theory but so far nothing significant has been achieved.
In conclusion, there has not been any breakthrough-method (neither fundamental nor technical) of price forecasting in the financial industry for
several decades.
J-Chart's philosophy makes price forecasting possible
J-Chart's philosophy is based on the assumption that using fixed time-sequence intervals is the major weakness in the currently accepted way
doing market analysis. Investors use (fixed) hourly, daily, weekly or even monthly time-sequence intervals to analyze markets but this approach is fundamentally
flawed.
"Time" is an irreversible vector, which has no meaning without "events". As a result, these events are the important factors and not time itself. In order to
identify events, we need a concept that allows a flexible handling of time.
Similarly, J-Chart’s philosophy is based on the following principles:
- History repeats itself,
- Only the "event" matters and "price" is the event,
- The event happened for the purpose of achieving equilibrium,
- The outcome of equilibrium is chaos — with an endless cycle between these two states.
J-Chart is an innovative forecasting technology, that allows a flexible handling of time in order to identify "events" as well as their future image points.
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