  In this paper we use fuzzy systems theory to convert the technical trading
rules commonly used by stock practitioners into excess demand functions which
are then used to drive the price dynamics. The technical trading rules are
recorded in natural languages where fuzzy words and vague expressions abound.
In Part I of this paper, we will show the details of how to transform the
technical trading heuristics into nonlinear dynamic equations. First, we define
fuzzy sets to represent the fuzzy terms in the technical trading rules; second,
we translate each technical trading heuristic into a group of fuzzy IF-THEN
rules; third, we combine the fuzzy IF-THEN rules in a group into a fuzzy
system; and finally, the linear combination of these fuzzy systems is used as
the excess demand function in the price dynamic equation. We transform a wide
variety of technical trading rules into fuzzy systems, including moving average
rules, support and resistance rules, trend line rules, big buyer, big seller
and manipulator rules, band and stop rules, and volume and relative strength
rules. Simulation results show that the price dynamics driven by these
technical trading rules are complex and chaotic, and some common phenomena in
real stock prices such as jumps, trending and self-fulfilling appear naturally.
