  This paper investigates the phenomenon of support and resistance levels (SR
levels) in financial time series, which act as temporary price barriers that
reverses price trends. We develop a heuristic discovery algorithm for this
purpose, to discover and evaluate SR levels for intraday price series. Our
simple approach discovers SR levels which are able to reverse price trends
statistically significantly. Asset price entering SR levels with higher number
of price bounces before are more likely to bounce on such SR levels again. We
also show that the decay aspect of the discovered SR levels as decreasing
probability of price bounce over time. We conclude SR levels are features in
financial time series are not explained simply by AR(1) processes, stationary
or otherwise; and that they contribute to the temporary predictability and
stationarity of the investigated price series.
