[abstract]:

FOUNDATIONS OF TECHNICAL ANALYSIS: COMPUTATIONAL ALGORITHMS,
STATISTICAL INFERENCE, AND EMPIRICAL IMPLEMENTATION

Journal of Finance 55(2000), 1705-1765.

Andrew W. Lo

Technical analysis, also known as ``charting,'' has been a part of financial practice for many
decades, but this discipline has not received the same level of academic scrutiny and acceptance as
more traditional approaches such as fundamental analysis. One of the main obstacles is the highly
subjective nature of technical analysis---the presence of geometric shapes in historical price
charts is often in the eyes of the beholder. In this paper, we propose a systematic and automatic
approach to technical pattern recognition using nonparametric kernel regression, and apply this
method to a large number of U.S.\ stocks from 1962 to 1996 to evaluate the effectiveness of
technical analysis. By comparing the unconditional empirical distribution of daily
stock returns to the conditional distribution---conditioned on specific technical indicators such
as head-and-shoulders or double-bottoms---we find that over the 31-year sample period, several
technical indicators do provide incremental information and may have some practical value.