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Technical Analysis (Technicals) Related Scholarly Compositions
See also:
Technical
Analysis Related News,
Technical Analysis
Related Books,
or
Technical Analysis Home Page.
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Application Of Neural Network To
Technical Analysis Of Stock Market Prediction
by Hirotaka
Mizuno, Michitaka Kosaka, Hiroshi Yajima, & Norihisa Komoda
Hitachi, Ltd. & Osaka University
April 27, 1998
Abstract
This paper presents a neural network model for technical
analysis of stock market, and its application to a buying and
selling timing prediction system for stock index. When the
numbers of learning samples are uneven among categories, the
neural network with normal learning has the problem that it
tries to improve only the prediction accuracy of most dominant
category. In this paper, a learning method is proposed for
improving prediction accuracy of other categories, controlling
the numbers of learning samples by using information about the
importance of each category...
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Currency Orders & Exchange-Rate
Dynamics: Explaining the Success of Technical Analysis
by C.S.
Osler
Abstract
This paper provides a microstructural explanation for the
success of two familiar predictions from technical analysis: (1)
trends tend to be reversed at predictable support and resistance
levels, and (2) trends gain momentum once predictable support
and resistance levels are crossed. The explanation is based on a
close examination of stop-loss and take-profit orders at a large
foreign exchange dealing bank. Take-profit orders tend to
reflect price trends, and stop-loss orders tend to intensify
trends...
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Foundations of Technical
Analysis: Computational Algorithms, Statistical Inference, and
Empirical Implementation
by Andrew
W. Lo, Harry Mamaysky, & Jiang Wang
1997
Abstract
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 we apply this method to a
large number of U.S. stocks from 1962 to 1996 to evaluate the
effectiveness of technical analysis...
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Is Technical Analysis in the
Foreign Exchange Market Profitable? A Genetic Programming
Approach
by
Christopher Neely, Paul Weller, & Robert Dittmar
1997
Abstract
Using genetic programming techniques to find technical trading
rules, we find
strong evidence of economically significant out-of-sample excess
returns to those rules for each of six exchange rates, over the
period 1981-1995. Further, when the dollar/deutschemark rules
are allowed to determine trades in the other markets, there is a
significant improvement in performance in all cases, except for
the deutschemark/yen. Betas calculated for the returns according
to various benchmark portfolios provide no evidence that the
returns to these rules are compensation for bearing systematic
risk...
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Market Efficiency and the Returns
to Technical Analysis
by Hendrik
Bessembinder & Kalok Chan
Arizona State University - College of Business
December, 1997
Abstract
We further investigate and provide interpretation for the
intriguing Brock, Lakonishok, and LeBaron (1992) finding that
simple forms of technical analysis contain significant forecast
power for U.S. equity index returns. We document that the
forecast ability is partially, but not solely, attributable to
return
measurement errors arising from nonsynchronous trading. We argue
that the evidence of technical forecast power need not be
inconsistent with market efficiency...
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Support for Resistance: Technical
Analysis and Intraday Exchange Rates
by Carol
Osler
Abstract
Early in the morning of each business day, the major foreign
exchange trading firms send their customers lists of technical
trading signals for that day. Timely technical signals are also
supplied by major real-time information providers. These
signals, which are based primarily on prior price and
volumemovements, are widely used by active foreign exchange
market participants for speculation and for timing their
nonspeculative currency transactions...
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Technical analysis and central
bank intervention
by
Christopher J. Neely & Paul A. Weller
Federal Reserve Bank of St. Louis & Henry B. Tippie College of
Business Administration
Abstract
This paper extends genetic programming techniques to show that
US foreign exchange intervention information improves technical
trading rules’ profitability for two of four exchange rates over
part of the out-of-sample period. Rules trade contrary to
intervention and are unusually profitable on days prior to
intervention, indicating that intervention is intended to halt
predictable trends. Intervention seems to be more successful in
checking such trends in the out-of-sample (1981–98) period than
in the in-sample (1975–80) period...
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Technical Analysis and Liquidity
Provision
by Kenneth
A. Kavajecz & Elizabeth R. Odders-White
The Wharton School & University of Wisconsin, Madison
February 25, 2002
Abstract
The apparent conflict between the level of resources dedicated
to technical analysis by practitioners and academic theories of
market efficiency is a long-standing puzzle. We offer an
alternative explanation for the value of technical analysis that
is consistent with market efficiency – specifically, that it
reveals information about limit order book liquidity. We find
evidence consistent with the hypotheses that support and
resistance levels coincide with peaks in depth on the book and
that moving average forecasts reveal information about the
relative position of depth on the limit order book...
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Why Have the Returns to Technical
Analysis Decreased?
by Willis
V. Kidd & B. Wade Brorsen
Oklahoma State University
Abstract
Returns to managed futures funds and Commodity Trading Advisors
(CTAs) have
decreased dramatically during the last several years. Since
funds overwhelmingly use technical analysis, this research
examines futures prices to determine if there is evidence of a
structural change in futures price movements that could explain
the reduction in fund returns. Bootstrap tests are used to test
significance of a change in statistics related to daily returns,
close-to-open changes, breakaway gaps, and serial correlation...
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Back to Scholarly Compositions
See also:
Technical
Analysis Related News,
Technical Analysis
Related Books,
or
Technical Analysis Home Page.
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