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[Shaw]
"A moving average will always lag stock price movement. The
movement of a stock below an uptrending moving average is considered
to be a sign of impending weakness. More important is that as the
moving average itself flattens out and begins to trend down, it
often will confirm that a shift in the basic trend in the stock
has occurred". |
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Data-snooping,
Technical Trading Rule Performance, and the Bootstrap, Sullivan,
Timmermann and White, 1997
"In this paper we utilize White's Reality Check bootstrap methodology
(White (1997)) to evaluate simple technical trading rules while
quantifying the data-snooping bias and fully adjusting for its effect
in the context of the full universe from which the trading rules
were drawn. Hence, for the first time, the paper presents a means
of calculating a comprehensive test of performance across all trading
rules. In particular, we consider the study of Brock, Lakonishok,
and LeBaron (1992), expand their universe of 26 trading rules, apply
the rules to 100 years of daily data on the Dow Jones Industrial
Average, and determine the effects of data-snooping. During the
sample period inspected by Brock, Lakonishok and LeBaron, we find
that the best technical trading rule is capable of generating superior
performance even after accounting for datasnooping. However, we
also find that the best technical trading rule does not provide
superior performance when used to trade in the subsequent 10-year
post-sample period. We also perform a similar analysis, applying
technical trading rules to the Standard and Poor's 500 futures contract.
Here, too, we find no evidence that the best technical rule outperforms,
once account is taken of data-snooping effects". |
The
moving averages demystified, Vandewallea, Ausloosa and Boverouxb
, 1999
"A common method in technical analysis is the construction
of moving averages along time series of stock prices. We show that
they present a practical interest for physicists, and raise new
questions on fundamental ground". |
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A
Moving Average Comparison of the Tel-Aviv 25 and S & P 500 Stock
Indices, Shachmurove, BenZion, Klein andYagil, 2001
"Random Walk and Efficient Market Hypotheses are central ideas
in explaining financial market efficiencies. The assumption that
market behavior embodies and reflects relevant information has a
great impact on securities prices. Any change in the relevant information
causes price adjustment. In contrast, technical analysts argue that
prices gradually adjust to new information. Thus, historical analysis
is useful in diagnosing the repeated pattern behaviors leading to
active investment strategies that generate better- than-market returns.
The purpose of this study is to examine the efficacy of using technical
trading rules in the emerging market of Israel, through the analysis
of the Tel-Aviv 25 Index (TA25) and to compare its weak-form market
efficiency to the performance of the S&P 500". |
Naive
Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction
Theory: A Study of "Technical Analysis, NEFTCI, 1991
"This article attempts a formal study of technical analysis,
which is a class of informal prediction rules, often preferred to
Wiener-Kolmogorov prediction theory by participants of financial
markets. Yet Wiener-Kolmogorov prediction theory provides optimal
linear forecasts. This article investigates two issues that may
explain this contradiction. First, the article attempts to devise
formal algorithms to represent various forms of technical analysis
in order to see if these rules are well defined. Second, the article
discusses under which conditions (if any) technical analysis might
capture those properties of stock prices left unexploited by linear
models of Wiener-Kolmogorov theory". |
Technical
analysis in the Madrid stock exchange, Rodriguez, Rivero and
Felix, 1999
"In this paper we assess whether some simple forms of technical
analysis can predict stock price movements in the Madrid Stock Exchange.
Our results provide strong support for profitability of these technical
trading rules". |
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Statistical
Evidence on a New Method of Trading the Financial Markets,
"The concept - well known to practitioners - of moving average
is recalled, and the one of adaptive moving average summarized.
Then a new algorithm is introduced, and it is shown that statistical
confidence limits are in favor of the thesis that such a method
is able to make constant profits on financial markets, specifically
on future markets, where commissions are not important. This results
are an obvious challenge to the efficient market hypothesis, if
the necessity of another challenge should be felt". |
The
predictability of asset returns: an approach combining technical
analysis and time series forecasts, FANG, YUE and XU, 2002
"We investigate predictability of asset returns by developing
an approach that combines technical analysis and conventional time
series forecasts. While exploiting predictable components as functions
of past prices or returns, technical trading rules and time series
forecasts capture different aspects of market predictability: the
former tends to identify periods to be in the market when returns
are positive and the latter is capable of identifying periods to
be out when returns are negative. Applied to daily Dow Jones Averages
over the first 100 years, the combined strategies outperform both
technical trading rules and time series forecasts. We focus on the
widely used double cross-over trading strategies in which two moving
averages are calculated and trading signals are generated when the
two moving averages intersect. These trading rules are typical trend-following
methods and serve frequently as the basis for more sophisticated
schemes". |
Unsystematic
Futures Profits with Technical Trading Rules: A Case for Flexibility,
BALSARA, NAUZER, CARLSON and RAO, 1966
"The dual moving average crossover rule, commonly used by technical
traders, is employed to generate signals for entering into and exiting
out of a trade. Moving averages of historic daily settlement prices
are calculated. The lengths of the two moving averages are unequal,
so as to allow for a crossover between the shorter and longer moving
averages. The shorter the time period over which the moving average
is calculated, the more responsive it is to price fluctuations.
Therefore, when the shorter of the dual moving averages crosses
above the longer moving average, this signifies an uptrend in prices,
generating a buy signal at the crossover point. Similarly, when
the shorter moving average crosses below the longer-term moving
average, we have a downtrend in prices, and the crossover signals
selling the commodity in question.
The conclusions arrived at in this paper support the findings of
Stevenson and Bear (1970) to the extent that mechanical trading
rules can be profitable at times. However, it would be naive to
believe that a given rule will perform consistently well across
different commodities and time periods. This is due to the fact
that although price trends do exist, these trends do not recur with
a regular periodicity. Consequently, the paper recommends the use
of flexible-parameter trading rules which adapt to changes in market
conditions, instead of expecting the market to operate within the
specifications of an unalterable set of rules". |
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