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Daily Report 28th June Crude Oil Futures - Indicators Technical Analysis
This Is The Daily Sceeto Report
For The Crude Oil Futures
On 28th June
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Courtesy of Wikipedia From Wikipedia, the free encyclopedia
While the advanced mathematical nature of such adaptive systems has kept neural networks for financial analysis mostly within academic research circles, in recent years more user friendly neural network software has made the technology more accessible to traders. However, large-scale application is problematic because of the problem of matching the correct neural topology to the market being studied.
[edit] Combination with other market forecast methods
John Murphy states that the principal sources of information available to technicians are price, volume and open interest.[10] Other data, such as indicators and sentiment analysis, are considered secondary.
However, many technical analysts reach outside pure technical analysis, combining other market forecast methods with their technical work. One advocate for this approach is John Bollinger, who coined the term rational analysis in the middle 1980s for the intersection of technical analysis and fundamental analysis.[38] Another such approach, fusion analysis,[39] overlays fundamental analysis with technical, in an attempt to improve portfolio manager performance.
Technical analysis is also often combined with quantitative analysis and economics. For example, neural networks may be used to help identify intermarket relationships.[40] A few market forecasters combine financial astrology with technical analysis. Chris Carolan's article "Autumn Panics and Calendar Phenomenon", which won the Market Technicians Association Dow Award for best technical analysis paper in 1998, demonstrates how technical analysis and lunar cycles can be combined.[41] Calendar phenomena, such as the January effect in the stock market, are generally believed to be caused by tax and accounting related transactions, and are not related to the subject of financial astrology.
Investor and newsletter polls, and magazine cover sentiment indicators, are also used by technical analysts.[42]
[edit] Empirical evidence
Whether technical analysis actually works is a matter of controversy. Methods vary greatly, and different technical analysts can sometimes make contradictory predictions from the same data. Many investors claim that they experience positive returns, but academic appraisals often find that it has little predictive power.[43] Of 95 modern studies, 56 concluded that technical analysis had positive results, although data-snooping bias and other problems make the analysis difficult.[11] Nonlinear prediction using neural networks occasionally produces statistically significant prediction results.[44] A Federal Reserve working paper[19] regarding support and resistance levels in short-term foreign exchange rates "offers strong evidence that the levels help to predict intraday trend interruptions," although the "predictive power" of those levels was "found to vary across the exchange rates and firms examined".
Technical trading strategies were found to be effective in the Chinese marketplace by a recent study that states, "Finally, we find significant positive returns on buy trades generated by the contrarian version of the moving-average crossover rule, the channel breakout rule, and the Bollinger band trading rule, after accounting for transaction costs of 0.50 percent."[45]
