uninvited guest ... other than your excellent choice of name ... you are giving yourself a bad name. Why not stop wasting thread space and be uninvited somewhere else?
Quote from marketsurfer:
darkhorse.
a question:
what is your opinion of "fooled by randomness" by taleb. do you consider his work junk science?
thanks!
surfer
Quote from darkhorse:
Great book. Why would I consider it junk science.
...
Given Taleb's extreme skepticism, it would seem longevity is about the only criteria he gives respect to. Trend followers have longevity in spades.
Quote from zygma:
A support level can become a resistance level and visa versa when those levels are breached. Also new levels emerge over time but I am assuming that when you want to trade you would be looking at the relevant levels at the time of that trade.
The most important point to note is that much of the time the charts will tell you nothing - so dont expect to look at a chart, do a few calculations and enter a trade. Its not like that - you need to wait for your opportunities. If a stock has been bouncing up against a resistance level for some weeks and then breaks through jump on board - but only when the break is confirmed.
At the race track when money comes for a particular horse it firms in the betting - on the market when you see increasing volumes and high prices (or lower prices) a footprint is being left - something is in the wind! Look at the market action of companies that have risen or fallen just before a 'surprise' announcement of impending bankrupcy/ takeover/discovery of a pill for eternal life etc. Money from people in the know. TA reveals a lot of that stuff
Quote from uninvited_guest:
27 pages and no proof that TA works.
Quote from jamis359:
Here's rigorous academic proof that T/A works.
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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.
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Table VI of this study lists 10 common T/A patterns that were tested. In the Nasdaq, all 10 patterns yielded positive, non-random returns. The best patterns are the triangle top, triangle bottom and inverted head and shoulders.