Maybe its better to say that some TA works for some people, at least some of the time.It does and it doesn't. When it does, it does, when it doesn't, it doesn't. There is no better explanation.
Maybe its better to say that some TA works for some people, at least some of the time.It does and it doesn't. When it does, it does, when it doesn't, it doesn't. There is no better explanation.
Maybe its better to say that some TA works for some people, at least some of the time.
I think I will agree with that. Then it is not a science because science success is independent of the person that applies it. I found this article and it looks interesting. I do not agree with everything in it but the role of serial correlation is interesting and requires further investigation.
Technical analysis was developed during the 1960s and 1970s when personal computers were not even available.
From the article:
I have books about the stock market that were written in the early 1900's in which the overarching principle to trading and investing is technical analysis.
I think I will agree with that. Then it is not a science because science success is independent of the person that applies it. I found this article and it looks interesting. I do not agree with everything in it but the role of serial correlation is interesting and requires further investigation.
Wow! It was Richard D Wyckoff, in the 1900's who says volume on the tape tells you everything, he did not read news release, he looked at the order quantity coming in. That was 100% technical analysis. Why do you think he did that?Successful traders don't trade using 100 percent TA.
Maybe its better to say that some TA works for some people, at least some of the time.
Markets today are very different to the markets in the 1900sWow! It was Richard D Wyckoff, in the 1900's who says volume on the tape tells you everything, he did not read news release, he looked at the order quantity coming in. That was 100% technical analysis. Why do you think he did that?
Today, there are more advanced ways of judging value perception and volume. Most of it is masked so very difficult to detect. This makes technical analysis harder and a low probability trading approach. If you trade agri futures, then you would use both technical and fundamental, if you traded stocks, you will be inclined to use Lvl 2 and 3 quotes to get more depth in the market, so almost all technical, unless you were a buy and hold would you do absolute valuation modelling. If you are a currency trader ideally in the absence of leverage you will be using fundamental's like interest rate changes, to make your decisions about long-term value but with central banks easing, it seems there is no long-term value in currencies, so the bottom comes every 4-5 years in some cases more, so if you miss the boat then that's it, things top out very quickly and then you watch 2 or 3 years go by of extreme range bound action. This market is now largely short-term because of leverage, so technicals are by far the only choice, by this I mean an analysis that involves short and medium term value perception. So in short statistical technical models work best. In the banking sector statistical modelling is all everyone does. No sense in the RSI, etc. That's for bloomberg and to sell you guys the instruments and give you a reason to trade.
So to answer your question it does work but it doesn't depending on how you do it. What most retail traders do does not work and that's fact. Otherwise half this forum will be millionaires.
Its tarder, trust me that one mr hoe :cheesy:
you got a cat fetish you need to work on haha
and not talking about pussy CATS lol :clap:
Markets today are very different to the markets in the 1900s
In the 1900's the markets would rise and fall irregularly whereas today the markets fluctuate.
...So unless you're riding an event post-factum with some clever strategy which would render the market unnaturally repetitive if it were not to be profitable in the long run, you stand no chance at telling the future with some indies that might have worked often enough in the past and even still do on every other occassion, just not every time or even often enough to keep you and your leveraged trading account afloat with a chance for profits in sight.
Have you been through a major market crash with your portfolio? Would it survive the second half of 2008 unoptimized, for instance?I agree. However, my argument against TA is that if you analyze price histories of stocks, currencies, market indices, etc., with statistical tests, they are basically "random walks", i.e., non-stationary time series, such that future prices changes are uncorrelated with past and present prices. The implication is that you can't predict future price movements by analyzing price charts.
That said, it is often possible to assemble a portfolio of trading instruments that are stationary or mean-reverting, so that trading strategies are possible. This is the basis of statistical arbitrage, which is what I use to trade. However, this approach requires a more sophisticated mathematical background than that of your average trader.
I've only been trading live with this algorithm for 9 months. If we have another crash, I guess I'll find out how it performs under those conditions. However, the portfolio is market neutral, and I employ only modest (2x) leverage, so I anticipate that I'll be OK. We'll see.Have you been through a major market crash with your portfolio? Would it survive the second half of 2008 unoptimized, for instance?
Interesting article. It argues that TA, a form of lossy compression, is basic useless in forecasting market prices. I tend to agree, based on statistical analysis of market time series' which show that price histories are basically "random walks" in which the past does not predict the future, at least not in any straightforward way. (Perhaps successful traders who use TA have developed an intuition about market movements that goes beyond the TA they're using.)
This is why I favor methods grounded in modern statistics, such as statistical arbitrage which allows traders to assemble portfolios that have better statistical properties for forecasting future price movements.