One problem with many of the methods commonly used to identify trends is that risk confuse trends with volatile markets. The method described in the paper below claims to avoid such problems. http://www.eurekahedge.com/news/attachments/Amplitude_Examining_Trend_Characteristics.pdf
"The TI(n) for a specific time t is calculated by doing a linear regression on the n minutes around t (n/2 before t and n/2 after)." Oops. There goes its applicability to trading, which is a real-time application that naturally doesn't allow peeking into the future. IMO the best public domain trend indicators are still Kaufman's Efficiency Ratio and Blau's TSI, but of course they have their flaws as well.
All you eyeball guys crack me up. Try doing that for scores of instruments every trading day for the rest of your trading lives. There's a reason why machines and other technologies are sooo popular world-wide.
Ya if i want to know the trend or lack of I just look at the timeframe im trading and draw some channels using my eyes, nothing will ever top that. I get it.... Now try it for thousands of instruments FoN
Of course. In that case, the eyeball works great without danger of overworking it. But not everyone watches only a single instrument either.
Well, trend indicators needs some kind of window over which the trend is calculated. They just state that the trend estimate is calculated for the center point of the interval. It is trivial to adjust to only use historical data points and use the regression estimate as an indicator. The big concern is whether at all this indicator could say anything about the continuation of the trend.
I totally agree. Here's where they lose me. It seems senseless to decide to include an arbitrary point (e.g., the center point) in a linear regression. Frankly I question the whole logic of using a linear regression, given that the vast majority of trends are nonlinear, but maybe that's just me. Fortunately there's more than one way to approach the measurement of trends.