Variations Index - Indicator for MetaTrader 4

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Uploaded: 10.10.2008
Content: ivar.rar (1,31 kB)

Description

Index variation - an indicator for MetaTrader 4 shows that prevails in the time series - trend or to the flat component, or a series of acts by accident.

General rules for the application of the following indicators:
The indicator value below 0.5 indicates a trend market conditions.
Extremely low value often precedes the end of the (correct) of the current trend of.
The indicator value above 0.5 means fletovoe market conditions.
Extremely high value often precedes the onset of significant trends.
The indicator value in the region of 0.5 means an uncertain market conditions.

Currently, the most popular representatives of the fractal time functions are financial time series.

The fractal structure of these series are well known and, according to Mandelbrot, is a "restatement of the well-known market saying that the movement of shares or currency is quite similar, regardless of the scale of time and price. The observer can not tell by appearance schedule, whether the data to weekly, daily or hourly changes. "

To determine the fractal dimension is usually calculated Hurst [2]. However, for a reliable calculation of this indicator requires:

- Large volume of data that is too much compared to the duration of traded trends.


The author introduces a new fractal characteristics - the index variation (m), is closely associated with the conventional fractal dimension.

In contrast to the Hurst exponent to determine the index variation requires data on two orders of magnitude smaller. This leads to the possibility of using it as a local characteristic, which determines the dynamics of the price series. In this case m <0.5 can be interpreted as a trend,
and the case of m> 0.5 - as a flat.

The proposed indicator calculates the index variations on the length of the preceding interval. The parameters set by the user.

Literature:

1. MM Dubovikov et al. - The dimension of the minimum coverage and local analysis of fractal time series, 2004.

2. Edgar E. Peters, Fractal Market Analysis. Applying Chaos Theory to Investment and Economics, John Wiley & Sons, 2003.

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